System and method for fuzzy concept mapping, voting ontology crowd sourcing, and technology prediction

• US 11,080,336 B2
• Filed: 09/13/2016
• Issued: 08/03/2021
• Est. Priority Date: 08/29/2012
• Status: Active Grant

• Current Assignee: Dennis Van Dusen
• Original Assignee: Dennis Van Dusen
• Inventors: Van Dusen, Dennis
• Primary Examiner(s): Lin, Kenny S
• Application Number:
  US15/263,373
• Publication Number:
  US 20170235848A1
• Time in Patent Office: 1,785 Days
• Field of Search: None
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 16/904 Browsing; Visualisation therefor for navigating the web G06F16/954; browsing optimisation for the web G06F16/957
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 2220/12 Usage or charge determination
• CPC Class Codes: G06Q 2230/00 Voting or election arrangements
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0279 Fundraising management
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06Q 50/18 Legal services
• CPC Class Codes: G06Q 50/184 Intellectual property management
• CPC Class Codes: G06Q 50/20 Education
• CPC Class Codes: G07C 13/00 Voting apparatus
• CPC Class Codes: H04L 41/04 : Network management architectures or arrangements

Abstract

The invention provides a system and method for providing ttx-based categorization services and a categorized commonplace of shared information. Currency of the contents is improved by a process called conjuring/concretizing wherein users'"'"' thoughts are rapidly infused into the Map. As a new idea is sought, a goal is created for a search. After the goal idea is found, a ttx is concretized and categorized. The needs met by such a Map are prior art searching, competitive environmental scanning, competitive analysis study repository management and reuse, innovation gap analysis indication, novelty checking, technology value prediction, investment area indication and planning, and product technology comparison and feature planning.

Claims

1. A computer-implemented method to make available a commonplace of information, comprising:

a. providing a computer storage to hold information added to the commonplace of information comprising a plurality of cnxpts representing concepts and at least one association representing a relationship between concepts represented by cnxpts among the plurality of cnxpts;

b. defining a knowledge model comprising a set of zero or more fxxts based on the information stored regarding the plurality of cnxpts and the at least one association, fulfilling at least one condition selected from the group of;

no association is marked with a fxxt, no cnxpt is marked with a fxxt, at least one cnxpt is marked with at least one fxxt, and at least one cnxpt participates in one or more associations marked with at least one fxxt;

c. generating, using a map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to zero or more associations and zero or more cnxpts into the derived ontology;

d. generating, using said map definition referencing the set of zero or more fxxts, a skeletal structure for a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map skeletal structure of said map instance is based upon a manner of analysis selected from the group of;

a spanning forest manner, a descendent forest manner, an enhanced descendent forest manner, an ascendant forest manner, an enhanced ascendant forest manner, and a structure comprising a combination thereof;

e. generating, using said map definition referencing the set of zero or more fxxts, one or more organizations of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly selected from the group of;

a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, a directed graph manner, a graph manner, a horizontal manner, a depth augmented manner, a time augmented manner, a purlieu augmented manner, and a structure comprising a combination thereof;

wherein vertical and horizontal are mere duals for labeling in combinations;

and

f. providing to the user said one or more domains of wisdom for utilization in a form selected from the group of;

i. providing access to the data contained in said one or more organizations of knowledge for one or more domains of wisdom of said map instance for utilization directed at a solution of a problem the user is considering;

and

ii. displaying a visual derivative of said one or more organizations of knowledge for one or more domains of wisdom of said map instance to a user, the displayed visual derivative of said map comprising at least one of;

a categorization, a classification, an index tool for accessing indexed information, a dynamically refreshed associative search tool, a personal perspective associative search tool, a compound topic non-classification personal perspective associative search tool, a sub-topic relevance based search tool, a non-indexed dynamically refreshed external information sub-topic relevance based associative search tool with alerting, an ideating tool, an organizer, a planner, a table of information, a book of information, a document authoring tool, a document management and retrieval tool, a budget structure, a personal perspective adaptive dynamic structured report structure manager tool for spreadsheet users, a search memory holder, an organizing tool, a harmonized classification tool, an adaptive dynamic classification index preservation tool, a personal perspective adaptive dynamic classification index preservation tool, a personal perspective adaptive dynamic search-refreshing classification index preserving information access tool, an innovation assistant, a subject-specific communication tool, a subject managing communication tool, a compartmentalized security linked information protection access tool, a tool for managing structures within spreadsheets, a tool for managing idea specific organizational communications, a management tool for idea-centric commercial transactions, a communal tool to foster idea extension, a machine learning supervising tool, a portfolio manager, a personal perspective adaptive dynamic classification index preservation portfolio analysis tool, an ordering, a precedence presentation, a view of a machine learning result, a structured data model, a type to sub-type presentation, a related information associative search tool, a modeling basis, a knowledge map, a predicting basis, an assembly process map, a mapping appropriate to a user application according to a user decision, a mind map, a task plan, a workflow, a project structure, an evaluation map, a decision tree, a Bayesian network, a trait based associative search tool, a causality network, a neuron map, a patent map, a technology map, a product line map, a personal perspective decision analysis presentation, a prospective perspective decision analysis presentation, a dynamic personal perspective audience interest recommender analysis tool, a fact to legal element mapping, an evidence to legal element mapping, a sequence structure, a strategic plan, a curriculum, a futures analysis, a plan, a procedure, a proof structure presenter, a ranking list, a competitive environment presentation, a strategic direction under uncertain competitive pressure and technology uncertainty expected return planning tool, a belief polling tool, an intelligence collection tool, a rapid response supervised collaborative collection uncertain provenance intelligence response effectiveness analysis tool, a data product subscription manager, a technology transfer supervision tool, a patent clearance operations manager, an intellectual property leak detecting loss analysis tool, an ontology manager, a complex organization general ledger, a skills list, a dynamic skills list showing training needs, a language mapping, a patent claim tree, a detailed prior art search manager, a detailed dynamic search prior art search manager, a classification-expansive dynamic prior art enumeration showing prospective prior art for minimally described prospective concepts, a business progress rating presentation, a mapping demarcating what is known from that which is unknown at any point in time, a branching diagram, a logic diagram, a legal case presentation, a computation derivation map, a method map, a product line formation analysis tool, a product feature set manager, a technology product gap finder, a hot investment area finder, a product development coordination tool, a product potential analysis, and a combination tool formed from two or more of the foregoing directed at a solution of a problem the user is considering;

whereby one or more domains of wisdom are formed by collections of references to cnxpts and references to zero or more associations among cnxpts.

2. The method of claim 1, further comprising:

a. accepting a command regarding a definition of a cnxpt from a user selected from the group of;

an info-item addition command defining a new cnxpt without parameters stated, an info-item addition command defining a new cnxpt along with stated parameters, an info-item change command refining the cnxpt definition, and an info-item change command refining stated parameters regarding the cnxpt definition;

b. accepting with said command regarding said cnxpt definition a cnxpt identity value of type selected from the group of;

a lack of value specifying to use a system generated identity, a parameter value acceptable as an identity, a form fill-in value acceptable as an identity, and a value acceptable as an identity that is acceptable to the user interface;

c. accepting with said command regarding said cnxpt definition an object typing selected from the group of;

classless, class, class instance, dynamic class with a defined cnxpt nature as specified by a given match of specified values held in zero or more specified cnxpt properties of an instance to be considered a member of the dynamic class;

d. accepting with said command regarding said cnxpt definition zero or more cnxpt identity values of type;

e. accepting zero or more actions affecting the nature of the cnxpt, the action selected from the group of;

i. assigning to said cnxpt a role on an association;

ii. assigning to said cnxpt a role on an association, the association being newly created in the operation wherein a second cnxpt identity is specified to hold a role on the opposing end of the association;

iii. marking said cnxpt with a fxxt;

iv. assigning to said cnxpt, wherein said cnxpt is a class, zero or more class properties, zero or more behaviors, zero or more roles, and zero or more fxxt markings;

v. assigning a cnxpt class property to a class of which said cnxpt is an instance, said property in said cnxpt given a default value inherited from the cnxpt defining the cnxpt class;

vi. assigning said cnxpt to a cnxpt class, wherein said cnxpt is a class;

vii. assigning to said cnxpt, wherein said cnxpt is a class, zero or more class properties, zero or more behaviors, zero or more roles, and zero or more fxxt markings to the class defined by said cnxpt, said class properties, behaviors, roles, and fxxt markings inheritable by cnxpt instances of the class, wherein properties that are inherited by the instances of the class that are new to the instance would be assigned to the instance and given a default value as stated in said cnxpt, wherein new associations are generated where the role at the opposing end of the association at the class level is copied to the new association but the role of the class cnxpt on the class level association is not copied, the role of the class replaced by said cnxpt on the new association, wherein the new association inherits as initial property values those values of the properties of the association at the class level, said cnxpt remaining an instance of the class if not removed from the class;

viii. assigning to said cnxpt a cnxpt class defined by a class cnxpt, effecting inheritance into said cnxpt as an instance of the cnxpt class, of zero or more class-defined properties, zero or more class-defined behaviors, zero or more class-defined roles, and zero or more markings of fxxt membership of the cnxpt class, wherein properties that are inherited by said cnxpt that are new to said cnxpt would be assigned to said cnxpt and given a default value as stated in the cnxpt defining the class, wherein new associations are generated where the role at the opposing end of the association at the class level is copied to the new association but the role of the class cnxpt on the class level association is not copied, the role of the class replaced by said cnxpt on the new association, wherein the new association inherits as initial property values those values of the properties of the association at the class level, said cnxpt remaining an instance of the class if not removed from the class;

ix. assigning a value to a property of said cnxpt causing said cnxpt to become a member instance of a dynamic class defined by a class cnxpt, effecting inheritance into said cnxpt as an instance of the cnxpt class, of zero or more class-defined properties, zero or more class-defined behaviors, zero or more class-defined roles, and zero or more markings of fxxt membership of the cnxpt class, wherein new associations are generated where the role at the opposing end of the association at the class level is copied to the new association but the role of the class on the class level association is not copied, the role of the class replaced by said cnxpt on the new association, wherein the new association inherits as initial property values those values of the properties of the association at the class level, said cnxpt remaining an instance of the class while said property holds a value conforming to the requirements of the dynamic class;

x. triggering calculation of cnxpt methods of said cnxpt, wherein a value resulting from the calculation is assigned to a property of said cnxpt;

xi. triggering calculation of cnxpt methods of said cnxpt, wherein a value assigned to a property of said cnxpt by the calculation causes conformance of said cnxpt to the membership requirements of a dynamic class defined by a class cnxpt to become a member instance of the dynamic class, effecting inheritance into said cnxpt as an instance of the cnxpt class, of zero or more class-defined properties, zero or more class-defined behaviors, zero or more class-defined roles, and zero or more markings of fxxt membership of the cnxpt class, wherein new associations are generated where the role at the opposing end of the association at the class level is copied to the new association but the role of the class on the class level association is not copied, the role of the class replaced by said cnxpt on the new association, wherein the new association inherits as initial property values those values of the properties of the association at the class level, said cnxpt remaining an instance of the class while said property holds a value conforming to the requirements of the dynamic class;

xii. assigning to said cnxpt a value of a property, wherein the value causes said cnxpt to become a marked member of a fxxt if the value conforms to the requirements of the fxxt, said cnxpt remaining a marked member of the fxxt while said property holds a value conforming to the requirements of the fxxt;

xiii. triggering calculation of cnxpt methods of said cnxpt, wherein a value assigned to a property of said cnxpt by the calculation causes said cnxpt to satisfy the membership requirements of a fxxt if the value causes conformance to the requirements of the fxxt, said cnxpt remaining a marked member of the fxxt while said property holds a value conforming to the requirements of the fxxt;

xiv. assigning a fxxt marking to said cnxpt, wherein said cnxpt is a class, causing said cnxpt and instances of the class defined by said cnxpt to become marked members of the fxxt, said cnxpt and instances of the class defined by said cnxpt remaining marked by the fxxt while said fxxt marking remains on said cnxpt;

xv. altering the membership requirement of a cnxpt dynamic class of which said cnxpt is a class member instance by changing one or more values required to be held by class member instances, said cnxpt considered an instance of the cnxpt dynamic class unless said cnxpt no longer satisfies the membership requirement;

xvi. marking said cnxpt with a fxxt, wherein said cnxpt is a class, wherein all member instance cnxpts of the class become marked by the fxxt while the marking of said cnxpt remains;

xvii. assigning a calculation equation to said cnxpt as a method for obtaining a value for a cnxpt property of said cnxpt, the equation referencing zero or more cnxpt properties of said cnxpt and zero or more cnxpt properties of zero or more other cnxpts;

xviii. triggering calculation of cnxpt methods of said cnxpt, wherein a value resulting from the calculation is utilized in a model;

xix. assigning a modeling variable to said cnxpt as a cnxpt property;

xx. assigning said cnxpt to a fuzzy cnxpt class with a fuzziness given by a probability density function;

xxi. assigning said cnxpt to a fuzzy cnxpt class with a fuzziness given by value of a property of said cnxpt;

xxii. assigning to said cnxpt a value for a property;

xxiii. assigning to said cnxpt a cnxpt property value an existence fuzziness probability density function selected from the group of;

the value of a fuzziness probability density function property of said cnxpt, a likely existence start area boundary, a likely existence end area boundary, a likely existence start area boundary under a condition, and a likely existence end area boundary under a condition, a value constant, a value held by a property, a calculated value given by an equation of a method;

xxiv. assigning to said cnxpt an existence fuzziness probability density function selected from the group of;

the value of a fuzziness probability density function property of said cnxpt, a likely existence start time frame, a likely existence end time frame, a likely existence start time frame under a condition, and a likely existence end time frame under a condition;

said existence fuzziness probability density function as represented by a cnxpt property;

xxv. assigning to said cnxpt a timing selected from the group of;

an epoch that the cnxpt represents, a time frame of said cnxpt, a time frame property of said cnxpt, a likely existence time frame, a preferred start time frame, a preferred end time frame, an actual start time frame, an actual end time frame, a time frame of a custom type, a time frame of a purpose represented by a variable property of said cnxpt, a deadline time frame, a patent protection end date, a next milestone time frame, a likely realization time frame, a preferred completion time frame, and a preferred obsolescence time frame;

xxvi. assigning to said cnxpt a location selected from the group of;

a location that the cnxpt represents, a purlieu of said cnxpt, a purlieu property of said cnxpt, a likely existence area, a preferred initial reference area, a preferred demise reference area, an actual initial reference area, a actual demise reference area, a location of a custom type, a location of a purpose represented by a variable property of said cnxpt, a destination location, a patent jurisdiction location, a next landmark location, a likely final landmark location, and a preferred completion landmark location;

xxvii. assigning to said cnxpt a workflow state selected from the group of;

a workflow status value representing a workflow state, a workflow state represented by a second cnxpt, a workflow state represented by a time frame, a workflow state represented by a epoch, a workflow state represented by a purlieu, a workflow state represented by a boundary, a workflow state represented by a landmark, a workflow state represented by an info-item, and a workflow state resolved upon request by computing a state using a probability density function defined over a range of one or more workflow states as represented by a cnxpt property value stating a domain of workflow states;

xxviii. altering the fxxt marking of an association on which said cnxpt holds a role to add said association to said fxxt wherein said cnxpt has a defined cnxpt nature as specified by a given match of specified values held in zero or more specified properties of said cnxpt to be considered a marked member of the fxxt;

xxix. assigning to said cnxpt one or more knowledge representation natures.

xxx. add information resource to said cnxpt as an occurrence;

xxxi. add reference to ttx from said cnxpt;

xxxii. add reference to ttx entry from said cnxpt;

xxxiii. navigate to said cnxpt;

xxxiv. adding said cnxpt to a result set;

xxxv. adding a result set to said cnxpt in connection with a search;

xxxvi. adding said cnxpt to an area of interest;

xxxvii. moving said cnxpt to appear as a child of a different cnxpt;

xxxviii. causing the adding of a vote for a hierarchical association;

xxxix. removing said cnxpt from a role on an association, the association being deleted in the operation;

xl. replacing a cnxpt having a role on an association by said cnxpt to take over the role on the association;

xli. removing said cnxpt from a cnxpt class, wherein the zero or more class properties inherited from the cnxpt class are removed from said cnxpt if the value in the property was never changed from the default assigned when said cnxpt was made an instance of the cnxpt class, wherein the zero or more class methods inherited from the cnxpt class are removed from said cnxpt if the method definition stored in said cnxpt was never overridden in said cnxpt, wherein the zero or more fxxt markings inherited from the cnxpt class are removed from said cnxpt if said cnxpt never assigned explicitly to the fxxt other than by inheritance, wherein the zero or more roles inherited from the cnxpt class and the association where the role is are removed from said cnxpt if said cnxpt never assigned explicitly to the role other than by inheritance;

xlii. changing a value of a property of said cnxpt causing said cnxpt to be removed as a member instance of a dynamic class;

xliii. changing a value of a property of said cnxpt causing said cnxpt to be removed as a marked member of a fxxt;

xliv. removing said cnxpt from a fxxt;

xlv. removing a cnxpt method from said cnxpt;

xlvi. removing a cnxpt property from said cnxpt;

xlvii. changing the value of a property of said cnxpt;

xlviii. changing the equation of a method of said cnxpt;

xlix. changing the definition of a method of said cnxpt;

l. removing a method from said cnxpt;

li. changing a fuzziness given by a probability density function for determining membership of said cnxpt in a fuzzy cnxpt class;

lii. removing a cnxpt property serving as a modeling variable from said cnxpt;

liii. removing a modeling calculation equation from said cnxpt;

liv. changing a modeling calculation equation of said cnxpt;

lv. changing on said cnxpt a value to an instance variable to serve as an identity resolver of said cnxpt when the identity of the class is provided;

lvi. removing the fxxt marking of an association on which said cnxpt holds a role to remove said association from a fxxt wherein cnxpt instances in the role have a specific cnxpt nature as specified by a given match of specified values held in zero or more specified cnxpt properties;

lvii. vote regarding an occurrence to said cnxpt;

lviii. vote regarding a reference to ttx from said cnxpt;

lix. vote regarding a reference to ttx entry from said cnxpt;

lx. vote regarding the appropriateness of appearance of said cnxpt in a map;

lxi. vote regarding the placement of said cnxpt in a result set;

lxii. culling a result set of said cnxpt;

lxiii. vote regarding the placement of said cnxpt in an area of interest;

lxiv. vote regarding the parentage of said cnxpt by a different cnxpt;

and

lxv. vote regarding the role of said cnxpt in a hierarchical association.

3. The method of claim 2, to include additional knowledge regarding affinity of cnxpts, further including:

a. determining info-item membership in a resultant fxxt by interpreting one or more rules selected from the group of;

i. info-item access and retention rules;

ii. weighting heuristic rules;

iii. ordering heuristic rules;

iv. ontology combination rules;

v. fxxt combination rules;

and

vi. rules allowing consideration of an association when an option of the map is set to a specified value, wherein the association would not be in the map otherwise, wherein the association states an affinitive relationship between two cnxpts in the map, wherein the association is only used for its weighting to show an affinity between said two cnxpts holding roles on the association, wherein the association weight is multiplied by a coefficient stated in the map if the coefficient is set to a value, wherein the resultant value is accumulated for use during roll-up generation.

4. The method of claim 1, to extract a derived ontology subset of the commonplace of information to provide a domain of wisdom basis for a map, further comprising:

a. detailing a map definition;

b. detailing zero or more fxxt specification steps defining a fxxt;

c. registering, regarding said map definition, resolved values for zero or more parameters;

d. determining user identity;

e. accepting from the map definition representing a knowledge model of a domain of wisdom a set of zero or more fxxt instances each fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value;

f. creating, a new empty named derived ontology to hold references to extracted instances and classes of info-items;

the resulting said named derived ontology assigned to the user causing the extraction by requesting the map, and said named derived ontology named by said new resultant fxxt by identity;

said named derived ontology assigned to reside in computer storage allocated to store information comprising a domain of wisdom forming the basis of the map;

said named derived ontology when filled to be comprised of a plurality of references to info-items, cnxpt instances and association instances among the plurality of cnxpt instances where each association instance states directionality and includes a weight indicating a strength of the association instance of a type selected from the group of;

a predefined default value for weights not stated, a value, a placeholder for a value, and an equation;

each cnxpt instance including a weight indicating importance of the cnxpt instance of a type selected from the group of;

a predefined default value for weights not stated, a value, a placeholder for a value, and an equation, each info-item instance including a weight indicating importance of the info-item instance of a type selected from the group of;

a predefined default value for weights not stated, a value, a placeholder for a value, and an equation;

g. interpreting said map definition;

further including;

i. accepting for processing a definition of a first map listing zero or more fxxts stating sources of wisdom to be referenced as contents in the map;

ii. resolving values for zero or more parameters for processing of said first map;

iii. accepting for analysis, if said map definition lists any fxxt, a first specification step of a first fxxt instance defining tasks to perform for said first fxxt instance;

iv. resolving, if said map definition lists no fxxt, a null fxxt identity, setting inherited from said map definition, and values present or default values for parameters fxxt-free mode fxxt extraction;

v. resolving, if said map definition lists any fxxt, values for zero or more parameters of said first specification step of said first fxxt instance;

and

vi. registering, if said map definition lists any fxxt, for proper later invocation zero or more fxxt specifications;

h. creating a plurality of temporary lists, further including;

i. creating an empty list of classes instantiated during extraction based upon said map definition;

ii. creating one or more empty temporary class lists of cnxpt classes containing tuples referencing one cnxpt class per tuple;

iii. creating one or more empty temporary class lists containing tuples, referencing one association class per tuple, the tuple referencing the cnxpt instance or class in each role;

iv. creating one or more empty temporary mixed lists containing tuples, referencing one association instance per tuple, each association instance with at least one role occupied by a cnxpt class, the tuple referencing the cnxpt instance or class in each role;

v. creating one or more empty temporary class lists containing tuples, referencing one non-cnxpt, non-association info-item class per tuple;

vi. creating one or more empty temporary instance lists containing tuples, referencing one cnxpt instance per tuple;

vii. creating one or more empty temporary instance lists containing tuples, referencing one association instance per tuple, the tuple referencing the cnxpt instance or class in each role;

and

viii. creating one or more empty temporary instance lists containing tuples, referencing one non-cnxpt, non-association info-item instance per tuple;

i. creating one or more temporary derived ontologies, setting an accumulated contextual coefficient indicating proportionality of impact for each temporary derived ontology to a default value, further including;

i. defining a new empty temporary derived ontology;

said temporary derived ontology assigned a new temporary fxxt identity;

said temporary derived ontology assigned to reside in computer storage;

and

ii. structuring said temporary derived ontology commonplace to register new references to info-item classes, info-item instances, cnxpt classes, cnxpt instances, association classes, and association instances from said commonplace, wherein each reference to a non-association info-item instance or class states a weight indicating importance of the info-item instance or class of a type selected from the group of;

a predefined default value for weights not stated, a value, a placeholder for a value, and an equation;

j. preparing for triggered processing for membership testing for info-items into said named derived ontology of the commonplace of information by interpreting a first specification step of a first fxxt instance listed on said map definition where at least one satisfaction exists of conditions selected from the group consisting of;

said map definition states its treat-as-trigger-able setting as affirmative, said first fxxt instance is defined to be trigger-able, said first fxxt specification step is marked as trigger-able, said first fxxt specification step that has been determined to be trigger-able, and said first fxxt specification step that has been determined to be not-easily-determined;

further including;

i. accepting for processing said first specification step of said first fxxt instance defining tasks to perform for said first fxxt instance;

ii. resolving values for zero or more parameters of said first specification step of said first fxxt instance;

and

iii. registering for proper later invocation zero or more fxxt specifications observed;

k. determining membership of an info-item reference in said named derived ontology of the commonplace of information where there are zero or more first fxxts specified on said map definition, by one or more observations before forest extraction is attempted, by detecting a mode for fxxt specification processing by one or more observations, the observations selected from the group of;

i. that fxxt-free mode is requested in said map definition and at least one first info-item in said commonplace is not marked by any second fxxt, is of a type selected from the group of;

cnxpt, association, and type given by info-item type inclusion parameter;

further including;

01. calculating an initial value for the accumulated contextual coefficient indicating proportionality of impact based upon a rule;

02. recording into said named derived ontology each info-item reference of said at least one first info-item;

and

03. recording into said named derived ontology each info-item reference of said at least one first info-item class where extract-classes mode is active;

ii. that a second fxxt member of said set of at least one fxxt referenced in said map definition marks, by a method selected from the group of;

directly marking due to fxxt specification having no defined specification steps, and interpreting fxxt specification step directly prescribing a marking;

zero or more first info-items in a configuration selected from the group of;

map definition specifying extract-classes mode and first info-item is a class, map definition specifying extract-classes mode and first info-item is an association instance having a role occupied by a cnxpt class, fxxt specification step specifying extract-classes mode and first info-item is a class, fxxt specification step specifying extract-classes mode and first info-item is an association instance having a role occupied by a cnxpt class, and first info-item is an instance other than an association instance having a role occupied by a cnxpt class or a relation instance having a role occupied by an info-item class;

said second fxxt providing a grant to such a user to allow utilization of said first info-item instances or no lockout affecting such a user access, said second fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value;

further including;

01. calculating an initial value for the accumulated contextual coefficient indicating proportionality of impact;

02. recording into instance lists by collecting instances;

and

03. recording into class lists by collecting classes where extract-classes mode is active;

iii. that a first fxxt specification step in the definition of a first fxxt member of said set of at least one fxxt referenced in said map definition prescribes an operation type selected from the group of;

a specification step stating an equation yielding upon recursive evaluation the identity of one or more second fxxts having no defined specification steps, a specification step stating a query yielding upon recursive evaluation the identity of one or more second fxxts having no defined specification steps, a specification step stating an equation yielding upon recursive evaluation the identity of one or more second fxxts having a defined specification step directly prescribing a marking, and a specification step stating a query yielding upon recursive evaluation the identity of one or more second fxxts having a defined specification step directly prescribing a marking;

said second fxxt providing a grant to such a user to allow utilization of the info-items or no lockout affecting such a user access;

said second fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value;

said operation not specifying any fxxt combination operation other than a union by addition of further info-items to the resulting extracted ontology;

further including;

01. enqueueing for said first fxxt specification step an entry into a fxxt list the set of all second fxxts found stemming from said first fxxt specification step;

and

02. processing in turn each queued second fxxt found stemming from said first fxxt specification step that marks, by a method selected from the group of;

directly marking due to fxxt specification having no defined specification steps, and interpreting fxxt specification step directly prescribing a marking;

zero or more first info-items in a configuration selected from the group of;

map definition specifying extract-classes mode and first info-item is a class, map definition specifying extract-classes mode and first info-item is an association instance having a role occupied by a cnxpt class, fxxt specification step specifying extract-classes mode and first info-item is a class, fxxt specification step specifying extract-classes mode and first info-item is an association instance having a role occupied by a cnxpt class, first info-item is an instance other than an association instance having a role occupied by a cnxpt class or a relation instance having a role occupied by an info-item class, and specific instances;

wherein access to marked info-items is allowed based upon a rule selected from the group of;

allowed according to said first fxxt and not locked out by said second fxxt, allowed according to said first fxxt and not locked out by said second fxxt, allowed according to said first fxxt and allowed according to said second fxxt, and not locked out by said second first or said second fxxt;

said first fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value;

said second fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value;

iv. that a first fxxt specification step in the definition of a first fxxt member of said set of at least one fxxt referenced in said map definition prescribes an operation type selected from the group of;

a specification step stating an equation yielding upon recursive evaluation a query, a specification step stating a query yielding upon recursive evaluation a query, a specification step stating an equation yielding upon recursive evaluation a query, and a specification step stating a query yielding upon recursive evaluation a query;

said second fxxt providing a grant to such a user to allow utilization of the info-items or no lockout affecting such a user access;

the search query to result in a list of info-items selected from the group of;

info-item classes, info-item instances, cnxpt classes, cnxpt instances, association classes, and association instances;

said query stating criteria arguments or resolvable parameters to allow searching of a type selected from the group of;

text field, text description, language, name, identity, property value, attribute value, scopx, infxtypx, txo type, weight, info-item type, presence of an attached entity, feature set, state of selection by user, result of assessment by analytic, state of membership in list or set, current or prior position in visualization, trait, occurrence information, association role type, association role fulfillment, relationship role type, relationship role fulfillment, existence in an area, existence in a time frame, membership in indicated list, membership in stated list, inclusion in an indicated map, categorization as stated by an indicated map, value within one or more ranges, membership of property value in a stated list, membership of property value in a named list, fxxt identity list, inverse extension, base fxxt marking, ownership by user, ownership by organization, usage by user, alteration by user, having an approval, satisfying a query in a query language, alteration by organization, creation date, change date, value range of function involving property, status, permission, protection level, status as child in specific relationship type, status as parent in specific relationship type, class membership, relative position in a list, position in an ordering by a property or a time reference attribute, a specific value or a null value for some attribute within a description field, having a workflow status, a level of interest shown, a degree of similarity, satisfying a statistical criteria, passing a custom test, existence of an attribute within a description, a value in an attribute of another info-item meeting a comparison criteria;

having a specified rating, satisfying a Boolean test, having a specified combination of properties and infxtypxs, having a specified combination of properties and scopxs, holding a queue position, membership in an ontology, membership in a directory, membership in a taxonomy, passing a cypher test, having a specified combination of attributes, a membership test, a Boolean combination of the foregoing, and a defined combination of the foregoing;

wherein when the search query is fully resolved a non-null set of info-items from said commonplace are found, said info-items being treated as if they were marked by said second fxxt and access to the info-items is allowed for such a user based upon a rule selected from the group of;

allowed according to said second fxxt and not locked out by said second fxxt, allowed according to said second fxxt and allowed according to every fourth fxxt marking the info-item and not locked out by said second fxxt or any fourth fxxt marking the info-item, allowed according to said second fxxt and not locked out by said second fxxt or any fourth fxxt marking the info-item, and not locked out by any fourth fxxt marking the info-item;

said second fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map selected from the group of;

a stated value, a value stated in the map definition, a formula resolving to a value when accessed, and a default value; and

not specifying any fxxt combination operation other than a union by addition of further info-items to the resulting extracted ontology, further including;

01. calculating an initial value for the accumulated contextual coefficient indicating proportionality of impact;

02. recording into instance lists by collecting instances;

and

03. recording into class lists by collecting classes where extract-classes mode is active;

and

v. that a first fxxt specification step in the definition of a first fxxt member of said set of at least one fxxt referenced in said map definition prescribes an operation on a domain;

l. producing into the resulting said named derived ontology by repeating until no classes remain in any temporary instance or class list, the named derived ontology generation process, further including;

i. generating into said first temporary derived ontology a first set of zero or more unique references to cnxpt instances based upon tuples in said first temporary instance list of cnxpt instances;

ii. generating into said first temporary derived ontology a first set of zero or more unique references to association instances based upon tuples in said first temporary instance list of association instances;

iii. generating into said first temporary derived ontology a first set of zero or more unique references to non-cnxpt, non-association info-item instances based upon tuples in said first temporary instance list of non-cnxpt, non-association info-item instances;

iv. instantiating into said first temporary instance list of cnxpt instances a set of second tuples for each first tuple in said first temporary class list of cnxpt classes upon an affirmative of observation regarding extraction mode selected from the group of;

extract-classes mode is active and expand-classes mode is active, and extract-classes mode is not active and expand-classes mode is active;

v. instantiating new tuples where the map definition or the fxxt specification step specifies extract-classes mode from tuples in first temporary class list of association classes to tuples in first temporary instance list of association instances upon an affirmative of observation regarding extraction mode selected from the group of;

expand-classes mode is active;

vi. instantiating new tuples from tuples in first temporary mixed list of association classes to tuples in first temporary instance list of association instances upon an affirmative of observation regarding extraction mode selected from the group of;

expand-classes mode is active;

vii. instantiating into said first temporary instance list of association instances a set of second tuples for each first tuple in said first temporary mixed list of association instances by instantiating to tuples in first temporary instance list of association instances upon an affirmative of observation regarding extraction mode selected from the group of;

expand-classes mode is active;

viii. instantiating into said first temporary instance list of non-cnxpt, non-association info-item instances a set of second tuples for each first tuple in said first temporary class list of non-cnxpt, non-association info-item classes upon an affirmative of observation regarding extraction mode selected from the group of;

extract-classes mode is active and expand-classes mode is active, and extract-classes mode is not active and expand-classes mode is active;

ix. generating into said first temporary derived ontology a first set of zero or more unique references to cnxpt classes based upon tuples in said first temporary class list of cnxpt classes upon an affirmative observation selected from the group of;

expand-classes mode is not active and extract-uninstantiated-classes mode is active;

x. generating into said first temporary derived ontology a first set of zero or more unique references to association instances and into said second temporary derived ontology a first set of zero or more unique references to cnxpt classes based upon tuples in said first temporary mixed list of association instances only where the association instances having a cnxpt class already in a role upon an affirmative observation selected from the group of;

expand-classes mode is not active and extract-uninstantiated-classes mode is active;

xi. generating into said first temporary derived ontology a first set of zero or more unique references to association classes and into said second temporary derived ontology a first set of zero or more unique references to cnxpt classes based upon tuples in said first temporary class list of association classes only where the association classes having a cnxpt class already in a role upon an affirmative observation selected from the group of;

expand-classes mode is not active and extract-uninstantiated-classes mode is active;

xii. resolving class entries based upon an observation selected from the group of;

the map definition specifies that extract-classes mode is active and expand-classes mode is active, the fxxt specification step specifies that extract-classes mode is active and expand-classes mode is active, and the map definition or the fxxt specification step specifies extract-classes mode and the map definition or the fxxt specification step specifies expand-classes mode during extraction;

merging into said named derived ontology the set of references to second association instances in said named derived ontology and the set of references to first association instances in said first temporary derived ontology by combining all references to any same association instance into one reference with a weight summed from all of the references to the same association instance, yielding a set of unique weighted references to unique association instances in said named derived ontology; and

removing all references to info-items from any temporary derived ontology that were merged into said named derived ontology;

xiii. moving classes to temporary class lists;

and

xiv. generating into said first temporary derived ontology a first set of zero or more unique references to non-cnxpt, non-association info-item classes based upon tuples in said first temporary class list of non-cnxpt, non-association info-item classes upon an affirmative observation selected from the group of;

expand-classes mode is not active and extract-uninstantiated-classes mode is active;

m. merging into said named derived ontology the summarized references in every temporary derived ontology;

n. performing, prior to release of the resulting said named derived ontology to forest extraction and until no changes are made to the resulting said named derived ontology and one or more conditions are satisfied from conditions selected from the group of;

said map definition states its treat-as-trigger-able setting as affirmative and a fifth fxxt listed on said map definition has a sixth fxxt specification step, a fifth fxxt listed on said map definition has a sixth fxxt specification step that is marked as trigger-able, a fifth fxxt listed on said map definition has a sixth fxxt specification step that has been determined to be trigger-able, and a fifth fxxt listed on said map definition has a sixth fxxt specification step that has been determined to be not-easily-determined;

triggered interpretation of each sixth fxxt specification step of each fifth fxxt to determine, recursively, membership of an info-item in the resulting said named derived ontology;

o. invoking, if one or more conditions are satisfied from conditions selected from the group of;

said map definition states its treat-as-trigger-able setting as affirmative and a fifth fxxt listed on said map definition has a sixth fxxt specification step, a fifth fxxt listed on said map definition has a sixth fxxt specification step that is marked as trigger-able, a sixth fxxt specification step of some fifth fxxt is registered for triggering, a fifth fxxt listed on said map definition has a sixth fxxt specification step that has been determined to be trigger-able, and a fifth fxxt listed on said map definition has a sixth fxxt specification step that has been determined to be not-easily-determined;

extraction of a forest on the resulting said named derived ontology;

p. annealing by triggering all trigger-able actions, repeatedly until no changes are made in the resulting said named derived ontology during a round of triggering and when one or more triggering conditions occur, the condition selected from the group of;

a change in the composition or consensus weighting of one or more associations in the resulting said named derived ontology upon a change made to the forest during forest extraction, a change in the set of or consensus weighting of one or more cnxpts in the resulting said named derived ontology upon a change made to the forest during forest extraction, a change of the forest forming during forest extraction, change of the consensus weighting of an association sufficient to require an altering of the set of associations already used for hierarchical tensor creation during forest extraction where the forest extraction is ordered by weight of association, and completion of a number of edge selections during forest extraction;

q. annealing, upon completion of forest extraction, by triggering all trigger-able actions, repeatedly until no changes are made in the resulting said named derived ontology during a round of triggering and when one or more triggering conditions occur, the condition selected from the group of;

a change in the composition or consensus weighting of one or more associations in the resulting said named derived ontology upon a change made to the forest during a necessary repeat of forest extraction, a change in the set of or consensus weighting of one or more cnxpts in the resulting said named derived ontology upon a change made to the forest during a necessary repeat of forest extraction, a change of the forest forming during a necessary repeat of forest extraction, change of the consensus weighting of an association sufficient to require an altering of the set of associations already used for hierarchical tensor creation during a necessary repeat of forest extraction where the forest extraction is ordered by weight of association, and completion of a number of edge selections during a necessary repeat of forest extraction;

r. merging, upon completion of forest extraction and all fxxt specification step interpretations, wherein the map definition has general-association-acceptance-for-affinities mode indicated, the effective affinity strengths of associations between cnxpts, pair-wise, that are not in parent to child or grandparent to child relationships in the map by adding undirected affinitive associations carrying strength weights based upon the total strength weights of all associations found between those cnxpts, by pair in the commonplace, into the resulting said named derived ontology and summarizing associations between unique pairs of cnxpts;

s. merging, where the map definition has explode-able-classes mode indicated, upon completion of forest extraction and all fxxt specification step interpretations, each cnxpt class that has been instantiated during this extraction and that is not already present in the resulting said named derived ontology, into the resulting said named derived ontology, said each cnxpt class marked as explodable rather than only displayable;

and

t. exposing to the user the fxxt identity of the resulting said named derived ontology, as a data set, holding zero or more objects of types selected from the group of;

cnxpt instances, cnxpt classes, association instances, association classes, info-item instances, info-item classes, custom entities, and tensors;

each with weights, sizing and positioning.

5. The method of claim 4 to determine a new extracted resultant derived ontology from an equation stating a boolean composite of two derived ontologies, wherein:

a. identifying a first and a second operand for an operation under consideration of said equation stating a boolean composite of two derived ontologies, in precedence order from highest to lowest, the operation selected from the group of;

i. identifying, for the highest precedence operation of said equation stating a boolean composite of two derived ontologies, the contents of a first derived ontology from a first fxxt extraction serving as a first operand and a second derived ontology from a second fxxt extraction serving as a second operand;

and

ii. identifying, for each lower precedence operation of said equation stating a boolean composite of two derived ontologies in precedence order, the contents of a first derived ontology from a first fxxt extraction serving as a and a second derived ontology from a second fxxt extraction;

b. determining a resultant derived ontology for the Boolean set operation under consideration, on operands said first derived ontology and said second derived ontology, the set operation considered selected from the group of;

i. performing a union operation, wherein;

01. generating a new first temporary derived ontology comprising a resultant association between a first cnxpt and a second cnxpt if an association between said first cnxpt and said second cnxpt exists in either of said first derived ontology from said first fxxt extraction or said second derived ontology from said second fxxt extraction, where a union Boolean set operation on said first derived ontology from said first fxxt extraction and said second derived ontology from said second fxxt extraction, wherein the resultant strength weight of the association is the sum of its strength weight from said first derived ontology if the association exists there plus its strength weight from said second derived ontology if the association exists there;

02. adding to said first temporary derived ontology a first cnxpt existing in either of said first derived ontology from said first fxxt extraction or said second derived ontology from said second fxxt extraction but where said first cnxpt is not a member of any association in either of said first derived ontology or said second derived ontology, where a union Boolean set operation is specified on said first derived ontology and said second derived ontology, wherein the resultant importance weight of said first cnxpt is the sum of its importance weight from said first derived ontology if said first cnxpt exists there plus its importance weight from said second derived ontology if said first cnxpt exists there;

ii. performing an intersection operation, wherein;

01. generating a new first temporary ontology comprising a resultant association between a first cnxpt and a second cnxpt if an association between said first cnxpt and said second cnxpt exists in both of said first derived ontology from said first fxxt extraction and said second derived ontology from said second fxxt extraction, where an intersection Boolean set operation on said first derived ontology from said first fxxt extraction and said second derived ontology from said second fxxt extraction, wherein the resultant strength weight of the association is the sum of its strength weight from said first derived ontology plus its strength weight from said second derived ontology;

02. adding to said first temporary derived ontology a first cnxpt existing in both said first derived ontology from said first fxxt extraction and said second derived ontology from said second fxxt extraction but where said first cnxpt is not a member of any association in either of said first derived ontology or said second derived ontology, where an intersection Boolean set operation is specified on said first derived ontology and said second derived ontology, wherein the resultant importance weight of said first cnxpt is the sum of its importance weight from said first derived ontology plus its importance weight from said second derived ontology;

iii. performing an exclusive-or operation, wherein;

01. generating a new first temporary derived ontology comprising a resultant association between a first cnxpt and a second cnxpt if an association between said first cnxpt and said second cnxpt exists in either but not both of said first derived ontology from said first fxxt extraction or said second derived ontology from said second fxxt extraction, where an exclusive-or Boolean set operation on said first derived ontology from said first fxxt extraction and said second derived ontology from said second fxxt extraction, wherein the resultant strength weight of the association is the strength weight from the derived ontology from where the association exists;

02. adding to said first temporary derived ontology a first cnxpt existing in either but not both of said first derived ontology from said first fxxt extraction or said second derived ontology from said second fxxt extraction but where said first cnxpt is not a member of any association in either of said first derived ontology or said second derived ontology, where an exclusive-or Boolean set operation is specified on said first derived ontology and said second derived ontology, wherein the resultant importance weight of said first cnxpt is its importance weight from said first derived ontology if said first cnxpt exists there or its importance weight from said second derived ontology if said first cnxpt exists there;

and

iv. performing a set-minus operation, wherein;

01. generating a new first temporary derived ontology comprising a resultant association between a first cnxpt and a second cnxpt if an association between said first cnxpt and said second cnxpt exists in said first derived ontology from said first fxxt extraction but not in said second derived ontology from said second fxxt extraction in a set minus operation, wherein the resultant strength weight of the association is its strength weight from said first derived ontology;

02. adding to said first temporary derived ontology a first cnxpt existing in said first derived ontology from said first fxxt extraction but not in said second derived ontology from said second fxxt extraction, wherein said first cnxpt is not a member of any association in said first derived ontology, where a set-minus Boolean set operation is specified on said first derived ontology and said second derived ontology, wherein the resultant importance weight of said first cnxpt is its importance weight from said first derived ontology;

and

c. present the result of the operation under consideration for use in the next lower precedence operation;

whereby a set operation generates a new derived ontology with a temporary fxxt name.

6. The method of claim 4 to also provide creation of a fxxt from the votes of a user, further including:

a. defining a new resultant fxxt for marking the results of interpreting the map definition when said user credentials permit, the resultant fxxt with an identity, and assigning to said new resultant fxxt the bundle of access rights to follow in allowing a user to utilize association instances and cnxpt instances;

b. adding zero or more votes regarding zero or more associations to the resultant fxxt by marking the zero or more associations with the resultant fxxt;

c. adding zero or more votes regarding zero or more cnxpts to the resultant fxxt by marking the zero or more cnxpts with the resultant fxxt;

whereby a user may subsequently apply a fxxt they have defined to a map to ensure the subjectivity of the map and to preserve their work.

7. The method of claim 1, further comprising defining an entity to be represented by a cnxpt;

whereby an entity of any nature including as a party to a transaction is made available as a binding point cnxpt;

whereby an entity is involved in modeling; and

whereby an entity is utilized in categ.orization.

8. The method of claim 1, wherein generating a map further comprises using a coefficient selected from the group of:

a default of one, a variable with a numeric value, and an assigned real number, stating the proportionality of impact of a fxxt, to each fxxt within the subset of selected fxxts;

whereby a weight indicating a strength of consideration the associations marked by a fxxt listed in the map definition;

whereby generating an organization of knowledge or a visualization from a map utilizes a combination, calculated pairwise by unique cnxpt pair, of the weights of the associations that are marked by fxxts in the set of fxxts listed in the map definition;

whereby determining the latent variables positioning the cnxpts of a domain of knowledge into a logically correct 2 to 4 dimensional diagram satisfying the subjective perspective of a user or the objective perspective of a crowd forms a presentation;

whereby varying perspectives of the commonplace information is presented to users requesting them.

9. The method of claim 1, wherein the organization of knowledge comprises a graph structure formed of cnxpts and associations represented by hierarchical tensors.

10. The method of claim 1, wherein the skeletal structure of a map comprises a forest structure formed of cnxpts and highest weighted summarized associations represented by hierarchical tensors;

whereby one or more spanning trees are formed from the summarized associations and connected cnxpts.

11. The method of claim 1, wherein the organization of knowledge comprises a forest of trees structure of cnxpts and associations.

12. The method of claim 1, wherein generating the organization of knowledge of a map further comprises computing a precedence directed acyclic graph from the summarized associations;

whereby a graphical representation of a decision tree, critical path analysis, non-iterative workflow or general precedence oriented structuring is produced;

whereby generating an organization of knowledge or a visualization from a map utilizes a combination, calculated pairwise by unique cnxpt pair, of the weights of the associations that are marked by fxxts in the set of fxxts listed in the map definition;

whereby determining the latent variables positioning the cnxpts of a domain of knowledge into a logically correct 2 to 4 dimensional diagram satisfying the subjective perspective of a user or the objective perspective of a crowd forms a presentation.

13. The method of claim 1, to generate a map combining a precedence graph with a hierarchy forest where at least one cnxpt exists in both precedence and hierarchy, further comprising:

a. generating, based upon a completed precedence graph map, one or more progression lines of precedence each bisecting a segment of a precedence graph, the segment a connected graph containing at least one result cnxpt representing a purpose selected from the group of;

result, sink, outcome, effect, assembly, output, terminal step, completion, and endpoint;

the progression lines of precedence parallel to the flow from start to completion of the flow of the segment;

i. generating, based upon a completed hierarchy forest map and a completed precedence graph map with at least one defined progression line of precedence, for hierarchical force directed determination, affinitive association based positioning vectors, wherein;

ii. forming a list, from associations resulting from fxxt and forest extraction, comprising all hierarchical association relationships not serving as the basis of hierarchical tensors in the structuring and all affinitive association relationships;

iii. summarizing all affinitive association list items of each cnxpt pair based upon absolute weight;

iv. forming an empty priority queue;

v. enqueueing on said queue an uncle roll-up association queue item and a cousin roll-up association queue item for each listed association having endpoints at different depths in the extracted forest;

vi. adding on said queue, for each first uncle association queue item in order, an additional uncle association queue item with the endpoint having less depth replaced by its parent until the depths of the endpoints of all uncle association queue items are no less than one level different and one uncle association queue item, derived from said first uncle association queue item, has been added having a from endpoint that is a root;

vii. replacing, for each cousin roll-up association queue item, the endpoint having greater depth with its parent until no cousin roll-up association queue item has endpoints having different depths;

viii. replacing, for each cousin roll-up association queue item, each endpoint by its parent for each cousin association queue item in order wherein the endpoint is not already a root and the parents of the endpoints are not the same cnxpt;

ix. generating, for each cousin roll-up association queue item for which each endpoint parent is the same as the parent of the other endpoint, a between-sibling-ring attractor tensor;

x. generating, for each cousin roll-up association queue item for which each endpoint is a root, a between-sibling-ring attractor tensor;

xi. generating, for each uncle roll-up association queue item, a to-uncle attractor tensor;

xii. summarizing all between-sibling-ring attractor tensors for each cnxpt pair;

and

xiii. summarizing all to-uncle attractor tensors for each cnxpt pair;

b. rolling up, for precedence aspect force directed position determination, flow associations into flow roll-up precedence tensors to have an effect in positioning of forcing a cnxpt to be in a position relative to a predecessor on a map, wherein;

i. forming a precedence-basis list from associations resulting from fxxt extraction, comprising all hierarchical association relationships with a marking selected from the group of;

dependency, process flow, causality, surrogate causality, conditioned-upon, and precedence;

ii. summarizing all precedence-basis list items of each cnxpt pair based upon weight;

iii. adding a list item to the precedence-basis list representing a relationship between a surrogate first cnxpt representing a fixed point of a timing, initiation, completion, or termination constraint or purlieu known for any second cnxpt and said second cnxpt, setting a timing factor for said second cnxpt to reflect a combination of the strength of the constraint and the direction of the constraint where a positive would reflect an initiation point or a termination constraint;

iv. computing, by a performance evaluation and review technique, a timing factor for each precedence relationship endpoint cnxpt, and a plurality of equal length phases delineating a sequence ordering appropriate to the precedence underlying the flow map wherein no more than one cnxpt or surrogate cnxpt of any precedence chain occupy a phase according to timing factor from the calculation of the technique;

v. generating, for each third cnxpt or surrogate cnxpt that is an endpoint of a list item of the precedence-basis list a precedence-aspect flow tensor relating the precedence map relative and phase defined representative fraction positioning in the precedence aspect point in the phase calculated to contain said third cnxpt corresponding to the timing factor from the calculation of the technique as computed for said third cnxpt, to said third cnxpt for precedence aspect positioning in map generation;

vi. forming an empty priority queue;

vii. enqueueing on said queue a flow uncle roll-up association queue item and a flow cousin roll-up association queue item for each listed precedence-basis list item having endpoint cnxpts at different phase sequence depths;

viii. adding on said queue, for each first flow uncle association queue item in order, an additional flow uncle association queue item with the endpoint having less phase sequence depth replaced by its predecessor until the phase sequence depths of the endpoints of all flow uncle association queue items are no less than one level different and one flow uncle association queue item, derived from said first flow uncle association queue item, has been added having a from endpoint that is the earliest listed endpoint cnxpt or earliest predecessor endpoint cnxpt in a chain;

ix. replacing, for each flow cousin roll-up association queue item having endpoints at different phase sequence depths, the endpoint having greater phase sequence depth with its predecessor, until every flow cousin roll-up association queue item either has at its endpoints equal endpoint predecessors or has at each endpoint either the earliest listed endpoint cnxpt or earliest predecessor endpoint cnxpt in a chain;

x. summarizing all flow cousin roll-up association queue item for each cnxpt pair to form one queue item with a summed weight;

xi. generating, for each remaining flow cousin roll-up association queue item for which each endpoint predecessor is the same as the predecessor of the other endpoint, a flow between-sibling-ring attractor tensor;

xii. generating, for each remaining flow cousin roll-up association queue item for which each endpoint is either the earliest listed endpoint cnxpt or earliest predecessor endpoint cnxpt in a chain and for which the endpoint predecessors are not the same, a flow to-uncle attractor tensor where the uncle is the endpoint with the least phase sequence depth;

xiii. generating, for each flow uncle roll-up association queue item, a flow to-uncle attractor tensor where the uncle is the endpoint with the least phase sequence depth;

xiv. summarizing all flow between-sibling-ring attractor tensors for each cnxpt pair;

and

xv. summarizing all flow to-uncle attractor tensors for each cnxpt pair;

and

c. generating, for map segment force directed position attractor determination, flow tensors based upon previously established map segmentations, wherein;

i. generating a flow tensor for the earliest or senior precedence cnxpt or surrogate cnxpt in the first segment to a flow aspect position according to a predetermined setting of a predetermined value to set a starting point for the flow positioning of the precedence map relative to a precedence map segment position for the start of the progression line of precedence, parallel to the progression line of precedence;

ii. forming a flow-positioning-basis list;

iii. adding to the flow-positioning-basis list associations resulting from fxxt extraction, comprising all hierarchical association relationships with a marking selected from the group of;

flow positioning and map segment positioning;

made into hierarchical tensors wherein the hierarchical association was a flow, setting a weight on said list item to reflect the relative distance from its identified segment centroid in said defined map segmentation;

iv. adding a list item to the flow-positioning-basis list representing a relationship between a surrogate first cnxpt representing a fixed identified segment centroid in said defined map segmentation known for any second cnxpt and said second cnxpt, setting a weight to the list item to reflect a combination of the strength of the constraint and the direction of the constraint where a positive would reflect an attraction and a negative would reflect a repulsion constraint;

v. adding to the flow-positioning-basis list entries positioning precedence relation endpoint cnxpts utilizing a flow positioning function, wherein if neither the predecessor of a predecessor endpoint cnxpt nor the predecessor endpoint cnxpt has been positioned perpendicular to the process flow line then a flow aspect position relative to a default map edge is assigned to the predecessor;

and

vi. generating a flow tensor for each association in the flow-positioning-basis list to a flow aspect position as defined in the list item;

whereby tensors are created to force the ancestors of a cnxpt in a hierarchical presentation to be in positions;

whereby tensors are created to force the predecessors of a cnxpt in a directed graph presentation to be in positions;

whereby generating a map for a domain of wisdom structured as an organization of knowledge of cnxpts results in one or more forms from;

a list, a hierarchical manner, a directed graph manner, or a structure comprising a combination thereof;

whereby the form generated is based on information derived from the included cnxpts and the stated relationships among those cnxpts;

whereby positional relationships between cnxpts are determined from associations of one or more of the types;

hierarchical, flow, precedence, directed, undirected, and affinitive.

14. The method of claim 1 to also construct a flow map, further including:

a. assigning a cnxpt pair to a flow by relating the cnxpt pair with a directed association, and performing a marking selected from the group of;

marking the association as a flow of type, marking the association as a member of a fxxt usable as a source for flow associations in one or more map definitions, marking the cnxpts of the cnxpt pair as usable in a flow of type, and setting one or more trait trxrts for each cnxpt of the cnxpt pair with a meaning that the cnxpt is usable in a flow of type;

b. forming zero or more property values for one or more of said cnxpts in one or more of the cnxpt pairs related by a flow association;

c. forming zero or more time frame epochs for one or more of said cnxpts in one or more of the cnxpt pairs related by a flow association;

d. forming zero or more purlieu purxpts for one or more of said cnxpts in one or more of the cnxpt pairs related by a flow association;

e. detailing a map definition specifying a result to be a flow of type;

f. specifying, for the map, a dimensionality for the map and the elastic surface selected from the group of;

two dimensions, three dimensions, and four dimensions;

g. specifying, for the map, a graphing technique to be used for the positioning of map artifacts;

h. specifying, for the map, an elastic surface view and an area on the canvas of the elastic surface view to be occupied by the map;

i. specifying, for the map, a representative fraction structure for the canvas of the elastic surface related to said flow;

j. specifying, for the map, a policy regarding directionality of associations for the purpose of positioning, the policy selected from the group of;

utilize the sense of the association as stored in the commonplace, and invert the sense of the association as stored in the commonplace;

k. specifying, for the map, a policy regarding utilization and pruning of hierarchical associations in the flow specific in the forming of the spanning forest skeletal structure during forest extraction for the purpose of positioning, the policies applied to the summarized associations in the flow based derived ontology, the policy selected from the group of;

utilize highest summarized strength hierarchical associations first, utilize highest absolute value summarized strength hierarchical associations first, utilize least strength summarized hierarchical associations first, utilize lowest absolute value summarized strength hierarchical associations first, utilize a custom ordering for hierarchical associations and utilize a custom algorithm for ordering of the hierarchical associations;

l. specifying, for the map, the orientation of the map on the elastic surface selected from the group of;

vertical for a single forest, horizontal for a single forest, 3D depth wise, and 4D depth wise, a custom orientation, waterfall display, data flow display, PERT, and an orientation defined for a specific domain of wisdom;

m. specifying, for the map, the directional orientation of the map selected from the group of;

root first in horizontal, root on top in vertical, root last in horizontal, and root on bottom in vertical;

n. specifying, for the map, a policy for setting a distance between the child cnxpts of a parent cnxpt, the children and parent cnxpts related by flow tensors, the policy selected from the group of;

using a constant spacing, using algorithms for spacing children esthetically within the confines of the parent, and using a result of an equation to set spacing involving a factor selected from the group of;

the depth of the child, the importance weight of the child, the strength weight of the flow tensor connecting the child to the parent, the prior position of a child cnxpt, the distance separation implied by the properties of the flow tensor, the distance separation implied by the properties of each cnxpt of the pair of cnxpts, a constant to constrain the depth of a level of children cnxpts, and the count of children on a level;

o. specifying, for the map, a policy for setting a distance between the cnxpts of the pair of cnxpts related by a flow tensor, the policy selected from the group of;

by time separation specified by the flow tensor, by time separation implied by the properties of the flow tensor, by time separation implied by the properties of each cnxpt of the pair of cnxpts, using algorithms for setting distances esthetically, by the result of an equation having as a factor the existence in a sequence of a cnxpt of the pair of cnxpts related by a flow tensor, by an equidistant spacing, by a default constant, by computing self-organized mapping based upon associations of the initial cnxpt with other cnxpts without parents, and by a set constant, and by the result of an equation having a factor selected from the group of;

the prior position of a child cnxpt, the depth of a cnxpt of the pair of cnxpts related by a flow tensor, the distance separation specified by the flow tensor, the distance separation implied by the properties of the flow tensor, the distance separation implied by the properties of each cnxpt of the pair of cnxpts, the strength weight of the flow tensor, the importance weight of a cnxpt, a constant to constrain the breadth of a level of children cnxpts, and the count of children on a level;

p. specifying, for the map, a policy for setting a size for displayed cnxpts in terms of elastic surface representative fractional segments relative to other cnxpts, the policy selected from the group of;

using algorithms for setting distances esthetically, and by the result of an equation having as a factor the properties of a cnxpt of the pair of cnxpts related by a flow tensor, by the result of an equation having as a factor the depth of a cnxpt of the pair of cnxpts related by a flow tensor, by a default constant, and by a set constant;

q. selecting a map definition specifying a flow of type;

r. performing fxxt extraction, generating, using said map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to one or more associations and two or more cnxpts into the derived ontology;

s. generating, using said map definition referencing the set of zero or more fxxts, a flow specific derived ontology for the one or more domains of wisdom by reprocessing the associations processed during fxxt extraction to summarize only directed associations for the type of flow sought, including directed associations from fxxts designated before or during extraction as for the type of flow sought by the definition of said map, placing references to one or more summarized flow specific associations and two or more cnxpts into the flow specific derived ontology;

t. inverting, for the purpose of positioning cnxpts, depending upon the flow type and the directional orientation policy specified in said map definition, the sense of the association directionality for all hierarchical associations in the flow specific derived ontology;

u. generating, using said map definition policies, from the summarized hierarchical associations in the flow specific derived ontology, hierarchical tensors forming a skeletal structure for a map instance for said one or more domains of wisdom wherein the resulting map skeletal structure of said map instance is based upon map policies regarding the manner of analysis selected from the group of;

a spanning forest manner, a descendent forest manner, an enhanced descendent forest manner, an ascendant forest manner, an enhanced ascendant forest manner, and a structure comprising a combination thereof;

v. generating structuring tensors, using said map definition referencing the set of zero or more fxxts, to structure one or more organizations of knowledge for a map instance for said one or more domains of wisdom in the flow specific derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly specified by the map definition, the manner selected from the group of;

a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, a directed graph manner, a graph manner, a horizontal manner, a depth augmented manner, a time augmented manner, a purlieu augmented manner, and a structure comprising a combination thereof;

w. determining, for each cnxpt in one or more of the cnxpt pairs related by a flow tensor in the spanning forest, the set of elastic surface representative fractional fragments indicated by the map policies and the properties of said cnxpt, if any, to set the strength weight and length of the flow tensor to indicate the policy driven approximate positioning for said cnxpt to be positioned in a fictitious elastic surface canvas for said flow;

x. determining from the policies of the map definition the basis for calculating roll-up, utilizing re-inverted sense or un-inverted generated hierarchical tensors from tree-extraction to prepare for roll-up to ensure that the root is considered as top and leaves are at the bottom logically;

Y. generating flow roll-up tensors, and summary flow tensors with weights for enforcing the child cnxpt'"'"'s anchoring location on said elastic surface during positioning on said map by anchoring a parent cnxpt to a representative fractional segment of said fictitious elastic surface canvas based upon said child'"'"'s anchoring location;

z. generating positioning for domain of wisdom member cnxpts according to process trees for organization of knowledge generation, position determination and final sizing means for calculation, based upon policies stated in the map definition, wherein said positionings of said cnxpts of the cnxpt pairs related by a flow tensor are computed by tree of the forest, the tree placed into a representative fractional segment of said fictitious elastic surface canvas for initial computation only, each tree of said map according to information selected from the group of;

the map definition, information associated with each cnxpt by trait or time frame or purlieu or property, and information derived from outside of said cnxpt;

aa. determining, independently for each tree of the spanning forest, the canvas size of the segment of the representative fractional segment of said elastic surface needed to display the tree for each tree of the forest, the dimensionality of the canvas specified in the map definition, the canvas dimensionality selected from the group of;

i. positioning a canvas having two dimensions, wherein;

01. determining the length needed in common for all segments, the length based upon the initial positioning of each tree of the spanning forest structured organization of knowledge for the map instance, the length as a representative fractional segment of said elastic surface canvas in the direction of flow parallel to the process flow line or line of precedence progression and between the latest outcome or outflow as root and the earliest cause or input as leaf, determining the representative fractional segment of said elastic surface canvas required to display the length of flow between that root and leaf, although said root and said leaf may not be in the same tree;

02. determining, for each tree of the spanning forest structured organization of knowledge for the map instance, based upon the initial positioning, the representative fractional segment of said elastic surface canvas perpendicular to the process flow line or line of precedence progression showing direction of flow in each segment for the set of cnxpts occupying each level of the positioned tree structure in the segment, selecting the greatest distance from all levels as the segment breadth for the tree;

03. choosing the placement of segments for assembly breadth wise, each segment length parallel to the direction of flow, the length of the segments all equal, aligning the levels of all trees by time or other marker of the flow to account for start or end delays or similar differences, obtaining an offset for each tree to apply to the initial positioning of each tree to obtain final positions;

ii. positioning a canvas having three or four dimensions, wherein positioning is completed using algorithms for setting distances esthetically between siblings, and parents in a specified graphing technique by the map definition;

01. deriving a position of a root cnxpt instance in an extracted forest of extracted trees of cnxpt instances based on hierarchical tensors created where a cnxpt instance that is not seen on any tensor in a child role is taken to be a root of an extracted tree and one of a set of root cnxpt instances where more than one extracted trees exist in said extracted forest, wherein the empty canvas upon which the forest is to be displayed is divided proportionally to the importance of such roots, the centrality of placement on the empty canvas is selected from the group of;

for hierarchical forests, the root of greatest importance is placed at the center of the canvas;

for hierarchical forests, the root of greatest importance is placed at the center of mass of the canvas based upon the translation of importance of roots to mass for the calculation;

for hierarchical forests, where a plurality of the roots have a trait usable as a depth offset determiner from one base root, the base root is placed at the center of the canvas;

for precedence forests, the root of greatest importance is placed at the center of the canvas;

for precedence forests, the root of greatest importance is placed at the center of mass of the canvas based upon the translation of importance of roots to mass for the calculation;

for precedence forests, where a plurality of the roots have a trait usable as a depth offset determiner from one base root, the base root is placed at the center of the canvas;

for precedence forests, of those dependent cnxpt instances having more than one precedent cnxpt instance in the enhanced descendent forest for the extracted precedence forest and having a first precedent root in a first extracted tree different from a second extracted tree holding a second precedent root for said dependent cnxpt instance, initially select as a dependent second cnxpt instance the dependent cnxpt instance with the greatest difference in depth from said first precedent root and said second precedent root where the depth from said first precedent root is greater, and place said first precedent root at the center of the canvas;

and

for precedence forests, of those dependent cnxpt instances having more than one precedent cnxpt instance in the enhanced descendent forest for the extracted precedence forest and having a first precedent root in a first extracted tree different from a second extracted tree holding a second precedent root for said dependent cnxpt instance, initially select as a dependent second cnxpt instance the dependent cnxpt instance with the greatest difference in depth from said first precedent root and said second precedent root where the depth from said first precedent root is greater, finding all such first precedent roots having the greatest depth, and place one such first precedent root at the center of mass of the canvas based upon the translation of importance of all such first precedent roots to mass for the calculation;

02. determining an error from a possible better position based upon factors selected from the group of;

out of region distance, cnxpt sizing, cnxpt overlap, Euclidean distance from centroid of a child cnxpt to a prior position, Euclidean distance from centroid of a first sibling cnxpt to centroid of a second sibling cnxpt, Euclidean distance from centroid of an uncle to centroid of a child cnxpt, Euclidean distance from centroid of a parent to centroid of a child cnxpt, Euclidean distance from a parent centroid to an uncle, precedence positioning by Euclidean distance from centroid of a precedent cnxpt to centroid of a successor cnxpt, Euclidean distance from centroid of a cnxpt to centroid of a constraint surrogate cnxpt, Euclidean distance from centroid of a child cnxpt to centroid of a representative fraction of the map visualization canvas where cnxpt belongs, and flow positioning;

03. deriving a position of a child cnxpt in an extracted forest of extracted trees of cnxpts based on tensors of the child cnxpt with cnxpts selected from the group of;

parent cnxpt of the child cnxpt, an uncle cnxpt of the child cnxpt, a predecessor cnxpt, a position constraint, a constraint surrogate cnxpt, and a sibling cnxpt of the child cnxpt;

04. modifying the organization of knowledge and the visualized map based on the positioning of the cnxpt;

and

05. updating positions with changes that have the best error reduction effect, until an error metric is reduced to a sufficient level or the descent is limited in its improvement per cycle, or a maximum number of change iterations has occurred;

and

bb. providing to the user said one or more domains of wisdom for utilization;

whereby the ability is provided to place objects for a 2D, 3D, or 4D map in a position related to the ordering of said object directly or relative to the positioning of others in a flow;

whereby generating an organization of knowledge or a visualization from a map utilizes a combination, calculated pairwise by unique cnxpt pair, of the weights of the associations that are marked by fxxts in the set of fxxts listed in the map definition;

whereby determining the latent variables positioning the cnxpts of a domain of knowledge into a logically correct 2 to 4 dimensional diagram satisfying the subjective perspective of a user or the objective perspective of a crowd forms a presentation;

whereby a cause independent Bayesian network with mechanisms ordered by strength to effect weak cause elimination may be drawn automatically.

15. The computer-implemented method of claim 14, further comprising:

a. depicting said at least one a priori event as a cnxpt in a precedence flow forest wherein said cnxpt is a root in the forest in the organization of knowledge and is shown on a flattened map visualization depicting a directed graph of Bayesian network, wherein said cnxpt is at an edge of the flattened map visualization if it is the last determinative a priori event resolved at a pre-determined point in time prescribed as being the time shown for consideration of circumstances prior to resolution of the likelihood of an a posteriori event on the visualization of the map.

16. The method of claim 1 to generate a Bayesian belief network, further comprising:

a. generating a flow map from cnxpts and associations from a commonplace, at least one cnxpt representing a cause, at least one cnxpt representing an effect, at least one association representing a mechanism or conditionality between an at least one cnxpt representing a cause and an at least one cnxpt representing an effect, the cnxpts as variable events and inbound associations as indicators of conditional dependencies wherein the weight of an inbound association when normalized provides a relative probability of the conditioned event among the set of inbound associations for the conditioned event;

a property of a cnxpt as variable event stating a reward for expectation analysis;

b. making available to the user the map and accompanying data structures;

whereby subject matter indicating a flow is organized into a directed graph for positioning and display, with accompanying spanning forests and directed graph networks to be utilized for developing models and improving understanding.

17. The method of claim 16 to also provide for determining a chain of a priori justifications and a posteriori results to determine a likelihood that a hypothesis is correct by generating a Bayesian network from a commonplace, further comprising:

a. extracting one or more subsets of association instances between cnxpt instances from a commonplace, each subset described by a fxxt, wherein at least one association instance extracted is in a subset defined by a fxxt which states that a first cnxpt instance on a first role of the association instance affects the condition of a second cnxpt instance on the opposite, second role in the association instance in a proportion determinable by the association instance'"'"'s weight, the presence of the effect on said second cnxpt instance by said first cnxpt instance termed a dependency, said effect termed a surrogate causality, said second cnxpt instance termed an event outcome;

b. determining a conditionality dependency association instance consensus by summarizing the weights of all instances of dependency association instances between each pair of a first cnxpt instance and a second cnxpt instance where said pair exists in the extracted set of association instances, according to utilize collective consensus through vote tallying means;

c. summarizing the weights of all instances of non-dependency association instances between each pair of a first cnxpt instance and a second cnxpt instance where said pair exists in the extracted set of association instances, according to utilize collective consensus through vote tallying means;

d. considering only conditionality dependency association instances, form hierarchical surrogate causality chains based upon most heavily weighted summarized dependency association instances according to fxxt basic descendant spanning tree extraction means;

e. considering only conditionality dependency association instances not used already for tree formation, form secondary hierarchical surrogate causality chains based upon these remaining summarized dependency association instances according to build enhanced descendant spanning trees means;

and

f. calculating likelihood of each dependent event outcome;

whereby subject matter organized into Bayesian networks is utilized for developing models.

18. The method of claim 1 to predict a best decision tree choice from a decision tree, further comprising:

a. defining a knowledge model comprising a set of one or more fxxts based on information stored regarding a required decision, the information stored comprising a plurality of cnxpts and a plurality of associations, a plurality of cnxpts and a plurality of associations are marked with at least one fxxt of said set of one or more fxxts based on information stored regarding said required decision;

b. defining a map specifying use of said set of one or more fxxts based on information stored regarding said required decision, the map definition specifying that the map instances generated from it will be of type decision tree and will have organizations of knowledge selected from the group of;

a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, and a horizontal manner;

c. generating, using said map definition, a map instance from the commonplace wherein each node is a cnxpt of a type selected from the group of;

i. a question;

ii. a potential completion of a user decision regarding a question that would be reached if the question was answered in a particular manner, the completion having zero or one reward values, the completion having zero or more outbound associations;

iii. a determination required before a question may be answered, an association between determination and question that would be reached if the determination had a particular result;

iv. an a priori event reached by a user decision regarding a question that would be reached if the question was answered in a particular manner;

v. a termination event reached as a result of any non-terminal node;

and

vi. an outcome that is a posteriori event having a calculable expectation value and conditioned on an a priori event;

vii. wherein a potential completion may also be a type of combined node when it also functionally serves as a type selected from the group of;

question, determination, an a priori event, and outcome;

viii. wherein a potential completion will be regarded as a combined node when it has a single outbound association to a type selected from the group of;

question, determination, an a priori event, and outcome;

ix. wherein transitions are represented by associations, providing a way to progress from one node to another, each transition having a starting role filled by a cnxpt representing a beginning state, a strength weight stating a likelihood that the association will be utilized, and an end role filled by a cnxpt representing a ending state, if a cnxpt has no outgoing associations then attaining that node ending state, the answer will result in the completion of the tree;

x. wherein the outbound associations from any node are strength weighted with a likelihood that a particular result is attained from the node, the likelihood based upon a stated probability density or mass function, the default of the likelihood for all associations leaving the node is (1 minus the sum of all likelihoods for the node with a value)/(the count of likelihood values for the node requiring a default), the sum of all strength weights of associations leaving the node normalized to be 1;

d. providing to the user a chart of expected values based upon the Bayesian or probabilistic ramification of each answer available and each determination outcome and the reward value of an outcome;

e. simulating by a model the Bayesian network from a commonplace to determine expectation values for outcomes, the model based upon determination results and answers previously received at the point of an interaction;

and

f. accepting answers to questions, determination results, outcomes of a priori events, and determining the present state of the decision model by determining the potential completion or termination event was reached based upon input;

g. and updating the state and expected rewards available;

whereby a decision tree may be constructed automatically from a commonplace with a defined map definition and a defined fxxt structure; and

whereby the decision tree is susceptible to improvement by analytics available to improve the understanding of the decision tree, while the fxxt structure would allow an amalgam of analytic restructuring and original structure for the decision tree.

19. The method of claim 18 to also provide for determining decision tree outcomes, further comprising:

a. extracting a plurality of subsets of associations between cnxpts from a commonplace, each subset described by a fxxt, wherein at least one association extracted defines a decision rule stating that a first cnxpt holding a role on a first end of the decision rule association is a decision point for making alternative choices one of which is the choice of the outcome state defined by the second cnxpt holding a role on the opposite, outbound second end in the decision rule association;

said first cnxpt role on the association termed a decision, criteria, cause or source state node role depending upon mode in the map definition;

said second cnxpt role termed an answer, case, a specifically valued factor, classification, chance, effect, action, event, or choice outcome state node role depending upon mode in the map definition;

said connection between said first cnxpt and said second cnxpt termed a decision rule, a source of decision, a belief from a line of reasoning, mechanism, decision rule, or a choice availability depending upon mode in the map definition;

the decision rule association'"'"'s strength weight providing a value of type selected from the group of;

information gain, cost complexity measure, the relative quality of the choice of one second cnxpt versus all other second cnxpts, a delay, a cost, a utility, a relative likelihood of the alternative, or the odds of being chosen as a decision depending upon mode in the map definition;

b. multiplying, for each subset of associations obtained from a fxxt, the strength weight of all associations in the subset by a coefficient indicating a proportionality of impact stated for the fxxt in the map definition, according to apply fxxt specification means;

c. determining a consensus regarding each decision rule by summarizing the strength weights of all instances of decision rule associations between each pair of a first cnxpt and a second cnxpt where said pair exists as having roles in at least one decision rule association in the extracted set of associations, according to utilize collective consensus through vote tallying means;

d. summarizing the strength weights of all instances of non-decision rule associations between each pair of a first cnxpt and a second cnxpt where said pair exists as having roles in at least one non-decision rule association in the extracted set of associations, according to utilize collective consensus through vote tallying means;

e. performing forest extraction, considering only decision rule associations, to form decision rule hierarchical tensors representing decision rule associations from source state to choice outcome state based upon most heavily weighted summarized associations representing decision rules according to fxxt basic descendant spanning tree extraction means;

f. forming, considering only decision rule associations not already causing a decision rule tensor for forest formation, second hierarchical decision rule tensors based upon any remaining summarized decision rule associations from source state to choice outcome state according to build enhanced descendant spanning trees means to provide secondary effect indications if called for in the map definition;

g. normalizing, if called for by the mode in the map definition, the strength weights for all inbound hierarchical decision rule tensors having a second role filled by the same third cnxpt so that the sum of strength weights is one;

h. applying a simplification algorithm if called for in the map definition;

and

i. generating a map based upon the forest extraction, the map providing a decision tree formed from a commonplace;

whereby subject matter organized into decision tree networks is utilized for developing models.

20. The method of claim 1, further including:

a. multiplying, for each subset of associations in a map obtained from a first fxxt, the weight of all associations in the subset by a coefficient indicating a proportionality of impact stated for the fxxt in the map definition underlying the map, according to apply fxxt specification means;

whereby quality of a prediction is altered by adjusting the weight of beliefs input.

21. The method of claim 1, to determine relevance of documents by culling, further including:

a. showing a new cnxpt internal to and smaller than an older cnxpt as smaller indicating that said older cnxpt is representing an idea that is actually a context or category, and as said new cnxpt is representing an offshoot idea.

22. The method of claim 1 further comprising:

a. arranging an identified first cnxpt that is a general categorization of one or more specific identified second cnxpts to logically portray containment of each second cnxpt by said first cnxpt;

and

b. arranging an identified third cnxpt that represents a concept close in meaning to the concept represented by an identified fourth cnxpt to be located relatively closer to said fourth cnxpt compared to an identified fifth cnxpt representing a concept having a less similar meaning, to logically portray semantic similarity by the structuring of the map, further including;

i. arranging the third cnxpt that represents a concept nearly identical in meaning to the concept represented by the fourth cnxpt according to the structuring of the map shown to be located very close together to said fourth cnxpt compared to the fifth cnxpt;

and

ii. arranging the third cnxpt that represents a concept indistinguishable in meaning from the concept represented by the fourth cnxpt according to the structuring of the map shown to be located largely overlapping said fourth cnxpt with an indication to a viewer of the apparent redundancy;

whereby the map indicates recognizable similarities and differences between concepts represented by cnxpts;

whereby the appearance of a cnxpt indicates its identity although cnxpts may be made more distinguishable by a display trait such as;

color, size, texture, avatar, position, shading, transparency, context membership, or labeling.

23. The method of claim 22 to relate entities of schemas of disparate data sources where entities have no significant differential in meaning in a specific use case, further including:

a. calculate consensus and impute associations, including preparing at least one consensus organization of knowledge of at least said domain of wisdom from said commonplace containing a first disparate data source and a second disparate data source and at least one pair of a first cnxpt representing a first entity from said first disparate data source and a second cnxpt representing a second entity from said second disparate data source wherein said first entity is very similar to said second entity, by calculating the consensus on the associations of said domain of wisdom according to utilize collective consensus through vote tallying means;

b. causing said first cnxpt to appear very near to said second cnxpt in the organization of knowledge according to map generation means;

and

c. providing access to said organization of knowledge;

whereby users are assisted in uniting entities that are very similar by receiving an indication of similarity;

whereby automation of entity reconciliation and record linkage are enabled;

whereby a subset of closely related cnxpts may be represented by a cntexxt represented by a cnxpt;

whereby deriving a consensus based harmonization is significantly aided but normally requires interactions with the generated organization of knowledge or visualization by the user.

24. The method of claim 1 to also provide for determining decision tree classifier structures, further comprising:

a. performing a fxxt extraction resulting in an extracted derived ontology;

b. performing a skeletal structuring to form a classifier forest map;

c. defining as a goal form of cnxpt a classification required by stating goal traits for matching to a classification;

and

d. walking from root to leaf of the skeletal structuring, choosing a branch in the classifier forest map based upon choosing a child having a trait matching a trait of the goal;

whereby a classifier is provided for matching based upon a match of a plurality of traits.

25. The method of claim 1 to compute a metric for satisfaction of need in a competitive scenario, wherein:

a. generating a first map instance having a first modeling forest of a first organization of knowledge for a domain of wisdom having one or more first cnxpts, each first cnxpt representing a first bundle of ways to satisfy a requirement of a second type, each first cnxpt competing with other first cnxpts;

b. generating a second map instance having a second modeling forest of a second organization of knowledge for a domain of wisdom having one or more second cnxpts, each second cnxpt representing a bundle of requirements satisfied by the ways of a first bundle;

and

c. imputing, via references in an equation in a property of a first cnxpt summing a property in some third set of second cnxpts representing the proportion of requirements of a second type that said first cnxpt may competitively satisfy, the third set formed by a factor selected from the group of;

time frame, geographic area, location in space, temperature range, demographic, marketplace, market segment, fuzziness, anticipated, actuals, set membership, veracity, definer, existence probability, custom grouping of requirements, custom classification, age, provenance, and owner;

d. reporting as a property value of each first cnxpt the competitive satisfaction anticipated;

whereby a calculation of values according to the target organization of data of one domain of wisdom is based at least in part upon the values obtained from wisdom of the plurality of a different organization of knowledge;

whereby specific types of relationships and specific extractions yield imputable values found in a source cnxpt serving as a computation cell for a first domain of wisdom to a target cnxpt serving as a computation cell; and

whereby the availability of a multi-organization of knowledge system provides values otherwise unavailable;

whereby the relationships by associations between cnxpts in different domains of wisdom and the appearance of particular cnxpts in each of two or more different domains of wisdom of the commonplace are useful for calculating in models with higher dimensionality and complexity.

26. The method of claim 25 to also form a value estimate of a tcept, further comprising:

a. calculating, by imputation of a summed value from appcepts in the second organization of knowledge that have estimates of value and are related by a satisfaction of need relationship to a tcept in the first organization of knowledge, the total value of a tcept;

whereby prediction by value of applications of technology is imputed to determine competitive values of technologies satisfying the requirements of a set of applications;

whereby the competitive value may be based upon any desired breakout or timeframe; and

whereby the technologies and applications of technologies need not be from the present or past.

27. The method of claim 1 to perform multi-basis modeling on the basis of a plurality of single organization of knowledge modeling maps, further including:

a. generating a first map instance having a first modeling forest of a first organization of knowledge for a domain of wisdom having a first cnxpt;

b. generating a second map instance having a second modeling forest of a second organization of knowledge for a domain of wisdom having a second cnxpt;

and

c. imputing, via relationships between cnxpts of said first modeling forest and cnxpts of second modeling forest, values of a property of said first cnxpt into a calculation for a property of said second cnxpt;

whereby a forest based model is augmented to model multiple forests in a manner allowing for imputation of information between perspectives;

whereby a calculation of values according to the target organization of data of one domain of wisdom is based at least in part upon the values obtained from another domain of wisdom of the plurality of organizations;

whereby specific types of relationships and specific extractions yield imputable values found in a source cnxpt serving as a computation cell for a first domain of wisdom to a target cnxpt serving as a computation cell; and

whereby the availability of a multi-organization of knowledge system provides values otherwise unavailable;

whereby the relationships by associations between cnxpts in different domains of wisdom and the appearance of particular cnxpts in each of two or more different domains of wisdom of the commonplace are useful for calculating in models with higher dimensionality and complexity.

28. The method of claim 1, to also provide information collection and categorization, further including:

a. creating a hierarchical association between a first cnxpt becoming a category and a second cnxpt becoming a member of the category, wherein said first cnxpt holds a from role on said hierarchical association and said second cnxpt holds a to role on said hierarchical association, wherein the relationship represented by said hierarchical association provides the structure for a categorization in said commonplace, wherein said second cnxpt holds the role on said association info-item defining a locatable sub-category of said first cnxpt;

and

b. attaching additional information to said second cnxpt becoming a member of the category represented by said first cnxpt;

wherein the additional information is available by access through said second cnxpt;

whereby a catalog is developed and information found is added allowing user to access said information through a categorized cnxpt providing an index of information searchable by association.

29. The method of claim 1, wherein organizing the plurality of contexts comprises:

a. identifying relationships between the cnxpts;

b. mapping cnxpts onto a lower dimensional shape using as shapes the cntexxts represented by cnxpts and generated by map generation techniques placing similar cnxpts in closer proximity than dissimilar cnxpts;

c. forming clusters from cntexxts at one or more depths of the organization of knowledge;

and

d. highlighting neighboring cnxpts corresponding to the plurality of cntexxts which form a network of clusters;

whereby a subset of closely related cnxpts are represented by a first plurality of avatars corresponding to the subset of information included in at least one cntexxt in the subset of the plurality of cntexxts in the second portion of the display screen and a different subset of more closely related cnxpts are represented by a second plurality of avatars corresponding to a second plurality of a different subset of information included in at least one cntexxt in a different subset of the plurality of cntexxts in the second portion of the display screen having a higher relevance score than a first subset of closely related cnxpts.

30. The method of claim 1 to cause a map revision, further comprising:

a. summarizing the weights, according to utilize collective consensus through vote tallying means, of all association instances between each pair of a first cnxpt and a second cnxpt where said pair exists in the extracted set of association instances in said domain of wisdom;

b. forming said organization of knowledge;

c. accepting a vote of the user intending to modify the organization of knowledge based on a perception of an inaccuracy via a change interaction selected from the group of;

change of said organization of knowledge, and change made in said visualization;

d. adding the vote to said commonplace and into said derived ontology;

and

e. generating a new organization of knowledge comprising a new consensus among the existing said organization of knowledge and said vote interaction, wherein user said vote is considered according to utilize collective consensus through vote tallying means;

whereby improvements to the commonplace stem from consensus and maps are altered after sufficient changes are made through user votes, whereby the vote a user makes to the data of a map is added into the domain of wisdom that is used for displaying the map.

31. The method of claim 1 to also form a data set of values of latent variables giving positioning of cnxpts in a map perspective satisfying to a user, further including:

a. detailing a map definition specifying said organization of knowledge to produce for said domain of wisdom;

b. structuring said commonplace to extract content by marking zero or more associations and zero or more cnxpts of said commonplace with fxxt identities;

c. interpreting said map definition for each referenced fxxt to extract said map from said commonplace by including cnxpts and associations found marked with said each referenced fxxt according to apply fxxt specification means, wherein the interpreting obtains all associations of said domain of wisdom although an association is not directly market by a referenced fxxt, wherein the interpreting obtains all cnxpts of said domain of wisdom although a cnxpt is not directly market by a referenced fxxt;

d. choosing structuring propositional hierarchical associations from the marked associations accumulated of said map to form an organization of knowledge structure by generating hierarchical tensors;

e. determining affinitive tensors by calculating rollups to direct positioning guidance according to calculate bottom up importance metrics for cnxpt categories means;

f. generating map specific organization of knowledge latent position variable values for cnxpts for generating visualization;

g. generating a visualization for display for said map;

and

h. presenting visualization for utilization;

whereby vectors of point locations with cnxpt radii are generated;

whereby classifications are derived from a relevant portion of commonplace data, cnxpts and associations are marked as members of fxxts, an organization of knowledge is formed and cnxpts are positioned onto a visualization according to an organization of knowledge.

32. The method of claim 1, wherein generating the organization of knowledge of a map further comprises boosting by applying the weighting coefficient indicating a proportionality of impact assigned to a fxxt by multiplying the strength weights of the associations within the fxxt by the assigned weighting coefficient for the fxxt and tallying the weights of the associations of each hierarchical association between a first cnxpt and a second cnxpt having roles, the associations garnered from the set of fxxts specified by a map definition, to generate, without retaining differentiation by fxxt, summarized weighted associations into the derived ontology.

33. The method of claim 1, wherein generating the organization of knowledge of a map further comprises boosting by applying the weighting coefficient indicating a proportionality of impact assigned to a fxxt by multiplying the importance weight of a cnxpt within the fxxt by the assigned weighting coefficient for the fxxt garnered from the set of fxxts specified by a map definition, and tallying the calculated importance weights of the cnxpt to generate, without retained fxxt differentiating, summarized weighted cnxpt importance into the derived ontology, to be utilized for the single appearance of the cnxpt in the map.

34. The method of claim 1, wherein generating the organization of knowledge of a map further comprises boosting by applying the weighting coefficient indicating a proportionality of impact assigned to a fxxt by multiplying the strength weights of the associations within the fxxt by the assigned weighting coefficient for the fxxt and tallying the weights of the associations of each non-hierarchical directed association between a first cnxpt and a second cnxpt having roles, the associations garnered from the set of fxxts specified by a map definition, to generate, without retained fxxt differentiating, summarized weighted non-hierarchical directed associations into the derived ontology.

35. The method of claim 1, wherein generating the organization of knowledge of a map further comprises applying the weighting coefficient indicating a proportionality of impact assigned to a fxxt by multiplying the strength weights of the associations within the fxxt by the assigned weighting coefficient for the fxxt and tallying the weights of the associations of each affinitive association between a first cnxpt and a second cnxpt having roles, the associations garnered from the set of fxxts specified by a map definition, to generate, without retained fxxt differentiating, summarized weighted affinitive associations into the derived ontology.

36. The method of claim 1 to form a consensus, further including:

a. forming consensus regarding categorizations based upon association consensus tallying by summarizing strengths, from votes or input, of a plurality of similar relationship info-items to form a single summary relationship info-item according to utilize collective consensus through vote tallying means;

and

b. forming consensus regarding properties based upon property consensus tallying summarizing a plurality of values, from votes or input, for a single property of an info-item to form a single summary property with one value for said info-item according to utilize collective consensus through vote tallying means;

whereby a basic level consensus of opinions regarding information in a commonplace is formed.

37. The method of claim 1, to produce a map from a commonplace of information demarcating the collective consensus of a crowd from what has not reached consensus to a predetermined level, further comprising:

a. extracting a resultant derived ontology of cnxpts by fxxt extraction based upon consensus voting where association choice is based upon consensus weighting of similar associations between a cnxpt pair comprising a first cnxpt and a second cnxpt, wherein each first cnxpt in common as having a parent role in all said cnxpt pairs and a set of second cnxpts each having a role as a child in the cnxpt pairs, wherein the consensus is formed to find the summary association between the first cnxpt and one second cnxpt as child has the greatest cumulative weight, wherein the associations have been extracted into a preliminary derived ontology according to a map definition;

b. calculating sample distributions for the sample domains defined to be the votes given regarding associations between said first cnxpt and each second cnxpt, wherein the statistic taken is the association weight of the votes per source of the vote;

c. locating, for the set of second cnxpts, sample distributions having a significant variance indicating a multimodal probability density function for the test of whether a single belief is held by those voting on the association between the first cnxpt and one second cnxpt;

and

d. depicting on said structuring an indication that for one or more first cnxpts for which a consensus was sought, a failed praxis was found to show a lack of consensus that a summary association between the first cnxpt and one second cnxpt has a high differential between the votes made by different groups of sources;

whereby an indication of a plurality of different beliefs or positions has been seen in the votes taken for one or more relationships indicated by the associations between the first cnxpt and the second cnxpts according to the extracted cnxpts and associations of the domain of wisdom shown in a map.

38. The computer-implemented method of claim 37 to produce a map from a commonplace of information demarcating the collective belief of a crowd, further comprising:

a. performing fxxt extraction based upon all votes in a domain of wisdom for a map definition;

b. eliminating, prior to structuring, from the derived ontology resulting from fxxt extraction any association for which a failed praxis is found within derived ontology;

and

c. extracting a structuring of remaining associations and cnxpts where association choice is based upon highest association weighting;

whereby major disagreements holding back from a consensus are removed in the resulting organization of knowledge for a map definition.

39. The method of claim 38, to produce a map from a commonplace of information demarcating the collective belief of a crowd regarding what outcomes are anticipated at any point in time, further comprising:

a. performing fxxt extraction based upon consensus voting;

b. eliminating, prior to structuring, from the extracted fxxt any cnxpt for which a failed praxis is found;

c. extracting a structuring of cnxpts where a dimension presents a time aspect and at least one cnxpt is an event and at least one cnxpt is an outcome, wherein at least one association weight determinative of outcome is based upon consensus voting, wherein at least one association choice is determinative of outcome, and wherein at least one association choice is based upon at least one consensus weighting;

d. slicing the structuring by a timeline to prepare a flattened aspect of a organization of knowledge where any outcome whose state is not resolvable at the time of the timeline fall to the future side of the timeline and are optionally not shown in a derived visualization;

and

e. depicting on said structuring, optionally, the cnxpts for which a consensus determination has found a failed praxis.

40. The method of claim 1, wherein generating the hierarchical skeletal structure for a map definition comprises:

a. ordering into a queue the summarized directed associations of the derived ontology resulting from fxxt extraction by summarized directed association weight, highest weight implying least cost, greatest first, wherein as only a convention each directed association has a first role considered to be a from role held by a first cnxpt and a second role considered to be a to role held by a second cnxpt, wherein the directionality would represent a transitive concept relationship generally of a type selected from the group of;

child to parent, sub category to category, category to super category, employee to employer, finish state to start state, dependent to independent, end to start point, succeeding to preceding, outcome to cause, sub-assembly to assembly, detail account to summary account, element to law, tactic to strategy, integer to claim, data set to data collection, class member to class, and leaf to root;

b. forming an empty skeletal structure to be filled with hierarchical tensors and singleton cnxpts;

c. filling the skeletal structure with all cnxpts extracted into a derived ontology for the map, as singletons;

d. examining, while the queue is not empty, each current front summarized directed association in the queue, the front association always having a highest weight of those in the queue, wherein;

i. designating said current front summarized directed association for consideration, the designation selected from the group of;

01. considering said current front summarized directed association, wherein the skeletal structure is to hold a least cost spanning forest, wherein the skeletal structure is to hold a spanning forest of hierarchical tensors whose endpoint roles are held by cnxpts, wherein no two tensors may have the same cnxpt in a to role to exclude any but a single first parent appearing for any cnxpt in the skeletal structure, testing whether said current front summarized directed association would be a proper edge in a graph-theoretic spanning forest of the derived ontology resulting from fxxt extraction by connecting a root of a sub-tree to a leaf of a second tree not otherwise connected to the sub-tree;

and

02. considering said current front summarized directed association, wherein prior to consideration for incorporation into the spanning forest the directed associations have all had their sense reversed causing the to role to be occupied by the child, wherein the skeletal structure is to hold a least cost spanning forest of a directed acyclic graph of a precedence flow where the output cnxpt is in a from role, the spanning forest comprising hierarchical tensors whose endpoint roles are held by cnxpts, wherein no two tensors may have the same cnxpt in a from role to exclude any but a single first parent appearing for any cnxpt in the skeletal structure, testing whether said current front summarized directed association would be a proper edge in a graph-theoretic spanning forest of the derived ontology resulting from fxxt extraction, wherein after complete formation of the spanning forest and the derivative positioning of cnxpts the sense of the associations are returned to their original state;

ii. adding, if test is successful, said hierarchical tensor representing said current front summarized directed association to said skeletal structure;

and

iii. removing the front summarized association from said queue;

whereby the summarized associations are used to form a spanning forest in either a forest with a single parent per child or a forest with a single child per parent depending upon the purpose of the map.

41. The method of claim 40, wherein generating the organization of knowledge of a map comprises designating each cnxpt as a root cnxpt that is not related by a hierarchical tensor in the skeletal structure of a map to any cnxpt in a child role.

42. The method of claim 1, wherein generating a map further comprises boosting of a first property of each cnxpt of a fxxt by applying a weighting coefficient indicating a proportionality of impact assigned to the fxxt by multiplying the first property of each cnxpt within the fxxt by the assigned weighting coefficient for the fxxt, each cnxpt garnered from the set of fxxts specified by a map definition, to generate, without retaining differentiation by fxxt, a summarized cnxpt with the first property summarized, into the derived ontology;

whereby increasing the importance of a cnxpt by boosting a fxxt more than another fxxt causes an impact to the map produced;

whereby the boosting increases the importance of property of a cnxpt of a boosted fxxt relative to the property of a cnxpt of a fxxt not boosted;

whereby the boosting will increase the effect of the cnxpts in the map for other calculations relative to those of a fxxt not boosted.

43. The method of claim 1, wherein generating the organization of knowledge of a map further comprises elimination of directed associations from filling a structural role in a resulting map, wherein:

a. ordering into a queue the summarized associations of the derived ontology from fxxt extraction by summarized association weight, greatest first;

b. examining, while the queue is not empty, each current front summarized association in the queue, the front summarization always having a highest weight of those in the queue, the manner of examination selected from the group of;

i. considering said current front summarized directed association, wherein the skeletal structure is to hold a least cost spanning forest, wherein the skeletal structure is to hold a spanning forest of hierarchical tensors whose endpoint roles are held by cnxpts, wherein no two tensors may have the same cnxpt in a to role in the spanning forest to exclude any but a single first parent appearing for any cnxpt in the spanning skeletal structure, wherein considering results in incorporation of a tensor derived from a qualified said current front summarized directed association into the spanning descendent forest, or marking a failing said current front summarized directed association with a designation selected from the group of;

useable as secondary child in the enhanced descendent forest, unusable for its direction but usable for showing affinity, and excess;

ii. considering said current front summarized directed association, wherein prior to consideration for incorporation into the spanning forest the directed associations have all had their sense reversed causing the to role to be occupied by the child, wherein the skeletal structure is to hold a least cost spanning forest of a directed acyclic graph of a precedence flow where the output cnxpt is in a from role, the spanning forest comprising hierarchical tensors whose endpoint roles are held by cnxpts, wherein no two tensors may have the same cnxpt in a child role to exclude any but a single first child appearing for any cnxpt in the skeletal structure, wherein considering results in incorporation of a tensor derived from a qualified said current front summarized directed association into the spanning descendent forest, or marking a failing said current front summarized directed association with a designation selected from the group of;

useable as secondary child in the enhanced descendent forest, unusable for its direction but usable for showing affinity, and excess;

and

iii. considering, by passing, with the context, said current front summarized directed association to a custom algorithm to obtain a decision, wherein considering by the algorithm results in a determination to incorporate a tensor derived from a qualified said current front summarized directed association into the spanning descendent forest, or to mark a failing said current front summarized directed association with a designation selected from the group of;

useable as secondary child in the enhanced descendent forest, unusable for its direction but usable for showing affinity, and excess;

and

c. removing said current front summarized directed association from said queue;

whereby a map product is formed based upon an extraction of cnxpts and associations marked by zero or more fxxts.

44. The method of claim 1, wherein a property of the summarized hierarchical associations of the derived ontology from fxxt extraction is used as the basis for ordering the queue from which associations are selected to cause derivation of tensors for the spanning descendant tree or otherwise marked.

45. The method of claim 1, wherein generating a map further comprises boosting of a first property of associations of a fxxt by applying a weighting coefficient indicating a proportionality of impact assigned to the fxxt by multiplying the first property of the associations within the fxxt by the assigned weighting coefficient for the fxxt and tallying the first property of each association between a first cnxpt and a second cnxpt having roles while adjusting for the directionality of associations, the associations garnered from the set of fxxts specified by a map definition, to generate, without retaining differentiation by fxxt, summarized weighted associations into the derived ontology;

whereby the boosting increases the chance that an association of a boosted fxxt will be utilized, relative to those of a fxxt not boosted, as a structural tensor in generating a forest for positioning in a map;

whereby the boosting will increase the effect of the associations and cnxpts in the map for other calculations relative to those of a fxxt not boosted;

whereby an association boosted may be retained while one not boosted would be eliminated in edge selection algorithms;

whereby an association boosted may be relatively more important while one not boosted would be less important depending upon association type, amplifying diversity within a set of associations marked by a fxxt.

46. The method of claim 1, further including:

a. generating a dummy cnxpt as parent for each cnxpt of said descendent tree having no parent cnxpt in domain of wisdom of said map and where said parentless cnxpt is known not to belong at the root level of said descendent tree, and generating one hierarchical tensor and zero or more associations connecting said dummy cnxpt as parent to said parentless cnxpt in said map to direct positioning of said added dummy cnxpt according to dummy cnxpt generation means for tree formation after forming an enhanced descendant forest of said map;

b. generating a dummy cnxpt as parent for each said added dxo or txo info-item anchored to a cnxpt in said descendent forest, and generating one hierarchical tensor and zero or more associations connecting said dummy cnxpt as parent to said added dxo or txo info-item in domain of wisdom of said map and one hierarchical tensor and zero or more associations connecting said dummy cnxpt as child to said anchoring cnxpt of said added dxo or txo info-item in domain of wisdom of said map to direct positioning of said added dummy cnxpt according to dummy cnxpt generation means for tree formation after adding dxo instances or txo instances of domain of wisdom of said map to said enhanced descendant forest;

c. generating a dummy cnxpt as parent for each alias-hyperlink of said descendent forest having no parent cnxpt in domain of wisdom of said map, and generating one hierarchical tensor and zero or more associations connecting said dummy cnxpt as parent to said alias-hyperlink in said map and one or more associations connecting said dummy cnxpt to the base cnxpt of said alias-hyperlink in said map to direct positioning of said added dummy cnxpt according to dummy cnxpt generation means for tree formation after adding alias-hyperlinks to said map to said enhanced descendant forest;

d. adding zero or more unanchored dxo instances and txo instances of domain of wisdom of said map to said enhanced descendant forest at the root level;

and

e. generating a dummy cnxpt as parent for each said added unanchored dxo or txo info-item, and generating one hierarchical tensor and zero or more associations connecting said dummy cnxpt as parent to said added unanchored dxo or txo info-item in domain of wisdom of said map to direct positioning of said added dummy cnxpts according to dummy cnxpt generation means for tree formation, and setting the prior position of said dummy cnxpt to be that given for said unanchored dxo or txo where positioning information for said unanchored dxo or txo is obtained from its placement on a prior generation of said map, if any, or from said map definition.

47. The method of claim 1, further including:

a. generating, from all cnxpts and knowledge structuring propositional hierarchical associations of a basic descendant forest, an enhanced descendant forest according to build enhanced descendant spanning trees means for tree formation;

b. adding zero or more alias-hyperlinks to said enhanced descendant forest according to build enhanced descendant spanning trees means for tree formation;

c. generating zero or more cnxpt importance properties with weights for enforcing relative sizing of added alias-hyperlinks in said enhanced descendant forest;

d. generating zero or more hierarchical tensors to said enhanced descendant forest to direct positioning of added alias-hyperlinks of said map according to build enhanced descendant spanning trees means for tree formation;

e. adding zero or more anchored dxo instances, zero or more unanchored dxo instances, and zero or more txo instances to said enhanced descendant forest according to build enhanced descendant spanning trees means;

f. generating, into said enhanced descendant forest, zero or more importance properties with weights for enforcing relative sizing of cnxpts;

and

g. generating, into said enhanced descendant forest, zero or more directed tensors to direct positioning of said added dxo and txo instances according to build enhanced descendant spanning trees means;

whereby the ability is provided to place objects for a map in a position related to the closeness of said object to others logically according to a map definition and a structuring derived therefrom.

48. The method of claim 1 to predict the timing of fruition of a subsumed cntexxt in a categorization, further including:

a. identifying known event timings for each of a set of congruent predecessors of a target entity anticipated to fit into a cntexxt subsumed by one or more first predecessor as an offshoot of the first predecessor, a predecessor represented by a predecessor cnxpt, the target entity represented by a target cnxpt, an event timing represented by an association or a trait entry on the target cnxpt, on a prediction basis given by at least one estimation rationale selected from the group of;

i. by when a productized predecessor of the target cnxpt became real;

ii. by when a feature of a productized predecessor, the feature anticipated also to be of the target cnxpt, became real;

iii. by when a product utilizing a predecessor was delivered;

iv. by when a predecessor was used in production;

v. by what the patent status is for a predecessor;

vi. by what the research status is for a predecessor;

and

vii. by what the rate of innovation has been for the incremental innovations prior to and in the ancestry of the target cnxpt based upon predecessors;

b. identifying anticipated event timings for a target entity, represented by a target cnxpt, on a prediction basis given by at least one estimation rationale selected from the group of;

i. by what the patent status is for the target cnxpt;

and

ii. by what the research status is for the target cnxpt;

and

c. generating an expected gestation event timeline assembling the anticipated gestation events of the target represented by the target cnxpt given approximate timings and durations, the timings and durations selected from the group of;

one or more of the known gestation events of one or more appropriate predecessors, and one or more of the anticipated gestation events of the target;

whereby the length of time before or time frame when a technology is reasonably anticipated to exist is estimated based upon gestation events of predecessors and how a target would likely become real.

49. The method of claim 1 to predict the distance or depth difference between a subsuming cntexxt and a subsumed cntexxt in a categorization, further including:

a. teasing out predictors of a ttx'"'"'s depth and summarizing those predictors to a series of probabilities for timeframes, resulting in a prediction of the status of each cnxpt based upon a mass incremental characterization for subsuming cnxpts;

b. calculating for a target cnxpt as a basis, including at least one of;

estimating the depth of the subsuming cnxpt;

estimating a depth differentiation characteristic of the differentiation between a subsumed cnxpt and its subsuming cnxpt;

and

c. adding the depth estimated for the subsuming cnxpt to the depth indicated by the differentiation of the subsumed cnxpt to estimate the depth of the subsumed cnxpt;

whereby the depth of a cnxpt in an extracted categorization forest is estimated.

50. The method of claim 1, wherein generating a map comprises:

a. determining positioning tensors based also on applying coefficient multipliers based upon type of basis association resulting in a tensor;

whereby tensors are created to force the ancestors of a cnxpt to be in positions with the cnxpt itself being positioned inside the ancestor in a categorization map or juxtaposed to the ancestor in a precedence map, as well as being in the defined segment.

51. The method of claim 50, wherein generating a map comprises:

a. performing a roll-up analysis that analyzes, for each cnxpt, a cumulative weight of associations that ascendants of the cnxpt have with other cnxpts within the map;

and

b. generating affinitive tensors based upon the cumulative weight of associations according to calculate roll-up association weights to form positioning tensors means;

whereby information in a commonplace is used to assemble strength information needed to position cnxpts based upon relationships beyond what is given in the spanning forests so that the full content of a map definition is utilized to form a perspective rather than merely the positions based only upon direct parentage.

52. The method of claim 1, to generate positioning of the cnxpts of a map, further including:

a. generate, according to calculate roll-up association weights to form positioning tensors means, for each second cnxpt holding an opposing role on one or more associations or association instances connected to a first cnxpt in a descendant extracted forest map skeletal structure for the map, an affinitive tensor with an accumulative weighting selected from the group of;

i. for said second cnxpt an uncle of said first cnxpt the summarized weights of said associations or association instances considering weights inherited from associations or association instances between said first cnxpt and descendants of said second cnxpt and weights inherited from associations or association instances between said second cnxpt and descendants of said first cnxpt;

ii. for said second cnxpt a cousin of said first cnxpt the summarized weights of said associations or association instances considering weights inherited from associations or association instances between said first cnxpt and descendants of said second cnxpt and weights inherited from associations or association instances between said second cnxpt and descendants of said first cnxpt;

and

iii. for said second cnxpt a sibling of said first cnxpt the summarized weights of said associations or association instances considering weights inherited from associations or association instances between said first cnxpt and descendants of said second cnxpt and weights inherited from associations or association instances between said second cnxpt and descendants of said first cnxpt;

and

b. generating zero or more elements of intermediate information selected from the group of;

an affinitive tensor, a sibling roll-up affinitive association, an uncle roll-up affinitive association, a cousin roll-up affinitive association, a strength weight for an affinitive tensor, and an importance weight for a cnxpt;

according to calculate roll-up association weights to form positioning tensors means;

whereby information in a commonplace is used to assemble strength and importance information needed to position cnxpts based upon the full content of a hierarchy in a perspective rather than merely the positions based only upon direct parentage;

whereby the relationships between cnxpts that are both at the same depth of the forest of trees or between cnxpts that are in adjacent levels are used to improve the positioning of cnxpts in a map.

53. The method of claim 52, wherein generating a map further comprises rolling-up affinities of cnxpts, dxos, and other txo info-items to form tensors for enforcing object spacing and sizing for a map, wherein:

a. forming a roll-ups result ontology to contain the results of roll-ups comprising, initially, all cnxpts, all dxos, all other txos, and all tensors from the enhanced descendant forest ontology of said map, wherein the tensors provide a structure for parentage, cousin determination, uncle determination, and depth determination;

b. forming a list of associations not serving as the basis of hierarchical tensors in the skeletal structuring of forest extraction given by the roll-ups result ontology, the list comprising associations selected from the group of;

all affinitive association relationships, all residual hierarchical association relationships, all surrogate associations whose endpoints are not both cnxpts, and other associations resulting from fxxt and forest extraction not serving as the basis of hierarchical tensors;

c. summarizing, for said list of associations, all affinitive association list items of each cnxpt pair based upon absolute weight;

d. forming an empty priority queue;

e. enqueueing on said queue an uncle roll-up association queue item and a cousin roll-up association queue item for each listed association having in roles info-item endpoints at different depths in the roll-ups result ontology;

f. adding on said queue, for each first uncle association queue item in order, an additional uncle association queue item with the endpoint having less depth replaced by its parent until the depths of the endpoints of all uncle association queue items are no less than one level different and one uncle association queue item, derived from said first uncle association queue item, has been added having a from endpoint that is a root;

g. replacing, for each cousin roll-up association queue item, the endpoint having greater depth with its parent until no cousin roll-up association queue item has endpoints having different depths;

h. replacing, for each cousin roll-up association queue item, each endpoint by its parent for each cousin association queue item in order wherein the endpoint is not already a root and the parents of the endpoints are not the same info-item;

i. generating, for each cousin roll-up association queue item for which each endpoint parent is the same as the parent of the other endpoint, a between-sibling-ring attractor tensor into said roll-ups result ontology;

j generating, for each cousin roll-up association queue item for which each endpoint is a root, a between-sibling-ring attractor tensor into said roll-ups result ontology;

k. generating, for each uncle roll-up association queue item, a to-uncle attractor tensor into said roll-ups result ontology;

l. summarizing all between-sibling-ring attractor tensors for each pair of info-items selected from the group of;

cnxpts, dxos, and other txos;

m. summarizing all to-uncle attractor tensors for each pair of info-items selected from the group of;

cnxpts, dxos, and other txos;

n. generating, for each info-item selected from the group of;

cnxpts, dxos, and other txos;

wherein said info-item had previously existed in a just prior generated instance of said map, a prior position tensor between said info-item and a fictitious object at the prior position of said info-item in said just prior generated instance of said map, setting the weight of said prior position tensor to a pre-specified tensor weight as an admixture coefficient;

and

o. generating, for each info-item selected from the group of;

cnxpts, dxos, and other txos;

wherein said info-item had a parent in a just prior generated instance of said map, a prior position in parent tensor between said info-item and a fictitious object at the prior position of said info-item in relation to its parent in said just prior generated instance of said map, setting the weight of said prior position in parent tensor to a pre-specified tensor weight as an admixture coefficient;

whereby classifications derived from a relevant portion of said commonplace data serve as the basis for positioning of cnxpts onto a visualization according to the map skeletal structure provided by the enhanced descendent tree forest, the prior positionings by the user for the same map, and for the maps from which the current map is derived;

whereby the ability is provided to place objects for a multi-dimensional map in a position related to the closeness of said object to others logically according to a map definition and a structuring derived therefrom, and based to some degree on the positioning by the user of the objects in prior work arranging those objects in a visualization; and

whereby the various generated tensors serve as a basis for computing an understandable and associative position of cnxpts into an organization of knowledge from the structure provided by said enhanced descendent tree forest.

54. The method of claim 1, wherein generating a map further comprises:

a. rolling up the directed nature of directed affinitive associations, wherein each summarization involving a directed affinitive association is performed on a ‘

netting out’

basis for the directionality or the association to have the effect in later positioning to force a cnxpt'"'"'s ancestors to be in a relative position based also upon direction.

55. The method of claim 1, comprising:

a. determining a location of each first cnxpt with respect to one or more other second cnxpt within the organization of knowledge of a map wherein the first cnxpt participates in zero or more first relationships between the first cnxpt with some other second cnxpt indicating a closeness of meaning of the first cnxpt and the second cnxpt;

wherein said first relationship is recorded by zero or more association info-items;

wherein the relationship is formed virtually from the collective information available in the map;

whereby carrying out an obfuscation process on info-item identifiers by translating from unique internal format identifier for an info-item to a unique external identifier according to a key encryption process security procedure.

56. The method of claim 1 to form an associative map, wherein generating a map further comprises:

a. determining positioning error metrics based also on applying admixture coefficient multipliers set to increase the apparent error existing of a specific error type;

b. calculating an overall error metric based upon use of the admixture coefficients multipliers;

c. selecting an error to correct based upon the contribution to the overall error metric of a specific error as adjusted by the admixture coefficient multipliers;

and

d. correcting the error based upon the actual error existing of a specific error type without regard to any admixture coefficient multiplier;

whereby error correction is prioritized to make position correction efficient.

57. The method of claim 56, further comprising:

a. deriving a position of an initial root precedent cnxpt without descendants in an extracted structuring of cnxpts based on relationships of the initial cnxpt with other cnxpts without descendants;

and

b. deriving a position of a descendant cnxpt in an extracted structuring of cnxpts based on relationships of the descendant cnxpt with cnxpts selected from the group of;

precedent cnxpt of the descendant cnxpt, an uncle cnxpt of the descendant cnxpt, and a sibling cnxpt of the descendant cnxpt.

58. The method of claim 1, to position cnxpts on a map being generated, further comprising:

a. deriving a position of an initial cnxpt without descendants in an extracted structuring of cnxpts based on associations of the initial cnxpt with other cnxpts without descendants;

b. deriving a position of a precedent cnxpt in an extracted structuring of cnxpts based on associations of the precedent cnxpt with cnxpts selected from the group of;

descendant cnxpt of the precedent cnxpt, a nephew cnxpt of the precedent cnxpt, and a sibling cnxpt of the precedent cnxpt;

and

c. modifying the map organization of knowledge based on the positioning of the cnxpt.

whereby bottom up, precedent first, precedent last, and top down organizations of structurings are developed.

59. The method of claim 1, further comprising:

a. deriving a position of an outcome event cnxpt without a posteriori dependent events in an extracted structuring of cnxpts based on relationships of the initial cnxpt with other cnxpts without a posteriori dependent events;

and

b. deriving a position of an a priori event cnxpt in an extracted structuring of cnxpts based on relationships of the a priori event cnxpt with cnxpts selected from the group of;

dependent a posteriori events cnxpt of the a priori event cnxpt, a nephew dependent event cnxpt of the a priori event cnxpt, and a sibling cnxpt of the a priori event cnxpt.

60. The method of claim 1, further comprising:

a. determining, for each one or more map instance organization of knowledge generated as a forest in forest extraction for said domain of wisdom, an orientation selected from the group of;

vertical for the single forest generated, horizontal for the single forest generated, vertical for the first of a plurality of forests generated and horizontal for the second of a plurality of forests generated, horizontal for the first of a plurality of forests generated and vertical for the second of a plurality of forests generated, a custom orientation, and an orientation defined for a specific domain of wisdom;

b. completing, for each one or more skeletal structures for a map instance generated as a forest in forest extraction for said domain of wisdom according to a method selected from the group of;

i. determining a layout orientation according to a method selected from the group of;

stated in map definition, defaulted according to predetermined system setting, default for a map type, and stated by user;

ii. determining an area for placement of initial cnxpts according to layout orientation, the area appropriate to the customary or esthetically pleasing layout orientation determined;

iii. deriving a position of a non-root cnxpt in an extracted structuring of cnxpts based upon a method selected from the group of;

01. basing, where non-root cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

sub-categories in a categorization, member in a team, participant, stakeholder, components in an assembly, instances in an object structure of a class breakdown, and children in a hierarchy;

in a root to leaf build orientation, further including;

deriving a position of an initial cnxpt substantially of the nature of a type selected from the group of;

super-categories in a categorization, team, participant, stakeholder, assemblies in an assembly graph, classes in an object structure of a class breakdown, and parents in a hierarchy;

without parents in an extracted structuring of cnxpts based upon the area for placement determined and upon a method selected from the group of;

 

prior position;

 

default value;

 

equidistant spacing;

 

self-organized mapping based upon associations of the initial cnxpt with other cnxpts without parents;

 

arrangement on a circle;

 

arrangement on a sphere;

 

arrangement on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

and

 

arrangement on a line;

deriving the relative position of a child cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of parent cnxpt relative to the child cnxpt;

 

logical distance from an uncle cnxpt of the parent cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from an uncle cnxpt of the child cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to edge of parent cnxpt;

 

relative importance of parent cnxpt with respect to siblings of parent cnxpt;

 

relative importance of child cnxpt with respect to importance of siblings of child cnxpt;

 

non-overlap rules;

 

parent edge to child edge protection minimums;

 

inter-child cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the child cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving positions of alias indicators of secondary parents in an enhanced forest skeletal structure based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

convenience positioning;

02. basing, where non-initial cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

super-categories in a categorization, team, participant, stakeholder, assemblies in an assembly graph, classes in an object structure of a class breakdown, and parents in a hierarchy;

in a leaf sub-category to highest category build orientation, further including;

deriving a position of an initial cnxpt substantially of the nature of a type selected from the group of;

sub-categories in a categorization, member in a team, participant, stakeholder, components in an assembly, instances in an object structure of a class breakdown, and children in a hierarchy;

without children in an extracted structuring of cnxpts based upon the area for placement determined and upon a method selected from the group of;

 

prior position;

 

default value;

 

equidistant spacing;

 

self-organized mapping based upon associations of the initial cnxpt with other cnxpts without children;

 

arrangement on a circle;

 

arrangement on a sphere;

 

arrangement on the interior of a circle;

 

arrangement on the interior of a sphere;

 

arrangement on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

arrangement in the center of the canvas;

 

and

 

arrangement on a line;

deriving the relative position of a primary parent cnxpt of a positioned child cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of child cnxpt relative to its immediate parent cnxpt;

 

logical distance from a nephew cnxpt of the parent cnxpt, the nephew cnxpt a sibling of the child, given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from a nephew cnxpt of the parent cnxpt given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to the edge of the child cnxpt;

 

relative importance of child cnxpt with respect to siblings of child cnxpt;

 

relative importance of parent cnxpt with respect to importance of siblings of the parent cnxpt;

 

non-overlap rules;

 

child edge to parent edge protection minimums;

 

inter-parent cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the parent cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving the relative position of an alias for a secondary immediate parent cnxpt of a positioned child cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

and

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

03. basing, where non-root cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

successors in a precedence graph, nodes with an inbound arc in a digraph, precedent components in an assembly;

in a predecessor-root to successor build orientation, further including;

deriving a position of an initial cnxpt substantially of the nature of a type selected from the group of;

predecessors in a precedence graph, nodes with an outbound arc in a digraph, and completed components in an assembly graph;

without predecessors in an extracted structuring of cnxpts based upon the area for placement determined and upon a method selected from the group of;

 

prior position;

 

default value;

 

equidistant spacing;

 

self-organized mapping based upon associations of the initial cnxpt with other cnxpts without predecessors;

 

arrangement on a circle;

 

arrangement on a sphere;

 

arrangement on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

and

 

arrangement on a line;

deriving the relative position of a successor cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of predecessor cnxpt relative to the successor cnxpt;

 

logical distance from an uncle cnxpt of the predecessor cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from an uncle cnxpt of the successor cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to edge of predecessor cnxpt;

 

relative importance of predecessor cnxpt with respect to siblings of predecessor cnxpt;

 

relative importance of successor cnxpt with respect to importance of siblings of successor cnxpt;

 

non-overlap rules;

 

predecessor edge to successor edge protection minimums;

 

inter-successor cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the successor cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving positions of alias indicators of secondary predecessors in an enhanced forest skeletal structure based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

convenience positioning;

04. basing, where non-initial cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

predecessors in a precedence graph, nodes with an outbound arc in a digraph, and completed components in an assembly graph;

in a successor to predecessor build orientation, further including;

deriving a position of an initial cnxpt substantially of the nature of a type selected from the group of;

successors in a precedence graph, nodes with an inbound arc in a digraph, and components in an assembly;

without successors in an extracted structuring of cnxpts based upon the area for placement determined and upon a method selected from the group of;

 

prior position;

 

default value;

 

equidistant spacing;

 

self-organized mapping based upon associations of the initial cnxpt with other cnxpts without successors;

 

arrangement on a circle;

 

arrangement on a sphere;

 

arrangement on the interior of a circle;

 

arrangement on the interior of a sphere;

 

arrangement on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

arrangement in the center of the canvas;

 

and

 

arrangement on a line;

deriving the relative position of a primary predecessor cnxpt of a positioned successor cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of successor cnxpt relative to the predecessor cnxpt;

 

logical distance from a nephew cnxpt of the predecessor cnxpt, the nephew cnxpt a sibling of the successor, given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from a nephew cnxpt of the predecessor cnxpt given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to the edge of the successor cnxpt;

 

relative importance of successor cnxpt with respect to siblings of successor cnxpt;

 

relative importance of predecessor cnxpt with respect to importance of siblings of the predecessor cnxpt;

 

non-overlap rules;

 

successor edge to predecessor edge protection minimums;

 

inter-predecessor cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the predecessor cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving the relative position of an alias for a secondary immediate predecessor cnxpt of a positioned successor cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

and

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

05. basing, where non-root cnxpts are to be interpreted substantially of the nature selected from the group of;

a posteriori, reward, consequent, ending, and completion;

event without successors in an a priori to a posteriori build orientation, further including;

deriving a position of an initial a priori event cnxpt substantially of meaning selected from the group of;

a posteriori, reward, consequent, ending, and completion event;

without predecessors in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of cnxpts representing a priori events without predecessors;

 

default value;

 

equidistant spacing of cnxpts representing a priori events without predecessors;

 

self-organized mapping based upon associations of the initial cnxpts representing a priori events without predecessors with other cnxpts representing a priori events without predecessors;

 

arrangement on a circle of cnxpts representing a priori events without predecessors;

 

arrangement on a sphere of cnxpts representing a priori events without predecessors;

 

arrangement of cnxpts representing a priori events without predecessors on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

and arrangement of cnxpts representing a priori events without predecessors on a line;

deriving the relative position of a cnxpt representing an a posteriori event based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the immediate a priori event predecessor relative to the a posteriori event cnxpt;

 

logical distance from an uncle cnxpt of the cnxpt representing the immediate a priori event predecessor given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from an uncle cnxpt of the a posteriori event cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to edge of a priori event cnxpt;

 

relative importance of the cnxpt representing the immediate a priori event predecessor with respect to siblings of the cnxpt representing the immediate a priori event predecessor;

 

relative importance of an a posteriori event cnxpt with respect to importance of siblings of an a posteriori event cnxpt;

 

non-overlap rules;

 

a priori event predecessor edge to a posteriori event edge protection minimums;

 

inter-child cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the a posteriori event cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving positions of alias indicators of secondary predecessors a priori event cnxpts in an enhanced forest skeletal structure based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

convenience positioning;

06. basing, where non-initial cnxpts are to be interpreted substantially of the substantially of the nature selected from the group of;

a posteriori, reward, consequent, ending, and completion;

event in an end point to start point build orientation, further including;

deriving a position of an initial cnxpt substantially of meaning selected from the group of;

a posteriori, reward, consequent, ending, and completion event;

without successors in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of initial cnxpts without successors;

 

default location value for initial cnxpt;

 

equidistant spacing of initial cnxpts;

 

self-organized mapping based upon associations of the initial cnxpts with other initial cnxpts;

 

arrangement on a circle of initial cnxpts;

 

arrangement on a sphere of initial cnxpts;

 

arrangement of initial cnxpts on an edge of the canvas;

 

arrangement based upon initial cnxpts intersecting cnxpts of a dominant map;

 

arrangement based upon internal cnxpts intersecting cnxpts of a dominant map causing slicing;

 

and

 

arrangement of initial cnxpts on a line;

deriving the relative position of a cnxpt representing a primary a priori event of a positioned a posteriori event based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the a posteriori event cnxpt relative to the immediate a priori event predecessor;

 

logical distance from a nephew cnxpt of the cnxpt representing the immediate a priori event, the nephew cnxpt a sibling of the a posteriori event cnxpt, given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from a nephew cnxpt of the immediate a priori event cnxpt given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to the edge of the a posteriori event cnxpt;

 

relative importance of the cnxpt representing the a posteriori event with respect to siblings of the cnxpt representing the a posteriori event;

 

relative importance of an immediate a priori event predecessor with respect to importance of siblings of the a priori event cnxpt;

 

non-overlap rules;

 

a posteriori event edge to predecessor a priori event edge protection minimums;

 

inter-a priori cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance between sibling a priori cnxpts of the immediate a priori event cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving the relative position of an alias for a secondary immediate a priori event cnxpt of a positioned a posteriori event cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

and

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

07. basing, where non-root cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

subtasks in a project plan, deliverables in a project plan, work package in a project plan, milestones in a project plan, a team, a requirement, participant, stakeholder, a resource, an event in a timeline, a period in a timeline, a required step, a result of a required step, an achievement, a completion, an end point, derivative effort, successor event, and children in a hierarchy;

in a start point to end point build orientation, further including;

deriving a position of an initial cnxpt substantially of the nature of a type selected from the group of;

start point, initiation, tasks in a project plan, major deliverables in a project plan, work package in a project plan, milestones in a project plan, a team, a requirement, participant, stakeholder, a resource, an event in a timeline, a period in a timeline, a required step, a result of a required step, an achievement, derivative effort, predecessor event, and parent in a hierarchy;

without predecessors in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of initial cnxpt;

 

default value;

 

equidistant spacing of initial cnxpts;

 

self-organized mapping based upon associations of the initial cnxpts with other initial cnxpts;

 

arrangement on a circle of initial cnxpts;

 

arrangement on a sphere of initial cnxpts;

 

arrangement of initial cnxpt on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

and

 

arrangement of initial cnxpt on a line;

deriving the relative position of a cnxpt representing a subtask based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the immediate starting point predecessor super-task of the subtask cnxpt;

 

logical distance from a nephew cnxpt of the cnxpt representing the immediate starting point predecessor given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from an uncle cnxpt of the subtask cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

relative importance of the cnxpt representing the immediate starting point predecessor with respect to siblings of the cnxpt representing the immediate starting point predecessor;

 

relative importance of a subtask cnxpt with respect to importance of siblings of a subtask cnxpt;

 

non-overlap rules;

 

starting point predecessor edge to subtask edge protection minimums;

 

inter-child cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the subtask cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving positions of alias indicators of secondary super-tasks or predecessors in an enhanced forest skeletal structure based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

convenience positioning;

08. basing, where non-initial cnxpts are to be interpreted substantially of the nature of a type selected from the group of;

start point, initiation, tasks in a project plan, major deliverables in a project plan, work package in a project plan, milestones in a project plan, a team, a requirement, participant, stakeholder, a resource, an event in a timeline, a period in a timeline, a required step, a result of a required step, an achievement, derivative effort, predecessor event, and parent in a hierarchy;

in an end point to start point build orientation, further including;

deriving a position of an initial cnxpt substantially of meaning selected from the group of;

subtasks in a project plan, deliverables in a project plan, work package in a project plan, milestones in a project plan, a team, a requirement, participant, stakeholder, a resource, an event in a timeline, a period in a timeline, a required step, a result of a required step, an achievement, a completion, an end point, derivative effort, successor event, and children in a hierarchy;

without successors in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of initial cnxpt;

 

default location value for initial cnxpt;

 

equidistant spacing of initial cnxpts;

 

self-organized mapping based upon associations of the initial cnxpts with other initial cnxpts;

 

arrangement on a circle of initial cnxpts;

 

arrangement on a sphere of initial cnxpts;

 

arrangement of initial cnxpts on an edge of the canvas;

 

arrangement based upon initial cnxpts intersecting cnxpts of a dominant map;

 

arrangement based upon internal cnxpts intersecting cnxpts of a dominant map causing slicing;

 

and

 

arrangement of initial cnxpts on a line;

deriving the relative position of a cnxpt representing a primary super-task of a positioned subtask based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the subtask relative to the cnxpt representing the immediate super-task;

 

logical distance from a nephew cnxpt of the cnxpt representing the immediate super-task, the nephew cnxpt a sibling of the subtask, given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from a nephew cnxpt of the super-task cnxpt given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to the edge of the subtask cnxpt;

 

relative importance of the cnxpt representing the subtask with respect to siblings of the cnxpt representing the subtask;

 

relative importance of an super-task cnxpt with respect to importance of siblings of the super-task cnxpt;

 

non-overlap rules;

 

subtask edge to super-task edge protection minimums;

 

inter-super-task cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance between sibling super-task cnxpts of the immediate super-task cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving the relative position of an alias for a secondary super-task cnxpt of a positioned subtask cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

and

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

09. basing, where non-root cnxpts are to be interpreted substantially of the nature selected from the group of;

possible decision, outcome of option, occurrence, reaction, secondary decision, outcome, then consequent, else consequent, reward, chance node, consequent, end result, end node, classification, and completion;

event, termed a consequent node, in start to finish build orientation for a decision tree, further including;

deriving a position of an initial question event cnxpt substantially of meaning selected from the group of;

initial decision, initial environment statement, initial state, criterion, prior decision, prior outcome, prior occurrence, problem statement, broadest categorization, and start node;

event without predecessors, termed a question node, in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of cnxpts representing question events without predecessors;

 

default value;

 

equidistant spacing of cnxpts representing question events without predecessors;

 

self-organized mapping based upon associations of the initial cnxpts representing question events without predecessors with other cnxpts representing question events without predecessors;

 

arrangement on a circle of cnxpts representing question events without predecessors;

 

arrangement on a sphere of cnxpts representing question events without predecessors;

 

arrangement of cnxpts representing question events without predecessors on an edge of the canvas;

 

arrangement based upon intersect cnxpts of a dominant map;

 

arrangement based upon cnxpts of a dominant map causing slicing;

 

and

 

arrangement of cnxpts representing question events without predecessors on a line;

deriving the relative position of a cnxpt representing an consequent event based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the immediate question event predecessor relative to the consequent event cnxpt;

 

logical distance from an uncle cnxpt of the cnxpt representing the immediate question event predecessor given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from an uncle cnxpt of the consequent event cnxpt given strengths of effective relationships with uncles as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to edge of question event cnxpt;

 

relative importance of the cnxpt representing the immediate question event predecessor with respect to siblings of the cnxpt representing the immediate question event predecessor;

 

relative importance of an consequent event cnxpt with respect to importance of siblings of an consequent event cnxpt;

 

non-overlap rules;

 

question event predecessor edge to consequent event edge protection minimums;

 

inter-child cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance from a sibling cnxpt of the consequent event cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving positions of alias indicators of secondary predecessors representing question event cnxpts in an enhanced forest skeletal structure based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

convenience positioning;

and

10. basing, where non-initial cnxpts are to be interpreted substantially of the substantially of the nature selected from the group of;

initial decision, initial environment statement, initial state, criterion, prior decision, prior outcome, prior occurrence, problem statement, broadest categorization, and start node;

event, termed a question node, in a finish to start build orientation for a decision tree, further including;

deriving a position of an initial cnxpt substantially of meaning selected from the group of;

possible decision, outcome of option, occurrence, reaction, secondary decision, outcome, then consequent, else consequent, reward, chance node, consequent, end result, end node, classification, and completion;

event without successors, termed a consequent node, in an extracted structuring of cnxpts based upon the area for placement determined and a method selected from the group of;

 

prior position of initial cnxpts without successors;

 

default location value for initial cnxpt;

 

equidistant spacing of initial cnxpts;

 

self-organized mapping based upon associations of the initial cnxpts with other initial cnxpts;

 

arrangement on a circle of initial cnxpts;

 

arrangement on a sphere of initial cnxpts;

 

arrangement of initial cnxpts on an edge of the canvas;

 

arrangement based upon initial cnxpts intersecting cnxpts of a dominant map;

 

arrangement based upon internal cnxpts intersecting cnxpts of a dominant map causing slicing;

 

and

 

arrangement of initial cnxpts on a line;

deriving the relative position of a cnxpt representing a primary question predecessor of a consequent event based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

bounds of the cnxpt representing the consequent event cnxpt relative to the cnxpt representing the immediate question event predecessor;

 

logical distance from a nephew cnxpt of the cnxpt representing the immediate question event predecessor given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

 

logical distance from a nephew cnxpt of the immediate question event given strengths of effective relationships with nephews as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths and relative distances of sibling cnxpts to the edge of the consequent cnxpt;

 

relative importance of the cnxpt representing the consequent event with respect to siblings of the cnxpt representing the consequent event;

 

relative importance of a question event cnxpt with respect to importance of siblings of the question event cnxpt;

 

non-overlap rules;

 

consequent event predecessor edge to question event edge protection minimums;

 

inter-question cnxpt edge protection minimums;

 

esthetic rules;

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

 

and

 

logical distance between sibling question cnxpts of the immediate question event predecessor cnxpt given strengths of effective relationships with siblings as captured in affinitive tensors due to association strengths in conjunction with accumulated roll-up strengths;

and

deriving the relative position of an alias for a secondary question event cnxpt of a positioned decision event cnxpt based upon one or more factors selected from the group of;

 

prior position;

 

default value;

 

non-overlap rules;

 

esthetic rules;

 

and

 

adjustments due to purlieu or time frame or depth or precedence synchronizations;

and

c. modifying the organization of knowledge and the visualized map based on the positioning of the cnxpt.

61. The method of claim 1, further comprising:

a. initializing fxxt specific ttx map data set of cnxpt instance centroid points;

b. deriving a position of a root cnxpt instance in an extracted forest of extracted trees of cnxpt instances based on hierarchical tensors created where a cnxpt instance that is not seen on any tensor in a child role is taken to be a root of an extracted tree and one of a set of root cnxpt instances where more than one extracted trees exist in said extracted forest, wherein the empty canvas upon which the forest is to be displayed is divided proportionally to the importance of such roots, the centrality of placement on the empty canvas is selected from the group of;

i. for hierarchical forests, the root of greatest importance is placed at the center of the canvas;

ii. for hierarchical forests, the root of greatest importance is placed at the center of mass of the canvas based upon the translation of importance of roots to mass for the calculation;

iii. for hierarchical forests, where a plurality of the roots have a trait usable as a depth offset determiner from one base root, the base root is placed at the center of the canvas;

iv. for precedence forests, the root of greatest importance is placed at the center of the canvas;

v. for precedence forests, the root of greatest importance is placed at the center of mass of the canvas based upon the translation of importance of roots to mass for the calculation;

vi. for precedence forests, where a plurality of the roots have a trait usable as a depth offset determiner from one base root, the base root is placed at the center of the canvas;

vii. for precedence forests, of those dependent cnxpt instances having more than one precedent cnxpt instance in the enhanced descendent forest for the extracted precedence forest and having a first precedent root in a first extracted tree different from a second extracted tree holding a second precedent root for said dependent cnxpt instance, initially select as a dependent second cnxpt instance the dependent cnxpt instance with the greatest difference in depth from said first precedent root and said second precedent root where the depth from said first precedent root is greater, and place said first precedent root at the center of the canvas;

and

viii. for precedence forests, of those dependent cnxpt instances having more than one precedent cnxpt instance in the enhanced descendent forest for the extracted precedence forest and having a first precedent root in a first extracted tree different from a second extracted tree holding a second precedent root for said dependent cnxpt instance, initially select as a dependent second cnxpt instance the dependent cnxpt instance with the greatest difference in depth from said first precedent root and said second precedent root where the depth from said first precedent root is greater, finding all such first precedent roots having the greatest depth, and place one such first precedent root at the center of mass of the canvas based upon the translation of importance of all such first precedent roots to mass for the calculation;

c. determining an error from a possible better position based upon factors selected from the group of;

out of region distance, cnxpt sizing, cnxpt overlap, Euclidean distance from centroid of a child cnxpt to a prior position, Euclidean distance from centroid of a first sibling cnxpt to centroid of a second sibling cnxpt, Euclidean distance from centroid of an uncle to centroid of a child cnxpt, Euclidean distance from centroid of a parent to centroid of a child cnxpt, Euclidean distance from a parent centroid to an uncle, precedence positioning by Euclidean distance from centroid of a precedent cnxpt to centroid of a successor cnxpt, Euclidean distance from centroid of a cnxpt to centroid of a constraint surrogate cnxpt, Euclidean distance from centroid of a child cnxpt to centroid of a representative fraction of the map visualization canvas where cnxpt belongs, and flow positioning;

d. deriving a position of a child cnxpt in an extracted forest of extracted trees of cnxpts based on tensors of the child cnxpt with cnxpts selected from the group of;

parent cnxpt of the child cnxpt, an uncle cnxpt of the child cnxpt, a predecessor cnxpt, a position constraint, a constraint surrogate cnxpt, and a sibling cnxpt of the child cnxpt;

e. modifying the organization of knowledge and the visualized map based on the positioning of the cnxpt;

and

f. updating positions with changes that have the best error reduction effect, until an error metric is reduced to a sufficient level or the descent is limited in its improvement per cycle, or a maximum number of change iterations has occurred;

whereby displayable cnxpt info-items are in positions with a cnxpt positioned inside the ancestor as well as being in the defined segment and relatively closer to the cnxpt'"'"'s uncles.

62. The method of claim 1 to prepare a co-location organization of knowledge, wherein:

a. constructing an organization of knowledge wherein similar concepts are placed relatively closer to one another to achieve a collocation objective wherein the user may better understand that ‘

nearly identical’

pairs of a first cntexxt defined by a first cnxpt and a second cntexxt defined by a second cnxpt being close together based upon;

i. similarity of one or more identity indicators such as the cnxpt name or cnxpt description as given by a semantic difference between said first cnxpt and said cnxpt;

ii. similarity information from one or more users stating an opinion or offering evidence that said first cnxpt is similar or identical to said second cnxpt;

iii. differentiation information from one or more users stating an opinion or offering evidence of a definable difference that said first cnxpt is not similar or not identical to said second cnxpt;

and

iv. information from one or more users stating that said first cnxpt represents a concept subsumed by or subsuming the concept represented by said second cnxpt;

and

b. preparing, optionally, a visualization from the organization of knowledge wherein similar concepts visually appear relatively closer to one another to achieve a collocation objective that is readily accessible;

whereby a tool for associative searching is populated for use with a map;

whereby a visualization may be created from the organization of knowledge to provide a directly understandable representation of the map content.

63. The method of claim 62 to improve residual familiarity, further including:

a. generating bias tensors with weights according to a previously established positioning for respecting prior dxo positions on said map;

and

b. generating positioning for the cnxpts of said map according to process trees for visualization generation, position determination and final sizing means for calculation;

wherein said bias tensors are considered in said determination of positioning of said dxo objects for forming the organization of knowledge and visualization for said map.

64. The method of claim 1, to visualize an organization of knowledge of the domain go wisdom of the commonplace, further comprising:

a. extracting a set of cnxpt instances and association instances based upon fxxt markings of info-items from the commonplace of information, where the map definition prescribed the fxxts to be used;

b. extracting a directed graph of cnxpt instances from said set of cnxpt instances and association instances, generating tensors;

c. generating rollup affinitive tensors;

d. generating positions for cnxpts to form an organization of knowledge from said domain of knowledge;

and

e. displaying a visualization of the cnxpt instances of the organization of knowledge in an associative presentation.

65. The method of claim 1 to improve quality of a generated map as described by an exemplar, further comprising:

a. creating a map definition for which an instance will be generated to be tested for quality against an exemplar, the exemplar generated from the same or very similar map definition;

b. generating a map instance for comparison for said map;

c. generating an initial exemplar map by an approach selected from the group of;

accepting a stated normative placement positioning of cnxpts in a map, and accepting a fxxt as a replacement for a specific fxxt of those in the map definition from which to generate an exemplar map instance stating normative placement positioning of cnxpts;

d. computing an error cost value based upon the positions of generated cnxpts in the map instance for comparison relative to the normative placements in the exemplar;

and

e. determining an alternative set of fxxt weighting coefficients indicating a proportionality of impact wherein a generated alternative map definition based upon the alternative set of fxxt weighting coefficients indicating a proportionality of impact results in an acceptably low value of the error cost value based upon positions of generated map cnxpts relative to the normative placements or the error cost value fails to decrease at an acceptably high rate or a predetermined number of cycles have been performed.

66. The method of claim 1 to improve quality of the generated map as described by an exemplar, to also accept user training, further including:

a. creating a map definition for which an instance will be generated to be tested for quality against an exemplar, the exemplar generated from the same or very similar map definition;

b. generating a map instance for comparison from said map definition;

c. generating an initial exemplar map by an approach selected from the group of;

accepting a stated normative placement positioning of cnxpts in a map, and accepting a fxxt as a replacement for a specific fxxt of those in the map definition from which to generate an exemplar map stating normative placement positioning of cnxpts;

d. accepting an initial set of quality metrics to comprise a cost function for determining an error cost value when comparing the map instance for comparison against the exemplar map;

e. accepting repositioning of zero or more cnxpt positions in the exemplar map by a user;

f. accepting a user command to open the map instance for comparison to be compared against the exemplar map;

g. accepting changes to the map instance for comparison to alter the organization of knowledge of the map instance for comparison by altering a visualization of the map instance for comparison by zero or more of a user command selected from the group of;

i. accepting repositioning of zero or more cnxpts in a visualization by a user;

ii. accepting re-categorization of zero or more cnxpts in a visualization by a user;

and

iii. accepting manual resolution of zero or more positioning defects in a visualization;

h. recalculating object positions in the organization of knowledge based upon the object locations in the visualization;

i. determining improved map definition from one or more determinations of an improved set of fxxt coefficients indicating a proportionality of impact in the map instance for comparison based upon finding an acceptably near minimum error cost value, the error cost value calculated by the cost function on differences in organization of knowledge from exemplar map to a version of the map instance for comparison after forming the version of the map instance for comparison by fxxt extractions, forest extractions, roll-ups, and positionings, the choice of fxxt coefficients indicating a proportionality of impact used to generate the version of the map instance for comparison based upon calculations selected from the group of;

i. applying one or more sets of algorithmically chosen fxxt coefficients indicating a proportionality of impact, the algorithm determined from a list of one or more algorithms;

ii. accepting manually entered values for fxxt coefficients indicating a proportionality of impact of one or more fxxts from which visualization was derived;

and

iii. determining values of fxxt coefficients indicating a proportionality of impact based upon analysis of functions for determining an error cost value, the functions derived from inspection of changes in error cost value based upon factors from the definition and formation of the map instance for comparison, the factors selected from the group of;

changes in fxxt coefficients indicating a proportionality of impact in the exemplar map, fxxt definitions of the exemplar map, forest extraction algorithm utilized in the exemplar map, roll-up algorithm utilized in the exemplar map, positioning algorithms utilized to generate the locations of cnxpts in the visualization of the organization of knowledge of the exemplar map, changes in fxxt coefficients indicating a proportionality of impact in the map instance for comparison, fxxt definitions of the map instance for comparison, forest extraction algorithm utilized in the map instance for comparison, roll-up algorithm utilized in the map instance for comparison, positioning algorithms utilized to generate the locations of cnxpts in the visualization of the organization of knowledge of the map instance for comparison, individual quality metrics, and the cost function;

j. stopping the recalculation process when the error metric cost value shows little improvement after a predefined number of recalculations, or the error metric cost value reaches an acceptably low value, or the error metric cost value fails to decrease at an acceptably high rate;

and

k. completing zero or more cycles wherein;

accepting an alteration of one or more quality metric to comprise a revised cost function and repeating determining an improved map definition from one or more determinations of an improved set of fxxt coefficients indicating a proportionality of impact in the map instance for comparison based upon finding an acceptably near minimum error cost value from the revised cost function;

whereby user changes regarding an exemplar and repositioning in said visualization as calculated based upon user votes provide a training pattern for fxxt coefficients;

whereby alterations in quality metrics are used to tune determinations of cost functions for improved use of exemplars in comparisons;

whereby quality improvement of maps, map generation, and the map comparison process are each possible.

67. The method of claim 1 to also provide for providing ontology statistical analysis and modeling, comprising:

a. forming a series of models from an ontology until the rate of improvement decreases to a pre-determined rate, wherein;

i. forming a plurality of set extraction specifications partitioning the contents of an ontology into one or more identified extraction sets, the nodes of the ontology being object classes, the relationships of the ontology being object classes to support node classes, the instances of the nodes of the ontology having storage to hold zero or more values and formulas to determine said zero or more values;

ii. creating a map definition for which an instance will be generated to be tested for quality against an exemplar;

iii. generating a map instance for comparison from said map definition, wherein;

01. accepting a structuring of an ontology as a basis for modeling by specifying a weighting coefficient indicating a proportionality of impact for an extraction set wherein said extraction set is included into a named derived ontology;

02. extracting the extraction sets of ontology components into a named derived ontology, wherein the strength of every relationship instance added to the named derived ontology during extraction becomes the weighting coefficient indicating a proportionality of impact multiplied by the relationship strength in the original ontology, wherein the node importance of every node instance added to the named derived ontology during extraction becomes the weighting coefficient indicating a proportionality of impact multiplied by the node importance in the original ontology;

and

03. developing a skeletal structure from the named derived ontology according to fxxt basic descendant spanning tree extraction means, respecting the weighting coefficient indicating a proportionality of impact of said extraction sets as incorporated in the named derived ontology relationships and nodes;

and

iv. calculating a model result from the structured named derived ontology by computing the zero or more values of each node instance, respecting the skeletal structure, the model result comprising the zero or more values of each node instance;

and

b. improving the model according to an exemplar map, wherein;

i. generating an initial exemplar map by an approach selected from the group of;

accepting a stated normative placement positioning of cnxpts in a map, accepting a fxxt as a replacement for a specific fxxt of those in the map definition from which to generate an exemplar map stating normative placement positioning of cnxpts, generating a second copy of the map instance for comparison and accepting into the second copy of the map instance for comparison for use as comparators zero or more normative results anticipated of the modeling, and accepting for use as comparators zero or more normative results anticipated of the modeling the normative results in the form of a map;

the normative results stated in the storage held by info-items of the map, each normative result specific to an identifiable model result;

ii. computing an error metric cost function for the differential between the modeling results and the normative results;

iii. adjusting the weighting coefficients indicating a proportionality of impact assigning a weighting variation to the extraction sets to reduce the cost value result of said error metric cost function wherein the model results based upon the weighting variation are nearer to said normative results based upon the cost value result of said error metric cost function;

and

iv. accepting said set of newly assigned weighting variation weighting coefficients indicating a proportionality of impact as an acceptable set for a model to achieve a more satisfactory predictive result;

whereby a map provides a structure to aid in both controlling and improving a model based upon a commonplace.

68. The method of claim 1, to calculate quality corrections according to prediction correction mechanism utilizing fxxts, wherein:

a. creating a map definition for which an instance will be generated to be tested for quality against an exemplar, the exemplar generated from the same or very similar map definition;

b. generating a map instance for comparison from said map definition;

c. generating an initial exemplar map by an approach selected from the group of;

accepting a stated normative placement positioning of cnxpts in a map, and accepting a fxxt as a replacement for a specific fxxt of those in the map definition from which to generate an exemplar map stating normative placement positioning of cnxpts;

d. repeatedly determining an error cost value based upon distances of the positions of the generated map cnxpts as cntexxt centers in a map for comparison from exemplar cnxpt placements for similar concept giving the normative placements;

further including;

i. accepting zero or more repositionings of one or more exemplar positions in the exemplar map by a user;

ii. accepting zero or more repositionings of one or more cnxpts in the map for comparison by a user;

iii. accepting zero or more re-categorizations of one or more cnxpts in the map for comparison by a user;

iv. accepting zero or more manual resolutions of one or more positioning defects in the map for comparison;

v. accepting zero or more manual changes of fxxt weighting coefficients indicating a proportionality of impact of one or more fxxts from which the map for comparison visualization was derived;

vi. recalculating display object positions based upon user changes in the map for comparison visualization;

vii. determining an alternative set of fxxt weighting coefficients indicating a proportionality of impact wherein a generated alternative map for comparison based upon the alternative set of fxxt weighting coefficients results in an acceptably low value of the error cost based upon positions of generated map cnxpts relative to the normative placements in the exemplar map or the error cost value fails to decrease at an acceptably high rate or a predetermined number of cycles have been performed;

viii. re-determining improved fxxt weighting coefficients indicating a proportionality of impact based upon quality error cost value calculations, fxxt extractions, forest extractions, roll-ups, and positionings in an alternative map for comparison;

ix. adjusting weighting coefficients indicating a proportionality of impact for fxxts based upon said alternative set of fxxt weighting coefficients and generating in an alternative map for comparison, and repeating the cycle;

x. re-determining fxxt extraction, forest extraction, and roll-ups based upon quality determinations and user changes affecting the alternative map for comparison;

and

xi. stopping the recalculation process when the error metric cost value shows little improvement after a predefined number of recalculations, or the error metric cost value reaches an acceptably low value, or the error metric cost value fails to decrease at an acceptably high rate;

whereby a map exemplar can convey to a map and model system a baseline expectation of the model;

whereby the method provides a tool for comparison of;

a market'"'"'s change over time based upon market structure differences, a market'"'"'s change over time based upon market data differences, a difference of a new production paradigm to an older one, a complex data collection approach versus an original mode of data collection, how the performance of a process might affect a result, whether a complex report from a source is believable given information known by a disparate team, how an econometric mode would need to be altered given a new set of data, whether a thinking pattern of a group affects a modeling result, and how a mindset of one group is different from another or affects a model result;

whereby use of votes and consensus computation provides for reapplying corrections where new data is ingested that contains the same error.

69. The method of claim 1 to improve map quality, further comprising modifying at least one item selected from the group of:

the subset of fxxts, the weights assigned to the subset of fxxts, the weights of the associations in the fxxts extracted, and the assignment of a cnxpt to a fxxt extracted.

70. The method of claim 1 to also provide protecting against unapproved or unpaid release of private information intended to be protected while held in the commonplace, further comprising:

a. controlling access by the user by identification of user, authentication, granting of access to the commonplace content;

b. performing fee-based usage and usage right granting of for fee functions;

c. controlling the user'"'"'s adding of information to the commonplace;

d. controlling participation by the user in one or more marketplaces for ideas;

e. controlling participation by the user in one or more marketplaces for data related to specific concepts categorized in the commonplace;

f. controlling access by the user to functions for establishing protection for an idea, granting access to the idea, granting access to project teams involved with applying the idea, and, if novel, to legal protection for the idea;

g. controlling access by the user to tools for ideating, searching, organizing, protecting, commercializing, communicating, and extending an idea in the commonplace;

and

h. controlling presentations of results to users and accepting navigation and other user commands for use of said maps, to at least one of registering votes for changes or causing changes to said commonplace content according to alter information through visualization means.

71. The method of claim 1, further comprising:

a. enabling participation around a categorization;

b. managing multi-source collaboration by consensus;

and

c. incentivizing creation of new or refining of knowledge.

72. The method of claim 1 to also provide forming a profit, further comprising:

a. deriving a chain of events structuring of ownership changes regarding a venture exploiting at least one idea, further comprising;

i. accepting a definition of a consortium showing an intent to exploit at least one cnxpt;

ii. accepting at least one request regarding participation in the consortium;

and

iii. providing a value creation protocol for the consortium that comprises a group of at least one related cnxpt, further including;

01. generating at least one first ownership right for the consortium;

02. generating a transactional data stream for communication regarding the consortium;

03. generating a first transaction regarding at least one related cnxpt by encapsulating into the transaction information selected from the group of;

information regarding request for a new ownership right in favor of a second user, second user identifying data, second user appropriate origination data related to said new ownership right, and cnxpt identity of said at least one related property cnxpt;

04. adding information regarding a first transaction into the transactional data stream;

05. distributing the transaction through the transactional data stream;

and

06. granting access to said consortium transaction according to said first ownership right.

73. The method of claim 1, to utilize assistance of others or experts when necessary in adaptive resource allocation, further including:

a. engaging zero or more others for work of a nature selected from the group of;

i. in the role of qualified data scientist in the data curation loop to determine questions that need to be answered from the input data and selecting analytics to apply for finding answers and performing automated error detection;

ii. in selecting an analytic to apply wherein sponsoring business articulates the value of running the analytic;

and

iii. in the role of qualified domain expert to answer data-centric questions regarding input data;

b. establishing zero or more incentives for others selected from the group of;

i. incenting the data creator or owner;

ii. incenting data producing human to curate and integrate data into said commonplace at the source;

iii. incenting data using human to curate and express opinion regarding correctness of data into said commonplace at the point in the process where wrong data causes sufficient frustration to cause responsive actions by knowledgeable users;

iv. incenting openly rather than hiding the operations to generate sense of participation and openness;

v. incenting specialized knowledge is required for data curation by identifying domain where human has expertise and their amount of expertise, from a novice level to enterprise expert;

and

vi. incentivizing business experts to assist in making curation decisions with hierarchy of experts inside an enterprise as well as various kinds of expertise externally;

and

c. accepting and processing one or more request selected from the group of;

i. registering one or more curating sponsors for data curation and noting compensation they offer for curation of the data they are seeking curation of;

ii. stating task definition and role curators are to fulfill;

iii. determining domain knowledge and skills requirements of curators;

iv. identifying data resources that require curation;

v. finding enterprise data sources;

vi. searching for data needing review wherein the data to be retrieved is within subject matter expertise domain knowledge of searcher, wherein said one or more curating sponsors for data curation have offered a higher level of compensation for the data retrieval than other such data;

vii. phasing of project to perform incremental identification, metadata adjustment, integration, reviewing iterations;

viii. scheduling resources adaptively;

ix. crawling to search a corporate internet to locate relevant data sources;

x. registering data to be curated;

xi. enlisting crowdsourcing labor;

xii. generating a fxxt under which the loaded data will be marked;

xiii. entering detailed provenance information regarding the data source and data segment identity information into said commonplace as an irxt instance marked by said fxxt;

xiv. invoking analytics to apply initial opinions regarding quality of knowledge of data sets by detailed provenance;

xv. establishing a data set segmentation structuring paradigm for the data to be curated as a detailed provenance record set;

xvi. loading data sets on a trial basis;

xvii. ingesting base data info-items for typing and traits while tracking detailed provenance and marking said base data info-items by said fxxt;

xviii. tracking by detailed provenance tasks for trial loading and successive reloads, identifying segments loaded by updating detailed provenance, stating a metric for data set quality after each segment incrementally loaded, and identifying as ready for detailed review iterations each successfully loaded data set segment;

xix. registering as a prioritized task and detailed provenance the necessity of a specific repair of an erroneous data set, based upon opinions recorded and resources available, on an irxt instance for tracking, marking said irxt instance by said fxxt;

xx. applying changes to data set data to fix errors based upon failure to properly load or quality found below a predetermined level of trustworthiness of opinion;

xxi. recording on an irxt instance for each data segment an opinion regarding the quality and veracity of the incrementally loaded data segment by detailed provenance identification based upon trustworthiness of opinion from viewpoint of sponsor and trustworthiness of data specialist involved in curation;

xxii. generating a cnxpt instance for each identifiable concept from a loaded data set segment, relating to said cnxpt instance the irxt instance being used for tracking of the data segment by an occurrence, assigning a default importance weighting for said cnxpt instance, and marking it by said fxxt;

xxiii. generating an association instance for each relationship of a first concept from a loaded data set segment, the first concept represented by a first cnxpt instance, to a second concept represented by a second cnxpt instance possibly of a different data source, assigning a default strength weighting for said association instance, marking the association instance by said fxxt;

xxiv. applying an analytic to obtain machine learning results from one or more algorithms that will generate one or more cnxpt or association instances and set a default weighting automatically on each generated instance;

xxv. iterating, until the curation effort is sufficiently complete, thorough unfinished work tasks, applying changes to weightings on generated association and cnxpt instances as concepts and relationships between cnxpts are better understood;

xxvi. executing modeling to generate a prediction;

and

xxvii. calculating quality corrections according to prediction correction mechanism.

74. The method of claim 1 to allow commonplace of information to be utilized in remote commonplaces without loss of control, further including:

a. providing an extracted commonplace separate from the primary controlled commonplace;

b. extracting portions of an individually identified record of information from said controlled commonplace into a partial record;

c. assigning a different unique identifier for said partial record to form an individually identified partial record according to key encryption means;

d. communicating said individually identified partial record into a foreign commonplace;

and

e. indexing information of said foreign commonplace to said individually identified partial record by referencing said different unique identifier according to key encryption means.

75. The method of claim 1 to also provide communication sessions earmarked to a cnxpt, further including:

a. providing a controlled communications information repository;

b. providing tools for communicating regarding a ttx on a confidential basis with others on a narrow-chat basis knowing the expertise of the other party merely because of their willingness to communicate on the narrow-chat basis for a specific ttx category with those of similar level of expertise;

and

c. establishing on-demand communication between users earmarked to designated ttx when requested with a command accepted through one or more access controlled interfaces.

76. The method of claim 75 to establish communications earmarked to a cnxpt, further comprising:

a. determining, by at least one processor, at least one user display visualization according to map generation means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

b. displaying to said user a portion of said organization of knowledge of at least one domain of wisdom according to display and delivery means;

and

c. accepting and processing a user command to request a connection with a person showing interest regarding concepts within a context represented by a cnxpt, the interest selected from the group of;

recent expertise, registered subscription, inventorship, investment interest, and a wish shown to purchase.

77. The method of claim 1, wherein distributing the subsets extracted from the commonplace of information comprises distributing immutable subsets among the multiple computer storages wherein each subset is uniquely identifiable by an extraction identifier;

whereby the state of commonplace information is preserved by timeframe.

78. The method of claim 1 to also structure modeling, further including:

a. accepting a model definition for an info-item property to establish a repeatable calculation procedure for generating a value for said property from said commonplace;

b. collecting commonplace of information as base information for said model;

and

c. accepting zero or more estimates for said info-item property to establish a baseline for detecting problems with said model, for acting in said place of said calculation before it works, and to act as a default value;

whereby a set of calculations is established to obtain values for info-item properties to be applied to each instance of said info-item in a set specified by said model.

79. The method of claim 78 to also form a value estimate of a tcept, further comprising:

a. limiting the calculating by imputation of value from appcepts related by a satisfaction of need relationship by the time frame of availability and non-obsolescence of the tcept;

whereby prediction by space of applications of technology is imputed to determine values of technologies satisfying the requirements of a set of applications.

80. The method of claim 78 to also predict, further including:

a. accepting a prediction definition for a map specification to establish a repeatable procedure for generating a value for said prediction from said commonplace based upon said map;

b. calculating preliminary predictions not depending upon hierarchy according to preliminary prediction calculation means;

and

c. calculating prediction for each cnxpt at a level by level of a formed map tree taxonomy according to forming predictions means;

whereby a set of calculations is established to obtain values for cnxpt info-item properties to be applied to each instance of a cnxpt in a set specified by said prediction specification.

81. The method of claim 1 to perform modeling wherein the method further comprises:

a. combining into a predictive model at least one form of information selected from the group of;

attribute value of structured entity, property of relationship, property of association, property of tensor, property of ttx, property of cnxpt, function of property of group of ttxs, function of property of group of cnxpts, parsing of text into indication of value, parsing of text into indication of relative position, parsing of text into semantic roles, structured text, numerical values, equation, algorithm, unstructured textual value, probability density function definition, statistical sampling, function, data set, probability mass function definition, and a distribution;

and

b. applying interpretations of predictive model to predict results.

82. The method of claim 81 to also form an estimate of a metric of a cnxpt, further including:

a. calculating the total metric value as the sum of the metric values of the children of the cnxpt in an extracted forest of cnxpts;

whereby prediction utilizes the calculation of metrics of cnxpt children.

83. The method of claim 81 to perform modeling on the basis of a structuring of info-items, further comprising:

a. structuring an organization of knowledge from an extraction of info-items from the commonplace of information;

and

b. determining a modeling result by interpreting the model;

wherein the structuring involves at least one criterion selected from the group of;

i. modeling is on the basis of a single forest of trees categorization;

ii. modeling is based upon multiple sub-categorizations with roots where at least one of the categorization cnxpts are of a different type or nature;

iii. modeling is based upon multiple sub-categorizations with roots where at least one inter-category association is of a different type in each said sub-categorizations sub-tree;

iv. modeling is based upon multiple forest of trees categorizations where at least one of the cnxpts are of a different type or nature, or at least one root occurs in only one forest, or at least one inter-category association is of a different type in each said forest;

v. modeling is based upon dependency, precedence, causality, or surrogate causality;

vi. modeling is based upon probability density functions for outcomes of a dependency, a precedence, a causality, or a surrogate causality;

vii. modeling is based upon categorization to determine result and result is determined based upon causality or surrogate causality wherein a causal association info-item exists between a parent to child category and a set, voted, probabilistically expected strength of associations between children and their possible parents is determinant;

viii. modeling is based upon a categorization where end products are shown as assemblies of constituent parts or work tasks, each being represented by a category;

ix. modeling is based upon a categorization where organizations are shown as groupings of individuals or functions, each being represented by a category;

x. modeling is based upon a categorization where outcomes are prioritized, tasks are prioritized;

tasks are assigned or work completed by category;

xi. modeling is based upon a categorization where prioritization or decisions are made by category;

xii. modeling is based upon a categorization where strategies are subdivided into plan phases or results each being represented by a category;

xiii. modeling is based upon a matching of categories between a plurality of single forest of trees categorizations;

xiv. modeling is based upon a calculation involving a property of an info-item;

xv. modeling is based upon a calculation involving a property of another info-item;

and

xvi. modeling is based upon an association occurring between a first category of a first single forest of trees categorization and a second category of a second single forest of trees categorization.

84. The method of claim 1 to also form an estimate of a metric of a cnxpt, further including:

a. calculating total space consumed by the two-dimensional area occupied by a cnxpt taken over all cnxpts shown on a visualization of a map of cnxpts at a given depth of said visualization of the map;

b. calculating by estimate, model, or imputation the total metric for all cnxpts shown on the visualization of the map of cnxpts at the given depth of said visualization of the map;

and

c. calculating the metric for the cnxpt based upon proportion of space by dividing the area of the cnxpt by the total space consumed on a visualization of the map of cnxpts at the depth of the cnxpt on the visualization of the map and multiplying the proportion by the total metric;

whereby prediction by space utilizes the calculation of metrics by space consumed on the map of cnxpts up to the horizon shown, or upon, including but not limited to;

interest shown, and predictions affecting sizing;

whereby the proportion of space allotted to a cnxpt, in specific fxxts serving as the basis, is calculated from the resulting size of the cnxpt.

85. The computer-implemented method of claim 1, further comprising:

a. providing modeling rule interpretation software instructing what if value analysis;

b. providing zero or more modeling tools for what if value analysis tuned to operate on said categorizations produced according to map generation means;

c. accepting zero or more definitions of a condition equation for a result based upon zero or more specific variables attached to zero or more referenced cnxpts;

d. accepting zero or more definitions of an outcome specification stating expected or potential outcomes in terms of modeling conditions that, if met, imply that the outcome will occur;

e. accepting at least one definition of a model;

f. accepting, for said at least one definition of a model, at least one definition of a modeling rule, said modeling rule selected from the group of;

calculation modeling rule, constraint modeling rule, and information base modeling rule, said at least one modeling rule specifying at least one equation to attach to at least one cnxpt;

g. accepting zero or more definitions of one or more default values of a type required, said default value type selected from the group of;

predetermined analytic control default value, predetermined analytic default result value, modeling variable default value, modeling parameter default value, modeling result default value, prediction parameter default value, and prediction result default value;

h. accepting a command to initiate processing of calculation specifications of a predetermined set of info-items;

i. accepting zero or more commands to initiate a methodology;

j. accepting zero or more definitions of one or more data fault mechanisms for raising an error indication, said data fault mechanism selected from the group of;

predetermined analytic data fault mechanism, modeling data fault mechanism, and prediction data fault mechanism;

k. accepting zero or more commands to initiate a workflow;

l. accepting zero or more definitions of one or more what if value analysis scenarios tuned to operate on a predetermined fxxt;

m. accepting zero or more definitions of a commonality determination rule stating an enrolling of a modeling tool for competitive analysis by what if value analysis tuned to operate on said commonplace and said categorizations produced according to map generation means;

n. accepting zero or more commands to initiate what if modeling;

o. accepting zero or more changes to said knowledge model of said commonplace;

p. accepting zero or more commands to initiate processing of different subject matter for generating a predetermined visualization;

q. accepting zero or more definitions of belief distribution functions;

r. accepting zero or more commands to initiate prediction management to manage acceptance of belief votes;

s. accepting zero or more belief votes, said belief votes selected from the group of;

subjective opinion votes, estimation votes, and analytic result votes;

t. accepting zero or more definitions of a prediction specification, said prediction specification'"'"'s type selected from the group of;

info-item specific, non-fxxt based prediction, and fxxt specific;

and

u. assembling predictions according to forming predictions means to calculate properties of info-items based upon the modeling rules specified for the info-item either by info-item type or for a specific instance of the info-item, without regard to any fxxt based taxonomy according to preliminary prediction calculation means.

86. The method of claim 1 to perform multi-forest modeling on the basis of single forests of trees, further including:

a. executing one or more cnxpt sub-setting operations selected from the group of;

a query, a reduction, a derived ontology, a fxxt extraction, a flow extraction, execution of an analytic, selection of a data set, selection of a portfolio, selection of a uniquely identified categorization, selection of a uniquely identified clump extract set, a filter application, or a user ad hoc selection set of cnxpts to obtain a set of cnxpts resulting from each of said sub-setting operations;

b. forming an area of consideration from each said set of cnxpts defining a forest of trees and the relationships extracted according to apply fxxt specification means based upon zero or more fxxt markings for said set of cnxpts;

c. extracting a descendent tree forest from each said area of consideration according to fxxt basic descendant spanning tree extraction means where results of modeling rule formulas are dependent upon tree structure and positioning;

d. interpreting said modeling rule formulas associated with said cnxpts in each said area of consideration where results of said modeling rule formulas are considered in positioning process and said modeling rule formulas do not depend upon positioning of cnxpts or where results of said modeling rule formulas are not considered in positioning process;

e. determining positioning of cnxpts in each said area of consideration on a predetermined visualization where results of said positioning results are to be considered in said modeling rule formulas according to process trees for visualization generation, position determination and final sizing means;

f. interpreting said modeling rule formulas associated with said cnxpts in each said area of consideration where results of said modeling rule formulas depend upon positioning of cnxpts;

g. applying zero or more filters determining inclusion based upon characteristics of cnxpts to eliminate one or more cnxpts of said area of interest;

h. re-interpreting said modeling rule formulas associated with said cnxpts remaining in each said area of consideration;

i. forming a set of intersection identifying tuples wherein each tuple is an ordered tuple of dimensionality set by the number of dimension forests obtained by said sub-setting operations and wherein each tuple is constructed by selecting one cnxpt from each set of cnxpts defining a dimension to hold a tuple position associated with the dimension identified by the order of said position in the tuple;

j. forming a subset of said intersection identifying tuples by extracting relationships according to apply fxxt specification means based upon zero or more fxxt markings wherein only tuples where the cnxpts of the tuple are fully connected by said extracted relationships are in said subset of said intersection identifying tuples;

k. applying zero or more filters determining inclusion based upon characteristics of cnxpts named in a valid intersection tuple to eliminate one or more intersection identifying tuples;

l. generating a plurality of model result tuples each associated with one said intersection identifying tuple and of;

values resulting from execution of modeling rule formulas on characteristics of said cnxpts forming a tuple in said subset of said intersection identifying tuples;

and

m. generating a model results data package of;

the set of said plurality of intersection identifying tuples each with associated model result tuple.

87. The method of claim 1 to perform modeling on the basis of one or more maps and one or more modeling rules, further including:

a. accepting a set of one or more modeling rules;

b. creating an empty first derived ontology;

c. determining the nature of each modeling rule to plan model execution;

d. executing one or more cnxpt sub-setting operation to obtain a set of cnxpts and associations in a first derived ontology resulting from said sub-setting operation;

e. executing all rules that determine whether a cnxpt or an association should or should not be in said first derived ontology;

f. executing all rules that determine a value of a property of a cnxpt or an association that could affect the skeletal structuring of a map being generated from said first derived ontology;

g. extracting a descendent tree forest from said first derived ontology according to fxxt basic descendant spanning tree extraction means while utilizing modeling rules that determine whether an association should or should not be used in the skeletal structure of a map to be generated from said first derived ontology;

h. executing production of enhanced descendent forest, basic ascending forest, and enhanced ascending forest using the descendant spanning forest and said first derived ontology;

i. executing all rules that depend upon results of generating forests but not later steps of map generation;

j. executing all rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied prior to roll-ups;

k. executing roll-ups on the generated forests while executing rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied during roll-ups;

l. executing all rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied after roll-ups;

m. executing positioning on the generated forests after roll-ups, utilizing all rules that could affect the positioning of info-items on a map being generated from said first derived ontology and that must be applied during positioning, according to process trees for visualization generation, position determination and final sizing means;

n. executing all rules that depend upon results of positioning but not later steps in map generation;

o. determining efficient derivation trees from each rule of type;

p. interpreting modeling rules iteratively based upon the derivation trees;

and

q. returning control to the supervising process while monitoring for triggering due to a change of data or organization of info-items;

whereby efficient modeling including interpretation of cell-like formulas for properties of cnxpts is performed.

88. The method of claim 1 to also provide for ontology statistical analysis and modeling, further comprising:

a. accepting a structuring of an ontology as a model basis;

b. calculating a model result from said model basis;

c. accepting a normative result anticipated of the modeling;

d. computing an error metric for the differential between the modeling result of the structuring and the normative solution;

e. adjusting the weighting coefficients indicating a proportionality of impact assigning weighting to said set extractions to reduce said error metric wherein a secondary model result is nearer to said normative result;

and

f. accepting said set of assigned weighting coefficients indicating a proportionality of impact as an acceptable set for a model to achieve a satisfactory predictive result.

89. The method of claim 1, to produce a map from a commonplace of information demarcating what is completed of a process from what is not completed at any point in time, further comprising:

a. extracting a structuring of cnxpts where a dimension presents a time aspect where the oldest cnxpt appears earliest and a cnxpt predicted to be most toward the future appears as latest;

and

b. slicing the structuring by a timeline as a plane representing a time horizon to prepare an organization of knowledge where the cnxpts anticipated to be incomplete at the time of the timeline fall to the future side of the timeline and are optionally not shown, and the cnxpts anticipated to be complete at the time of the timeline fall to the more historic side of the timeline and are optionally not shown;

wherein the visualization of the organization of knowledge presents at least one cnxpt or informs the user that all cnxpts are hidden.

90. The method of claim 89 to produce a demarcation on a map from a commonplace of information, further comprising:

a. extracting a forest of cnxpts to position cnxpts in a organization of knowledge having two or more dimensions;

b. dividing the map by positions of cnxpts by drawing a demarcation hyperplane of a type selected from the group of;

i. time, further including;

01. drawing a demarcation hyperplane of a type based upon dimensionality selected from the group of;

a line perpendicular to the flow of time in a two-dimensional organization of knowledge, a plane perpendicular to the flow of time in a three-dimensional organization of knowledge, and a hyperplane perpendicular to the flow of time in a dimensionality greater than three but reduced to three for display;

the hyperplane representing a time point in the flow of time represented by the positioning of cnxpts in the visualizable organization of knowledge of at least one domain of wisdom derived from the commonplace of information, wherein the time point hyperplane is substantially positioned at a first distance from the oldest root cnxpt and at a second distance from a cnxpt that is predicted to be the most into the future;

02. slicing the forest across on said hyperplane and flattening the organization of knowledge to show root cnxpts and those cnxpts on or more shallow than the hyperplane to prepare a two-dimensional flattened visualization where the cnxpts further than the hyperplane from the earliest root are not shown, the two-dimensional slice representing a time horizon;

and

03. interpreting the demarcation hyperplane to substantially be an indication selected from the group of;

the demarcation separating what is known from that which is unknown at any chosen point in time stated by a time horizon, the substantiality of knowledge high for time horizons earlier than the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating what is completed of a process from what is not completed at any chosen point in time stated by a time horizon, the substantiality of knowledge high for time horizons earlier than the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating the time frames of a technology selected from the group of;

including where the feasibility of the technology is essentially zero from a time frame where the technology may be formed into a product, the time of the technology reaching a sales goal, the time of the technology reaching a determined point in marketability of a set of features, the time of the technology reaching breakeven on investment, the time of the technology being productized from a time frame where the technology may have captured its maximal market, the time of the technology losing its competitive edge from a time frame where the technology may be a cash cow, and the time of the technology being a cash cow from a time frame where the technology may have become ineffective as a product;

the substantiality of knowledge high for time horizons prior to the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating the time frame phases in a battle plan, the substantiality of knowledge high for time horizons prior to the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating the time frame phases in a legal case, the substantiality of knowledge high for time horizons prior to the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating the time frame phases in a logististics or operations management plan, the substantiality of knowledge high for time horizons prior to the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

and

the demarcation separating what outcomes have been achieved or are highly likely from what outcomes are merely anticipated at any chosen point in time stated by a time horizon relative to the probabilistic model viewed, the substantiality of knowledge high for time horizons earlier than the presumed state of completion of the probabilistic model, the substantiality of knowledge predicted for time horizons more futuristic than the presumed state of completion of the probabilistic model;

and

ii. agreement regarding belief at a time horizon, further including;

01. accepting a cut-off value for consensus proportion from the user, the cut-off regarding the percentage of those agreeing to a belief represented by a cnxpt as determined by the existence and veracity of the association where the cnxpt has a role examined in conjunction with votes regarding the veracity of the cnxpt itself, the cut-off stating acceptability of a cnxpt having an expressed belief level percentage higher than the cut-off in the population of voters reflected in the derived ontology for the map instance;

wherein the cut-off to improve the believability that the model stated by the map honorably reflects that beliefs are reflected by such associations and stated votes regarding beliefs represented by cnxpts;

02. re-extracting the forest from the derived ontology of the map wherein only associations that represent time related orderings are considered for use as hierarchical tensors, wherein constrictions are applied on generation of hierarchical tensors as selected from the group of;

removing from consideration the associations having a product of association consensus proportion and veracity consensus of the cnxpt in the child role of the association that is below the cut-off, generating hierarchical tensors with consensus weights greater than a cut-off for cnxpt veracity votes to eliminate low veracity cnxpts from roles in associations to cause association elimination from consideration, and generating hierarchical tensors with consensus weights greater than a cut-off for association veracity;

03. drawing a demarcation hyperplane of a type based upon dimensionality selected from the group of;

a line perpendicular to the flow of time in a two-dimensional visualization, a plane perpendicular to the flow of time in a three-dimensional visualization, and a hyperplane perpendicular to the flow of time in a dimensionality greater than three but reduced to three for display;

the hyperplane represents a time point in the flow of time represented by the positioning of cnxpts in the visualizable domain of wisdom derived from the commonplace of information, wherein the time point hyperplane is substantially positioned at a first distance from the oldest root cnxpt and at a second distance from a cnxpt that is predicted to be the most toward the future;

04. slicing the forest across on said hyperplane and flattening the visualization to show root cnxpts and those cnxpts on or more shallow than the hyperplane to prepare a two-dimensional flattened visualization where the cnxpts further than the hyperplane from the earliest root are not shown, the two-dimensional slice representing a time horizon;

and

05. interpreting the demarcation hyperplane to substantially be an indication selected from the group of;

the demarcation separating what is commonly accepted as known from that which is unknown or not commonly accepted as known at any chosen point in time stated by a time horizon, the substantiality of knowledge high for time horizons earlier than the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating what is commonly accepted as completed of a process from what is not completed or not commonly accepted as completed at any chosen point in time stated by a time horizon, the substantiality of knowledge high for time horizons earlier than the date of viewing, the substantiality of knowledge predicted for time horizons more futuristic than the date of viewing;

the demarcation separating what outcomes are commonly accepted as having occurred or likely to from what outcomes are merely anticipated by a small group at any chosen point in time stated by a time horizon relative to the probabilistic model viewed, the substantiality of knowledge high for time horizons earlier than the presumed state of completion of the probabilistic model, the substantiality of knowledge predicted for time horizons more futuristic than the presumed state of completion of the probabilistic model;

the demarcation separating what beliefs are likely to be held by a proportion of a population of voters from what beliefs are not yet settled on objectively by the population of voters at any chosen point in time stated by a time horizon relative to the probabilistic model viewed, the substantiality of knowledge high for time horizons earlier than the presumed state of completion of the probabilistic model, the substantiality of knowledge predicted for time horizons more futuristic than the presumed state of completion of the probabilistic model;

and

the demarcation separating objective beliefs from subjective beliefs at any chosen point in time stated by a time horizon relative to the probabilistic model viewed, the substantiality of knowledge high for time horizons earlier than the presumed state of completion of the probabilistic model, the substantiality of knowledge predicted for time horizons more futuristic than the presumed state of completion of the probabilistic model.

91. The method of claim 1, to produce a map from a commonplace of information demarcating what outcomes are anticipated from what outcomes are no longer anticipated at any point in time, further comprising:

a. extracting a structuring of cnxpts where a depth dimension presents a time aspect and at least one cnxpt is an event and at least one cnxpt is an outcome;

b. slicing the structuring by a timeline horizon plane where any outcome whose state is not resolvable at the time of the timeline fall to the future side of the timeline plane;

and

c. incorporating the timeline plane into a visualization.

92. The method of claim 1 to also provide for ensemble modeling related to concepts represented by cnxpts within a commonplace of information, further comprising:

a. adding to at least one first cnxpt a characteristic to hold zero or more values wherein the first cnxpt has at least one internal construct selected from the group of;

an attribute, a property, a method variable, and a method result;

b. adding to zero or more second cnxpts a method to state a computing operation;

c. providing zero or more modeling tools for fuzzy set based model analysis according to map generation means;

d. extracting a derived ontology according to a map definition wherein a said first cnxpt is in the derived ontology, and said second cnxpt is in the derived ontology;

e. executing modeling on said derived ontology by performing operations on copies of cnxpt instances of said commonplace where said copies of cnxpt instances are referenced in said derived ontology, according to map generation means, further including;

f. assigning at least one value to a cnxpt property characteristic according to a referenced value specification of a type selected from the group of;

i. a value primitive;

ii. a null;

iii. a default;

iv. a referenced property characteristic of a cnxpt;

v. a result of a specified cnxpt method;

and

vi. the result of interpreting an equation specification referencing zero or more exposed constructs selected from the group of;

sets of cnxpts, sibling cnxpts, parent cnxpts, cnxpts marked by a fxxt, children cnxpts, ascendant cnxpts, descendant cnxpts, cousin cnxpts, uncle cnxpts, leaf cnxpts, root cnxpts, related cnxpts in other generated structures, map object internal property constructs, model definition internal property constructs, user specified values, and user specified parameters;

and

g. utilizing at least one value of at least one cnxpt property characteristic, the utilizing of a type selected from the group of;

reporting to user, reporting to an external function, entering a vote into the commonplace stating a value based upon the resulting value of the property, and performing an action based upon the resulting value of the property;

whereby a derived ontology formed on the basis of a map definition holds a cnxpt that participates in said ensemble modeling as a computing object in an object-oriented paradigm.

93. The method of claim 1, to perform fuzzy logic modeling on the basis of categorization, further including:

a. create an empty derived ontology to accept member info-items;

b. preparing, by at least one processor, at least one consensus organization of knowledge of at least one domain of wisdom comprising at least in part a fxxt with a fuzzy marking criterion specified in an fuzziness parameter info-item with at least one fuzziness parameter property object identified by an identity of a property of the info-items that may be members of the fxxt to provide for a multi-factor fuzziness and classification fuzziness, the members added to the derived ontology, the object providing parameters for the fuzzy extraction depending upon the marking criterion, wherein the marking criterion for fuzziness is selected from the group of;

i. a bivalent condition marking to define crisp fuzzy sets wherein the fxxt has a defined fuzziness parameter info-item with one fuzziness parameter property object having a minimum threshold value field, a maximum threshold value field, and an a-cut value between the minimum and maximum, the values in the value fields for normalization of the values of the property with the same property identifier in each info-item considered for membership, wherein the value of the property in an info-item being considered for membership when normalized according to the fuzziness parameter property object is termed the grade of membership, wherein if the value of the property in an info-item being considered for membership is greater than or equal to the value in the maximum threshold value field the info-item is extracted to be in the resulting extraction, wherein if the value of the property in an info-item being considered for membership is less than or equal to the value in the minimum threshold value field the info-item is not extracted to be in the resulting extraction, wherein if any other value is assigned to the value of the property in an info-item being considered for membership the info-item would become a member if the value of the property is greater than or equal to the a-cut value;

ii. a function based bivalent condition marking to define crisp fuzzy sets wherein the fxxt has one or more defined fuzziness parameter info-items with one fuzziness parameter property object having a minimum threshold value field, a maximum threshold value field, a function to compute a membership grade normally from the properties of info-items being considered that match the property objects of the fuzziness parameter info-item, and an a-cut value between 0 and 1, wherein the values in the value fields for normalization of the values of the property with the same property identifier in each info-item considered for membership, wherein the value of zero or more properties in an info-item being considered for membership are normalized according to the fuzziness parameter property object and used in the function as a factor to produce a value termed the grade of membership, wherein if the grade of membership of an info-item being considered for membership is greater than or equal to the value a-cut value field the info-item is extracted to be in the resulting extraction, and otherwise is not extracted to be in the resulting extraction;

iii. a function based l-fuzzy set and neutrosophic fuzzy set marking to define partial membership sets wherein the fxxt has one or more defined fuzziness parameter info-items with one fuzziness parameter property object having a minimum threshold value field, a maximum threshold value field, a degree of membership function whose value is always between 0 and 1, a degree of non-membership function whose value is always between 0 and 1, and a degree of indecisiveness function whose value is always between 0 and 1, wherein the sum of degree of membership and degree of non-membership and degree of indecisiveness is less than or equal to 1 and greater than or equal to 0, wherein the values in the minimum and maximum value fields for normalization of the values of the property with the same property identifier in each info-item considered for membership, wherein for each one or more properties in an info-item being considered for membership where there is a fuzziness parameter property object of the same identity in the defined fuzziness parameter info-item the property is normalized according to the fuzziness parameter property object and used in the functions of the defined fuzziness parameter info-item to determine the degree of membership and degree of non-membership and degree of indecisiveness for each property, wherein the use of the degree of membership and degree of non-membership and degree of indecisiveness results is based upon the property of the info-item, wherein if any of the one or more properties in an info-item meet the criteria for membership then the info-item is made a member of the fuzzy set of the extracted fxxt, the property of a type selected from the group of;

01. univariate wherein if the degree of membership is greater than 0, the degree of membership is multiplied against the property value to reset the property in the info-item and make it a member;

02. bivariate wherein if the degree of membership is greater than 0 or if the degree of non-membership is greater than 0, the degree of membership is multiplied against the first factor variable value of the property and the degree of non-membership is multiplied against the second factor variable value of the property and the info-item with the new values is made a member;

03. univariate with indecisiveness wherein if the degree of membership is greater than 0, the degree of membership is multiplied against the property value to reset the property in the info-item and make it a member while the degree of assuredness is set to 1 minus the result of the degree of indecisiveness function;

and

04. bivariate with indecisiveness wherein if the degree of membership is greater than 0 or if the degree of non-membership is greater than 0, the degree of membership is multiplied against the first factor variable value of the property and the degree of non-membership is multiplied against the second factor variable value of the property and the info-item is made a member while the degree of assuredness is set to 1 minus the result of the degree of indecisiveness function;

iv. a marking wherein the fxxt has a defined threshold value and the marking is selected from real numbers between 0 and 1 where if the value of 1 is assigned to an info-item the info-item is extracted to be in the resulting extraction, wherein if the value of 0 is assigned to an info-item the info-item is never extracted to be in the resulting extraction, wherein if any other value is assigned to an info-item the info-item is extracted to be in the resulting extraction on the basis of the marking being greater than the threshold;

and

v. a marking wherein the fxxt has a defined threshold function yielding a value, the input to the function a property of an info-item under consideration for extraction, and the marking is selected from real numbers between 0 and 1 where if the value of 1 is assigned to an info-item the info-item is extracted to be in the resulting extraction, wherein if the value of 0 is assigned to an info-item the info-item is never extracted to be in the resulting extraction, wherein if any other value is assigned to an info-item the info-item is extracted to be in the resulting extraction on the basis of the marking being greater than the value obtained from the threshold function for that info-item;

whereby a fuzzy set is constructed as a fxxt extraction into a derived ontology.

94. The method of claim 1, further including:

a. accepting creation of instances of info-items;

and

b. accepting creation of relationships between info-items;

whereby txo instances, cnxpts, and other objects are created and commonality relationships, sub-typing relationships, keyword relationships, phrase commonality thesauri, and other relationships created to improve the commonplace data.

95. The method of claim 1, further including:

a. accepting a command regarding a definition of said fxxt from said user selected from the group of;

an info-item addition command defining a new fxxt along without parameters stated, an info-item addition command defining said new fxxt along with stated parameters, and an info-item change command refining a fxxt definition along with stated parameters;

b. accepting with said command regarding said fxxt definition a fxxt identity value of type selected from the group of;

a lack of value specifying to use a system generated identity, a parameter value acceptable as an identity, a form fill-in value acceptable as an identity, and a value acceptable as an identity that is acceptable to the user interface;

c. accepting with said command regarding said fxxt definition an assignment of zero or more rights policies regarding the organization of knowledge wherein a rights policy assigned to a fxxt specification is applicable to all knowledge marked by the fxxt, wherein the user is enabled to access an info-item within the organization of knowledge with the accumulation of access rights applicable to zero or more applicable rights resolution regimes selected from the group of;

i. a regime based upon identity of a first user;

ii. a regime based upon identity of a first organization, said first organization of a type selected from the group of;

entity, consortium, project team, investment pool, social grouping, and work grouping;

iii. a regime based upon a role of a first organization, the role defined in the usage agreement established by system provider with said first organization, said first organization of a type selected from the group of;

entity, consortium, project team, investment pool, social grouping, and work grouping;

iv. a regime based upon a user role in a first organization, the role defined in the usage agreement established by system provider with said first organization, said first organization of a type selected from the group of;

entity, consortium, project team, investment pool, social grouping, and work grouping;

v. a regime based upon a user role of said first user, the role defined in the usage agreement established by system provider with said first user;

vi. a regime based upon class of said first user;

vii. a regime based upon identity of said first user, and identity of subscription held by said first user;

viii. a regime based upon identity of said first user, identity of a first organization, and identity of a subscriptions held by said first user;

ix. a regime stating explicit custom access rights or policies based upon identity of said first user as defined in the usage agreement established by system provider with an organization granting rights to said first user under the agreement;

x. a regime stating explicit custom access rights or policies based upon role of said first user as defined in the usage agreement established by a first organization granting rights under said role to said first user under the agreement;

xi. a regime stating explicit custom access rights or policies based upon identity of said first user as defined in the usage agreement established by system provider with said first user;

and

xii. a regime stating explicit custom access rights or policies based upon identity of said first user as defined in the usage agreement established by system provider with said first organization granting rights to said first user under the agreement;

d. accepting with said command regarding a fxxt definition zero or more fxxt identity values of type;

and

e. accepting with said command regarding said fxxt definition one or more fxxt specifications each defining an extraction process for extracting a set of cnxpt instances and association instances from a commonplace, the fxxt specifications of a nature selected from the group of;

i. an extraction based upon marking of one or more association instances;

ii. an extraction based upon marking of one or more cnxpt instances;

iii. an extraction based upon marking of one or more cnxpt instances and association instances;

iv. an extraction based upon solving a set arithmetic fxxt equation;

v. an extraction based upon solving a not ‘

easily-determined’

fxxt specification;

and

vi. an extraction based upon a criterion.

96. The method of claim 1 further comprising:

a. defining the fxxt to provide external marking for organizing data;

b. marking an info-item of the commonplace as being a member of the fxxt;

and

c. granting access to the fxxt marked data in the commonplace to an automated process for map building;

whereby an external marking structure where nodes of an ontology is marked as having a position in a taxonomy and the position is conveyed to an application process;

whereby cell-like calculation equations on the taxonomy cnxpts nodes are available for use by external process.

97. The method of claim 1, wherein generating a map further comprises:

a. determining, by resolving by priority of information selected from the group of;

user directives, directives of said set of fxxts, nature of map, map directives, cnxpt class instances in extract, cnxpt instances in extract, association class instances in extract, association instances in extract, a multi-forest comprising a categorical spanning forest and a precedence spanning forest if both categorical and precedence nature hierarchical associations are found, a default of precedence if precedence nature hierarchical associations are found, and a default of simple categorization, the types of each one or more map instance skeletal structures for said domain of wisdom, the types of each one or more map instance organization of knowledge for said domain of wisdom;

and

b. determining, by resolving by priority of information selected from the group of;

user directives, nature of map, map directives, directives of said set of fxxts, the type of map instance skeleton, cnxpt class instances in extract, cnxpt instances in extract, association class instances in extract, association instances in extract, a multi-forest comprising a horizontal categorical forest and a vertical precedence forest if both categorical and precedence nature hierarchical associations are found, a default of a multi-forest comprising a vertical categorical forest and a horizontal precedence forest if both categorical and precedence nature hierarchical associations are found, a default of precedence if only precedence nature hierarchical associations are found, and a default of simple categorization, the types of each one or more map instance skeletal structures for said domain of wisdom, the types of each one or more map instance organization of knowledge for said domain of wisdom.

98. The method of claim 1 to control the process of ingesting knowledge of a body of data, further including:

a. creating a relationship info-item;

b. filling one role of said relationship info-item with the info-item identifier of an irxt info-item representing a collection of data with a source info-item identifier of a type selected from the group of;

a data set identity, a result set identity, a business identity, a universal resource locator, a document identity, a document section identity, a document part identity, a library location identity, a data source identity, a data stream segment identity, an identifier for a body of information, and a version identity;

c. filling a second role of said relationship info-item by an identifier selected from the group of;

txo identifier, cnxpt identifier, or result set identifier;

d. marking said irxt info-item by detailed infxtypx to indicate the type of source and zero or more parameters describing the data collection in terms of one or more members of the group of;

usability, quality, data currency, purlieu of data, description, identity, segmentation, segment sequence, version, provider reliability, provenance, classification, use restrictions, cost, restrictions on release, factor useful as a basis for a reliability weight, and factor useful as a basis for classification;

e. processing ingested data set batches of citation rich documentation to find new categories of ttxs to become represented by new cnxpts;

and

f. creating an irxt for the information resource or internal resource serving as an information resource.

whereby a txo has any number of sources, a relationship info-item has a source role, or in one embodiment, a relationship info-item item identifier fills a role in a source relationship.

99. The method of claim 1, to also provide acceptance of occurrences, further including:

a. locating information possibly relevant to a cnxpt instance and representing it by a txo in said commonplace;

b. accepting from a user one or more requests selected from the group of;

i. to add said information to said cnxpt instance in said commonplace by generating an occurrence instance between said txo instance and said cnxpt instance with a strength stated for the relevance of said information to said cnxpt instance;

and

ii. to add a vote regarding presence or strength of said occurrence relationship info-item between said cnxpt and said information resource or internal resource serving as an information resource by accepting zero or more opinions;

and

c. forming a consensus of the strength of said relevance of said information item to said cnxpt instance;

wherein said strength of relevancy is adjusted based upon said opinions entered to form said consensus.

100. The method of claim 1 to also provide acceptance of an information resource or internal resource serving as an information resource, further including:

a. locating an information resource or internal resource serving as an information resource possibly relevant to a cnxpt and representing it by forming an irxt;

and

b. relating said information resource or internal resource serving as an information resource to said cnxpt in said commonplace by generating an occurrence between said irxt and said cnxpt with a strength stated for said relevance of said information resource or internal resource serving as an information resource to said cnxpt.

101. The method of claim 1, to locate an information resource or internal resource serving as an information resource by analytic, further including:

a. describing a crawling by providing crawl description and parameters;

b. invoking a crawling software tool for scanning one or more heterogeneous repositories to collect information resource or internal resource serving as an information resource metadata and information resource or internal resource serving as an information resource content located therein according to web, file, and document crawler analytic, common mental map initiation process, import taxonomy, import collateral information resource or internal resource serving as an information resource, relevance based relationship info-item building, and enter information resource or internal resource serving as an information resource for a ttx means;

c. forming a crawl result structure and adding said crawling parameters to indicate a crawling instance;

d. adding a result set to said crawl result to hold rsxitems related to irxts each representing one found information resource or internal resource serving as an information resource;

e. obtaining said information resource or internal resource serving as an information resource'"'"'s metadata from said heterogeneous repository location provided by said locator;

f. forming, for an information resource or internal resource serving as an information resource not already related to an irxt, a new irxt containing properties having said locator and said metadata of said information resource or internal resource serving as an information resource as values according to import collateral information resource or internal resource serving as an information resource and enter information resource or internal resource serving as an information resource for a ttx means;

g. forming an rsxitem for each irxt representing an information resource or internal resource serving as an information resource in said crawl result according to result set processes means and according to create result set means;

and

h. applying mining analytics on said result set to shape categorized groupings from said rsxitems according to new category generation and category relation generation from result set means;

whereby a crawling engine obtains data from online repositories or mounted repository export data set.

102. The method of claim 101 to apply curation rules while preserving raw, original data, further including:

a. saving data sets for all imported data, the source of the data set and its relationships with other data must be stored;

b. performing clustering, cross citation, and other analysis techniques;

c. configuring said processors to operate according to utilize collective consensus through vote tallying means;

d. ingesting said data into said commonplace by converting said data'"'"'s format to the format of a commonplace info-item of a predetermined type, where each relationship info-item between said data set table row and an identified entity record is translated into a new translated relationship info-item of predetermined type between said ttx instance and the ttx instance stemming from said identified entity record and mark said new translated relationship info-item by the identity of said fxxt;

e. ingesting said data into said commonplace by converting said data'"'"'s format to the format of a commonplace info-item of a predetermined type, where each attribute of said new translated relationship info-item between said data set table row and said identified entity record is translated into a characteristic of predetermined type on said new translated relationship info-item;

f. integrating said new data entity record into said commonplace by providing a default vote, with an authority level commensurate with the known quality of the data added, regarding the veracity of the meaning of the term defined by said data set table row against said new ttx instance;

g. integrating, by zero or more iterations of processing according to generate commonality relationships means and zero or more iterations of processing according to imputed association generation means, said new data entity record into said commonplace by providing zero or more initial votes, with an authority level commensurate with the known quality of the data added times the predetermined metric for the combined analytic quality, regarding the similarity of meaning of said new term ttx instance to the meaning of an existing term ttx instance of even roughly similar type against a new similarity relationship info-item of predetermined type between said new term ttx instance and said existing term ttx instance;

and

h. integrating said new data entity record into said commonplace by providing a default vote regarding the likelihood of existence of said new translated relationship info-item stating that said likelihood is 100 percent with an authority level commensurate with the known quality of the data added if no characteristic of said new translated relationship info-item states such a likelihood value.

103. The method of claim 102 to apply curation rules while preserving raw, original data, further including:

a. processing ingested data set batches of citation rich documentation to find new categories of ttxs to become represented by new cnxpts;

and

b. creating an irxt for the information resource or internal resource serving as an information resource;

whereby information resources or internal resources serving as information resources are associated with the ttxs in the taxonomy data set or other source, and if an irxt is not in the common mental map for any information resource or internal resource serving as an information.

104. The method of claim 1 to allow refreshing of query results, further including:

a. interpreting a query by selecting a query step of a query for reinterpreting to form a new query and result instance by re-executing said original query;

b. interpreting said query step to form a new result instance into a result set;

c. reapplying result set culling to set the relevance of rsxitems to be the same as set in prior culling, to add zero or more new rsxitems and prepare them for culling according to result set processes means and according to create result set means;

and

d. reapplying result set evaluation and cnxpt positioning.

105. The method of claim 104 to refresh queries for an information resource or internal resource serving as an information resource, further including:

a. interpreting a query by selecting a query step of a query for reinterpreting to form a new query and result instance by re-executing said original query;

b. interpreting said query step to form a new result instance into a result set, possibly invoking a metasearch interceptor software analytic to catch relevant search results during a user query from a search tool selected from the group of;

according to finding, searching, query and retrieval means; and

according to goal based searching means;

further including for query step invoking a metasearch;

i. obtaining from said user'"'"'s returned result of said query a locator for an information resource or internal resource serving as an information resource;

ii. obtaining said information resource or internal resource serving as an information resource'"'"'s metadata from said heterogeneous repository location provided by said locator;

and

iii. forming an irxt containing properties having said locator and said metadata of said information resource or internal resource serving as an information resource as values according to import collateral information resource or internal resource serving as an information resource and enter information resource or internal resource serving as an information resource for a ttx means;

c. forming an rsxitem in said result set for said query according to result set means and according to create result set means;

d. reapplying result set culling to set the relevance of information resource or internal resource serving as an information resource rsxitems to be the same as set in prior culling, to add zero or more new rsxitems and prepare them for culling according to result set means and according to create result set means;

and

e. reapplying result set evaluation and cnxpt positioning;

whereby a search engine result obtained is semi-automatically refreshed and the effect of said new result alters the placement of said target cnxpt in a categorization of a fxxt.

106. The method of claim 1 to also provide for a machine to learn of a new concept from a user merely conjuring while using a commonplace and without a user burden of description, further comprising:

a. determining, by at least one processor, at least one user display visualization according to map generation means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

b. displaying to said user a portion of said organization of knowledge of at least one domain of wisdom according to display and delivery means;

c. accepting a request to add or refine said commonplace and effecting change therefrom;

d. accepting one or more user navigation commands to traverse from a first context represented by a first cntexxt represented internally by said first cnxpt on the organization of knowledge and derived visualization of said commonplace to a second, more detailed second context represented by a second cntexxt encompassing concepts each having a specific differentiation from said first context wherein said detailed second concept is more specific in meaning, wherein said navigation command is intended to narrow the set of contexts where said user might find the concept being conjured by said user;

e. accepting a user command indicating that said concept being conjured by said user should be within said first context represented by said first cntexxt said user has navigated to but is not, finalizing a search for information represented only by empty spaces within a context where the concept represented by a space is only within the mind of the user and their wisdom is imparted to the commonplace by their stating that the search has located the information in the empty space, the stating termed staking a claim to said space to encompass that wisdom;

and

f. creating a new third cnxpt within said first context represented by said first cntexxt to objectify the concretized conjuring of said concept being conjured by said user by identifying said space.

107. The method of claim 1 to also accept user voting, further including:

a. accepting repositioning of zero or more goals in a visualization by a user;

b. accepting repositioning of zero or more cnxpts in a visualization by a user;

c. accepting re-categorization of zero or more cnxpts in a visualization by a user;

d. accepting manual resolution of zero or more positioning defects in a visualization;

and

e. recalculating display object positions based upon user changes in a visualization.

108. The method of claim 1 to also provide for crystalizing meaning of cnxpts with less documentation through reuse of results of prior efforts, further comprising:

a. re-positioning cnxpts in a map as close to where the user last viewed them to improve the consistency of the perceptions of the user;

b. suppressing search result sets to only entries non-common with the context a concept is a member of in an organization of knowledge in a manner that the concept is seen as a differentiation from the context based upon the result set contents in a map;

and

c. retaining differentials between actuals, corrected beliefs, and beliefs for inclusion in weighted moving averages of viewpoint metrics.

109. The method of claim 1 to also provide continuous curation, further including:

a. accepting opinions by votes on presented data;

b. updating base data with votes without altering base data;

c. forming consensus by operations prior to and during extractions;

d. extracting, using consensus for fxxt within the extracted results;

and

e. summarizing fxxt weightings for fxxt instance into summary by fxxt where possible;

whereby a user may make changes and rearrangements of classifications to have some impact objectively and high impact subjectively.

110. The method of claim 1 to refine a structure for the meanings of ideas, further including:

a. highlighting to indicate high similarity, cnxpts positioned close to each other in the same cntexxt;

and

b. suggesting, if a predetermined system setting is set to a predetermined value, the removal of one cnxpt of a pair of cnxpts having high similarity.

111. The method of claim 110 to combine instances of an info-item having no significant differential in meaning in any use case, further including:

a. integrating by semantic meaning of a second ttx instance to a first ttx instance already situated in a categorization by semantic meanings;

b. integrating by value of a characteristic indicating semantic meaning of a second ttx instance to a first ttx instance already situated in a categorization by semantic meanings;

c. integrating by trait indicating semantic meaning of a second ttx instance to a first ttx instance already situated in a categorization by semantic meanings;

d. integrating by Venn overlap of set of information resources found relevant to a second ttx instance relative to the set of information resources found relevant to a second ttx instance to the covering to a first ttx instance already situated in a categorization by semantic meanings;

and

e. curating and combining redundancies and duplicate cnxpts.

112. The method of claim 111 to refine a structure for the participant'"'"'s meanings of related ideas respecting objectivity and subjectivity, further including:

a. accepting a command to reparent a cnxpt;

b. processing said command to reparent a cnxpt as a vote for consideration under consensus;

and

c. processing said command to reparent a cnxpt as authoritatively reparented in a subjective view for the user who has voted to reparent the cnxpt;

whereby a user may make rearrangements of classifications to have some impact objectively and high impact subjectively.

113. The method of claim 111 to eliminate redundant information and keep information properly connected, further including:

a. suggesting that a pair of cnxpts comprised of;

a first cnxpt and a second cnxpt be transformed into a set of three cnxpts, where a parent cnxpt is formed from the characteristics in the intersection of characteristics equal for both said first cnxpt and said second cnxpt and making both said first cnxpt and said second cnxpt into children of said parent cnxpt.

114. The method of claim 1, to accept results of analytics, further comprising;

a. accepting a relationship between a pair of information resources from an analytic program;

b. imputing a relationship info-item between a first irxt representing the first information resource and a second irxt representing the second information resource from said relationship between a pair of information resources;

and

c. imputing an affinitive association relationship info-item between a first cnxpt having as an occurrence the first irxt and a second cnxpt having as an occurrence the second irxt from the imputed relationship info-item between the first irxt and the second irxt;

whereby commonalities of other varieties are accepted by raising imputed relationships found to relationships between cnxpt pairs.

115. The method of claim 1, to curate added information, wherein in no set order:

a. accepting one or more user commands selected from the group of;

i. to add an info-item to said commonplace;

ii. to add a concept represented internally by a cnxpt to said commonplace;

iii. to add an indication of a differentiation of a first concept represented internally by a cnxpt from a second concept wherein said first concept will no longer be equivalent to second concept in said commonplace;

iv. to register a vote stating that said user believes that said commonplace needs to be altered;

v. to add a data set of data to be interpreted as instances of info-items having specified values in said commonplace wherein said info-items are marked with a fxxt describing at least the provenance of the data set;

and

vi. to add a concept represented internally by a cnxpt to said commonplace;

b. accepting one or more commands from a user specifying an alteration believed to be needed to refine said commonplace;

c. adding into said commonplace categorizations for concepts from available sources translating each node of said categorization into a cnxpt with category node name as name and marking each said cnxpt with a specified fxxt wherein said categorizations are translated to become relationships indicating cnxpt hierarchy and are marked with said specified fxxt;

d. ingesting published databases of all published patents and patent applications translating each said patent or application into a cnxpt with said patent or application title as cnxpt name and a proper occurrence instance to represent said patent or application document, marking each said cnxpt and occurrence with a specified fxxt wherein citations amongst said patents and applications are translated to become relationships indicating cnxpt prior art hierarchy structure, classifications specified for said patents and applications are translated to become relationships indicating cnxpt relevance to and membership in a grouping of concepts, utilizing meta-data of said patents and applications to set characteristics for said cnxpt and occurrence instance, and marking relationships with said specified fxxt;

e. creating a cnxpt for any information resource cited for which no cnxpt was yet created, a proper occurrence, and marking said cnxpts, occurrence instances, and relationships with a specified fxxt;

f. scraping the internet for technical publications having citations, creating a cnxpt for each information resource found for which no cnxpt was yet created, a proper occurrence, and marking said cnxpts, occurrence instances, and relationships with a specified fxxt;

g. creating, for each citation found, a directional relationship info-item between a first occurrence and a second occurrence where said first occurrence is set as a tail endpoint of said relationship info-item wherein said first occurrence is representing a cited information resource and said second occurrence is set as a head endpoint wherein said second occurrence is representing a citing information resource and marking said cnxpts, occurrence instances, and relationships with a specified fxxt;

h. searching meta-search engines using names of cnxpt items as search terms to collect information resource citations and to generate occurrences wherein relevance rankings from said meta-search engines are used as default relevance votes for said occurrences, and marking said cnxpts, occurrence instances, and relationships with a specified fxxt;

i. forming a structure for storing commonalities;

j. determining semantic distances for names of cnxpts and registering said semantic distance as a commonality weight;

k. determining semantic distances for information resource titles and registering said semantic distance as a commonality weight;

l. determining semantic distances for information resource abstracts and registering said semantic distance as a commonality weight;

m. determining commonalities for known information entered as characteristics selected from the group of;

people involved, time, institution, funding agency, application, and industry of information resources;

n. determining commonalities for known information entered as characteristics selected from the group of;

people involved, time, institution, funding agency, application, and industry of occurrences;

o. determining commonalities for known information entered as characteristics selected from the group of;

people involved, time, institution, funding agency, application, and industry of cnxpts;

and

p. imputing commonality relationships according to generate commonality relationships means for commonalities determined, marking each relationship info-item by a specified fxxt.

116. The method of claim 1, further comprising stating an opinion regarding at least one item type selected from the group of:

the weighting coefficient indicating a proportionality of impact assigned to a fxxt specified in a map definition, the positioning of a cnxpt within the organization of knowledge of a map, the weight of an association, the importance of a cnxpt, the existence of a cnxpt in a time frame, the veracity of a cnxpt, the veracity of a property of a cnxpt, the veracity of information associated with a cnxpt, the existence of an association between two cnxpts within the organization of knowledge of a map, the veracity of a property of an association, the inappropriateness of an association between two cnxpts, the value of a property of a cnxpt, the relevance of information regarding a cnxpt, the similarity of a plurality of cnxpts, a marking of a cnxpt as being a part of a fxxt, the value of a property of an association, and a marking of an association as being a part of a fxxt.

117. The method of claim 1, wherein an indicated fxxt of the set of fxxts from which a map is generated is altered by a cnxpt positioning interaction selected from the group of:

changing the parent of a cnxpt;

creating a new association between two cnxpts within the map, adding a cnxpt within the map, and modifying a weight of an association within the map.

118. The method of claim 1, wherein the interactions comprise at least one of:

a. traversing the organization of knowledge of a map;

b. conversing with a different party on a channel associated with a cnxpt;

c. starting a consortium associated with one or more cnxpts;

d. investing in a pool associated with one or more cnxpts;

e. advertising for assistance with efforts associated with one or more cnxpts;

f. selling data regarding a cnxpt;

g. seeking investment based upon one or more cnxpts;

h. providing services keyed to a cnxpt;

i. organizing a project on the basis of classifications based upon cnxpts;

j. organizing a project on the basis of classifications based upon a map;

k. viewing industry news specifically according to a cntexxt;

l. setting strategy based upon a projection of future competitive value of something represented by a cnxpt;

m. planning a product line based upon a cnxpt representing a cntexxt;

n. managing a portfolio based upon a map showing one or more cnxpts;

o. filtering a map based upon properties of one or more cnxpts;

p. aligning production with intellectual property represented by a cnxpt;

q. aligning production with product management of products represented by a cntexxt represented by a cnxpt;

r. aligning product strategy with innovation toward future ideas represented by a cnxpt;

s. seeking opportunities for investment at an intellectual property stage where inventors are only willing to state that they have intellectual property in a technology area represented by a cntexxt;

t. managing a project requiring rapid information gathering and resource management and consensus building;

u. harmonizing classifications;

v. managing machine learning projects;

w. managing bio-informational studies;

x. managing data science projects requiring data entity cleanup;

y. managing intelligence projects where information obtained may not be correct;

z. managing legal cases where information stream is complex;

aa. re-positioning the cnxpts within a visualization of a map;

bb. creating a new association between two cnxpts within the map;

cc. adding a cnxpt within the map;

dd. defining a new fxxt;

and

ee. modifying a weight of an association within the map.

119. The method of claim 1, further including:

a. accepting culling commands as votes with strength set by expertise of person culling;

and

b. forming culling relevance based upon weighted average of culling votes for a result set.

120. The method of claim 1 to also provide for accepting user information, further including:

a. accepting from a user one or more requests selected from the group of;

i. to add an idea into said commonplace by incrementally conjuring and concretizing a subjectively differentiated idea as a cnxpt instance;

ii. to add an idea into said commonplace by concretizing a query goal converting a goal into a cnxpt instance;

iii. to add a vote regarding presence and strength of a hierarchical relationship represented by an association instance between a first cnxpt instance and a new second cnxpt instance by defining a differentiation from said first cnxpt instance in the perspective of a map as stated by the presence of said second cnxpt instance by adding said new second cnxpt instance into the original said first cnxpt instance wherein said first cnxpt instance represents a cntexxt representing a context where the idea represented by said new second cnxpt instance belongs;

iv. to add a vote regarding classification of a first cnxpt instance stating an opinion regarding presence and strength of an association instance relationship between said first cnxpt instance and a second cnxpt instance to serve as a context in a map into which said first cnxpt instance is to be classified, said second cnxpt instance referred to as a category context represented by a cntexxt represented by said second cnxpt instance;

v. to add a vote regarding similarity of ideas in the perspective of a map represented by cnxpt instances stating an opinion regarding presence and strength of an association instance representing a similarity relationship between said cnxpt instances;

vi. to add a vote regarding presence or strength of a relationship info-item between commonplace info-items;

vii. to add an objection vote regarding presence or strength of an association instance;

and

viii. to add an objection vote regarding presence or strength of a relationship.

121. The method of claim 1 to allow refreshing of query results, further including:

a. accepting zero or more commands to select a subsequent cntexxt of wisdom within said organization of knowledge to process said zero or more commands by zero or more functional components selected from the group of;

according to ideation means;

according to finding, searching, query and retrieval means;

according to goal based searching means;

according to selection set management means;

according to focus on information means; and

according to alter information through visualization means;

wherein said default cntexxt is retained as the subsequent cntexxt if no command of this type is entered before entering a command to specify said zero or more commands to act upon said subsequent cntexxt of wisdom, said zero or more commands to select a subsequent cntexxt of wisdom.

122. The method of claim 1 to also provide for determining decision tree classifier structures, further comprising:

a. performing a fxxt extraction;

b. performing a structuring to form a classifier forest;

c. defining as a goal form of cnxpt a classification required by stating goal traits for matching to a classification;

and

d. conducting a walking, the walking controlled by an entity selected from the group of;

i. a user navigating a walk from root to leaf of the structuring, subjectively choosing a branch in the classifier based upon what the user considers at the time to be the best match of child normally preferring the one having the closest matching to the goal;

and

ii. an algorithm walking from root to leaf of the structuring, choosing, at each branch in the classifier tree, represented by a cnxpt reached where the cnxpt has children any of which might be chosen as a next visit, a branch in the classifier based upon choosing the best match of child by the one formed by an association with greatest strength weight of all associations connecting to the children from the parent cnxpt as determined by consensus voting and raw association strength weights, by fxxt weighting coefficients indicating a proportionality of impact of one or more fxxts stated by the map definition, and by a determination of semantic associative similarity of a child to the goal;

whereby a classifier is provided for fuzzy matching based upon best match of a plurality of traits.

123. The method of claim 1 to locate a concept more similar to that thought of by a user by sorting of results by appropriateness to the concept sought, further including:

a. providing, for user culling, an area of consideration based upon a search;

b. moving the user'"'"'s focal point in the visualization to a point near the centroid of the area of consideration;

c. accepting a user culling of the area of consideration;

and

d. moving the user'"'"'s focal point in the visualization to the new centroid of the area of consideration;

whereby a user search goal is pushed to a different location in a visualization.

124. The method of claim 1 to locate a concept more similar to that thought of by a user by appropriateness to the concept sought, further including:

a. providing a result set of at least one query basis selected from the group of;

features, time frame, purlieu, locale, attribute values, and property values;

for user culling based upon a search;

b. generating an area of consideration based upon the cnxpts having features, time frame, purlieu, locale, attribute values, or property values in said result set;

c. determining which set of at least one cnxpt in the area of consideration have sets of features, time frame, purlieu, attribute values, or property values most similar to the items in said result set, forming an area of interest from the set;

d. moving the user'"'"'s focal point in the visualization to a point near the centroid of the area of interest defined by the set of cnxpts;

e. accepting a user culling of said result set;

f. generating an area of consideration based upon the cnxpts having features, time frame, purlieu, locale, attribute values, or property values in said result set as culled;

g. determining which set of at least one cnxpt in the area of consideration have sets of features, purlieu, locale, attribute values, and property values most similar to the items in said result set, forming an area of interest from the set;

h. moving the user'"'"'s focal point in the visualization to a point near the centroid of the area of interest defined by the set of cnxpts;

and

i. adjusting the organization of knowledge based upon changes made to the derived visualization;

whereby a user search goal is pushed to a different location in a visualization.

125. The method of claim 1, further including:

a. choosing a next cntexxt on a basis selected from the group of;

i. entry of a find query specification, wherein;

01. accepting a find command comprising a search query for a value of a type selected from the group of;

a value of a property of a cnxpt, a pattern of a property of a cnxpt, a value not held by a property of a cnxpt, a pattern not held by a property of a cnxpt, a value of a property of an association, a pattern of a property of an association, a value not held by a property of an association, a pattern not held by a property of an association, a string in an information resource related to a cnxpt, a pattern in an information resource related to a cnxpt;

02. executing said find command, resulting in zero or more matching items;

and

03. moving the focus of the user to the cnxpt selected from the group of;

the first cnxpt wherein a match of the stated search query was to an object selected from the group of;

the property of a cnxpt, the property of the association for which a cnxpt holds a from role, the property of the association for which a cnxpt holds a to role, and the string in the information resource related to a cnxpt; and

the next cnxpt wherein a match of the stated search query was to an object selected from the group of;

the property of a cnxpt, the property of the association for which a cnxpt holds a from role, the property of the association for which a cnxpt holds a to role, and the string in the information resource related to a cnxpt;

ii. entry of a search query specification, wherein;

01. accepting a choice from a list of cntexxts an alternative said cntexxt, said list determined by accepting and processing a search query specification according to finding, searching, query and retrieval means resulting in a list of cnxpts to narrow the possibilities to said list of cntexxts, such choice replacing any prior cntexxt as the new first cntexxt presented as the first cntexxt defined by said cnxpt, wherein such list of a type selected from the group of;

a result set, members of an area of consideration, members of an area, instances of a cnxpt class, members of a set of cnxpts, members of a subtree of a cnxpt in said map, cnxpts in a bounded area of said map, cnxpts having a trait meeting a criterion, cnxpts to which an info-item has been related wherein the info-item satisfies a criterion, cnxpts to which an information resource has been related wherein the information resource satisfies a criterion, members of a set of cnxpts having a property meeting a criterion, and members of a fuzzy set of cnxpts in said map;

and

iii. entry of a goal representing an idea, wherein;

01. accepting a query, comprising one or more query step specifications, to attach to said goal to locate relevant search results according to finding, searching, query and retrieval means;

02. adding said query to said goal according to attach a query to goal means;

03. forming a result set for said query for said goal for holding search results to retain the basis for said goal for reuse, according to create result set means, according to process a query for goal, according to process query step specification, generating result set means, according to execute query and attach result set to goal means, and according to result set processes means;

04. forming an rsxitem to obtain an index to said information, according to result set processes means and according to create result set means and according to process a result set for goal or cnxpt means;

05. presenting said result set items of said result set to user for culling, according to extract and generate ordering for taxonomy from selection set for culling means;

06. accepting zero or more culling commands on said result set rsxitems to obtain a relevant set of result set items according to result set processes means;

07. accepting zero or more assessments of the propriety of said rsxitem to said result set as a measure of the relevance of an rsxitem to said goal, cnxpt, query, or search having said result set;

08. summarizing said result set into query independent result set for goal, setting summarized relevance rankings according to result set conversion to properties, occurrences, and categorizations means;

and

09. determining zero or more cntexxts in said map definition that said search goal should be associated with by comparing said search results with relevant information of existing cnxpts in said map to reposition said goal into the best cntexxt based on said result set according to result set evaluation for positioning means;

wherein if no cntexxt is considered by said user to be better than the present cntexxt to act as parent to the goal;

granting said user the authority to convert the goal to a cnxpt within the present cntexxt, attaching the result set and other known goal information to the cnxpt, accepting zero or more identifiers for the cnxpt, and granting control over the cnxpt to said user;

whereby movement of a user'"'"'s focus to a cntexxt represented by a cnxpt is done by jumping to a context rather than navigating via the organization of knowledge.

126. The method of claim 125 to also provide associative searching based upon a stated goal, further including:

a. accepting a choice of map organization of knowledge and the visualized map on which to search;

b. moving the goal to an initial position on the organization of knowledge and the visualized map as determined from prior user query results, if any, or a default positioning for a new query for the goal;

c. setting up an additional query step of said query to retain the repositioning result of the associative search for the map chosen;

d. accepting navigation commands for manually moving said search goal to a cntexxt in said map more strongly related to the ttx in said user'"'"'s mind according to goal based searching means and goal positioning means;

and

e. collecting the positioning chosen by said user for the search goal during the navigation to form associations between the cntexxts visited and the search goal according to goal based searching means, wherein the effect of the newly formed associations between the cntexxts are weakened as newer positions are chosen.

127. The method of claim 126 to accept a conjuring of an idea, further including:

a. accepting a command affirming that said idea as represented by said search goal is in a proper cntexxt category cnxpt in the context of said map where said query is performed and is differentiated from said cntexxt category itself and any sibling idea ttx as represented by the sibling cnxpts in said cntexxt category in said map, the differentiation caused by said user;

b. converting said search goal into a cnxpt;

c. associating said cnxpt with said category cnxpt of said cntexxt found by generating an association between said goal'"'"'s new cnxpt and said category cnxpt in said map;

d. generating, if said search goal has a result set, occurrence relationships between said cnxpt and each relevant result set item information txo or irxt found;

and

e. informing a user regarding said new cnxpt.

128. The method of claim 127 to also initiate activity regarding an added idea, further including:

a. informing said user of information available to a user entering a new concept represented by a cnxpt, the information selected from the group of;

i. assistance in basic classification of the cnxpt;

ii. assistance in working with cnxpt classes if the user has chosen that type;

iii. information inheritable into the cnxpt from its parent in the perspective of the map being used;

iv. information inheritable into the cnxpt from the user information and affiliation information of the user;

v. information regarding concept ownership and security and choices available given policies in the perspective of the context the cnxpt is placed into;

vi. information inheritable from queries attached to the parent of the cnxpt in the perspective of the map used;

vii. a choice of types optionally with an explanation of what the type can provide to users substantially listing use cases and workflows and social interactions available;

viii. what information will be needed for full description of the cnxpt upon setting the type of cnxpt;

ix. what information will be needed for full description of the concept represented by the cnxpt upon setting the type of cnxpt;

x. what information will be needed if the idea is to be considered for patenting;

and

xi. how to state a description to show the innovative thought of the idea represented by the cnxpt;

b. providing selected information regarding said cnxpt based upon the nature of the concept it represents as stated by the user, the information selected from the group of;

i. ownership styles regarding the cnxpt and the concept it represents that are available to the user and applicable to the cnxpt;

ii. workflows applicable to the cnxpt;

iii. authorities applicable to the cnxpt;

iv. use cases available to the user and applicable to the cnxpt;

and

v. social networking facilities available to the user and applicable to the cnxpt;

c. setting access to said new cnxpt according to access management for ttxs means and according to managing ideas means;

d. providing a methodology or workflow for establishing cnxpt protection according to apply for patent means of patent application workflows;

e. providing some portion of ownership of and rights to some degree of control of attached communities based upon said cnxpt in a category based online community system according to socialize means;

f. authorizing access as inventor to a high trust expert networking mechanism based upon said cnxpt to enable narrow chat, confidential negotiations for licensing technology, confidential consortia communications, confidential business plan and concept information repository community tools according to share and commune in innovation and consortium investment means;

and

g. authorizing access as inventor to confidential consortia communications, confidential business plan and concept information repository, investment pool community tools according to innovation investment pools means and according to consortium investment means.

129. The method of claim 1 to refine a concept sought by attached query, further including:

a. sorting of results of a query by appropriateness to said cnxpt representing a concept sought;

and

b. retaining said results with said cnxpt representing a concept sought as a result set, the result set serving as a subject identifier.

130. The method of claim 1 to locate a concept more similar to that thought of by a user by culling of results by appropriateness to the concept sought, further including:

a. providing a result set, based upon a search query for criteria selected from the group of;

trait values, keywords, subject identifier contents, and occurrences;

for user culling, the result set serving as a sought after subject identifier;

and

b. accepting, until notice of completion, from the user information selected from the group of;

i. accepting a user culling of said result set, wherein;

01. determining which set of at least one cnxpt having characteristics matching to said result set;

02. moving the user'"'"'s focal point in the visualization to a point nearer to the cnxpt of said set of at least one cnxpt having the closest set of matching characteristics;

and

03. preparing for additional culling of said result set;

ii. accepting notice that the user is satisfied with the contents of said result set, wherein;

01. placing an indicator of the status of the search onto the visualization;

02. adjusting the organization of knowledge based upon changes made to the derived visualization;

and

iii. accepting notice that the user is abandoning the search effort, wherein;

01. placing an indicator of the abandoned search onto the visualization, the indicator retaining said result set;

02. adjusting the organization of knowledge based upon changes made to the derived visualization;

whereby a user search goal is pushed to a different location in a visualization.

131. The method of claim 1 to allow searching for an idea, further including:

a. accepting and carrying out at zero or more user actions selected from the group of;

i. accepting a choice from a list of cntexxts an alternative said cntexxt, said alternative said cntexxt not the present point of focus, said list determined by accepting and processing a search query according to finding, searching, query and retrieval means resulting in a list of cnxpts representing cntexxts to determine priority of the possibilities as a next focal point, said alternative said cntexxt having a highest priority in said list of cntexxts after culling, said alternative said cntexxt becoming the focus point presented to the user;

ii. accepting and processing a search query according to finding, searching, query and retrieval means resulting in a result set list of cnxpts, the position of the cnxpt leading said result set becoming the focus point presented to the user;

iii. accepting and processing a search query according to finding, searching, query and retrieval means resulting in a list of cnxpts representing cntexxts comprising an area of consideration, the center point of the combined positions of the cntexxts of said area of consideration becoming the focus point presented to the user;

iv. accepting user culling, by one or more iterations, a list of cntexxts comprising an area of consideration to derive a list comprising an area of interest, the center point of the combined positions of the cntexxts of said area of interest becoming the focus point presented to the user;

v. accepting user culling, by one or more iterations, a list of cntexxts comprising a first area of interest to derive a list comprising a second area of interest, the center point of the combined positions of the cntexxts of said second area of interest becoming the focus point presented to the user;

vi. accepting a choice, by one or more iterations, a selected result set list of one or more cnxpts, the position of the cnxpt leading said result set becoming the focus point presented to the user;

vii. determining from a list of cntexxts a center point as an alternative point of focus presented to the user, said list determined by accepting and processing a search query according to finding, searching, query and retrieval means resulting in a culled list of cnxpts representing cntexxts;

viii. determining from a list of cntexxts a highest priority cnxpt to serve as a center point as an alternative point of focus presented to the user, said list determined by culling a result set of cnxpts representing cntexxts;

ix. accepting a choice from a list of cntexxts an alternative said cntexxt represented by a cnxpt having priority in said list, said list determined by accepting and processing a search query specification according to finding, searching, query and retrieval means resulting in a result set of cnxpts to alter priority and ordering of the possibilities for focusing by culling to said list of cntexxts, the position of said cnxpt having priority replacing any prior point of focus presented to the user;

x. accepting a command to start a search for an idea in a user'"'"'s mind and creating a uniquely identifiable search goal info-item;

xi. accepting user navigations to perform a non-associative search for said idea and positioning the goal according to the result;

xii. accepting user navigations to perform associative searching to said user using one or more maps to allow seeking a cntexxt in said one or more maps where said idea topically fits according to goal based searching means;

and

xiii. accepting a command to finalize the search, the command selected from the group of;

01. finalize the search by stating that a new ttx was to be concretized and categorized;

and

02. finalize the search by stating that a new ttx did not need to be concretized or categorized.

132. The method of claim 1 to also provide a curatable personal commonplace, further comprising:

a. receiving, from the user, a choice of a context represented by a cntexxt within a map of a domain of wisdom to use as a focus point;

b. managing an addition or refinement, of said domain of wisdom, received from the user by performing at least one of;

i. accepting votes regarding information of said domain of wisdom based upon entered commands and navigation;

ii. tracking strength of associations of said domain of wisdom by tallying of votes according to utilize collective consensus through vote tallying means for said plurality of votes by said user, considering votes of others included in generation of said map;

iii. forming an altered organization of knowledge by performing at least one of;

01. altering weighting coefficients indicating a proportionality of impact of one or more fxxts of said map definition to create a second map definition;

and

02. altering said domain of wisdom specified by said map definition to create a second map definition;

and

iv. perform cleanup according to data cleanup means;

and

c. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said map of a domain of wisdom;

ii. to add or refine content of said personal commonplace and effect change by entering content change votes;

iii. to navigate around a visualization of said commonplace;

iv. to request a search for wisdom;

v. to traverse from a first context represented by a first cntexxt represented internally by a first cnxpt instance on the visualization of said commonplace to a second, more detailed second context represented by a second cntexxt encompassing concepts represented by cnxpt instances each having a specific differentiation from said first context wherein said detailed second concept has been defined by said user to be more specific in meaning, wherein said navigation command is intended to narrow the set of contexts where said user might find the concept being conjured by said user;

vi. to indicate that said concept represented by a cnxpt being conjured by said user is within said first context represented by said first cntexxt said user has navigated to but is not, to finalize a search for information represented only by empty spaces within a context where the concept represented by a space is only within the mind of the user and their wisdom is imparted to the commonplace by their causing the creating of a new third cnxpt within said first context represented by said first cntexxt to objectify the concretized conjuring of said concept being conjured by said user;

vii. to indicate how said concretized conjuring represented by said third cnxpt is differentiable from said first concept represented by said first cntexxt represented internally by said first cnxpt;

viii. to state that a first concept is a differentiable offshoot of second concept, wherein said second concept represented by a second cnxpt is to be a parent in a parent child association info-item with said first concept represented by a first cnxpt;

ix. to state that a first concept is of a temporally differentiable timeframe occurring after a second concept, wherein said second concept represented by a second cnxpt is to be the parent in a parent child association info-item with said first concept represented by a first cnxpt;

x. to state that a first concept is within a context defined by a second concept, wherein said second concept represented by a second cnxpt is to be the parent in a parent child association info-item with said first concept represented by a first cnxpt where said parent child association info-item indicates context membership;

and

xi. to state that a first concept is dependent in a precedence upon the existence, initiation, or completion of a second concept, wherein said second concept represented by a second cnxpt is to be the predecessor in a predecessor successor association info-item with said first concept represented by a first cnxpt.

133. The method of claim 132, wherein the interactions comprise at least one action selected from the group of:

traversing the organization of knowledge of a map, re-positioning the cnxpts within the organization of knowledge of a map by altering the visualization of the map, creating a new association between two cnxpts within the organization of knowledge of a map by altering the visualization of the map, adding a cnxpt within the organization of knowledge of a map, defining a new fxxt, marking an association by a fxxt, marking a cnxpt by a fxxt, adding information regarding a cnxpt, searching regarding a cnxpt, causing a change of a position of a cnxpt by altering the information associated with the cnxpt in a map, modifying the importance of a cnxpt, stating a similarity between a plurality of cnxpts, and modifying a weight of an association within the organization of knowledge of a map.

134. The method of claim 1 to accept at least one indication of how a concept being conjured by a user is differentiated from the context within which it has been placed, further comprising:

a. accepting at least one indication of how said concept being conjured by said user, the concept conjured represented by a first cnxpt, is differentiated from said context, said existing context a concept represented by a second cntexxt itself a second cnxpt, said cntexxt wherein said first cnxpt is being added, the indication a first characteristic, the indication selected from the group of;

i. a textual entry stating a differentiation as the first characteristic;

ii. the stating of one or more words describing a differentiation type not listed;

iii. the stating of one or more words describing a differentiation type not listed and setting a differentiated value due to presence of said characteristic;

iv. the stating of one or more words describing a differentiation type not listed and stating a benefit due to presence of said characteristic;

v. the stating of one or more words describing a differentiation type not listed and stating a benefit due to presence of said characteristic and a differentiated value due to presence of said characteristic;

vi. a selection from a list of differentiation types;

vii. a selection from a list of differentiation types and setting a differentiated value due to presence of said characteristic;

viii. a selection from a list of differentiation and stating a benefit due to presence of said characteristic;

ix. a selection from a list of differentiation types and stating a benefit due to presence of said characteristic and a differentiated value due to presence of said characteristic;

x. a selection of list items stating predefined second characteristics to attribute to possible offshoots of said second concept represented by said cntexxt;

xi. a selection of list items stating predefined second characteristics to attribute to possible offshoots of said second concept represented by said cntexxt and setting a differentiated value due to presence of said characteristic;

xii. a selection of list items stating predefined second characteristics to attribute to possible offshoots of said second concept represented by said cntexxt and stating a benefit due to presence of said characteristic;

xiii. a selection of list items stating predefined second characteristics to attribute to possible offshoots of said second concept represented by said cntexxt and stating a benefit due to presence of said characteristic and setting a differentiated value due to presence of said characteristic;

xiv. a selection of a third cnxpt and also selecting an entry from a list of characteristics stating how said third cnxpt is differentiated from the context it is in for use as the description of the differentiation of said concept being conjured by said user from said second concept represented by said second cntexxt;

xv. a selection of a third cnxpt and also selecting an entry from a list of characteristics stating how said third cnxpt is differentiated from the context it is in to use as the description of the differentiation of said concept being conjured by said user from said second concept represented by said second cntexxt and stating a benefit due to presence of said characteristic;

xvi. a selection of a third cnxpt and also selecting an entry from a list of characteristics stating how said third cnxpt is differentiated from the context it is in to use as the description of the differentiation of said concept being conjured by said user from said second concept represented by said second cntexxt and stating a differentiated value due to presence of said characteristic;

xvii. a selection of a third cnxpt and also selecting an entry from a list of characteristics stating how said third cnxpt is differentiated from the context it is in to use as the description of the differentiation of said concept being conjured by said user from said second concept represented by said second cntexxt and stating a benefit due to presence of said characteristic and a differentiated value due to presence of said characteristic;

xviii. the definition of the first characteristic had by said concept being conjured by said user but not by said second concept represented by said second cntexxt;

xix. the definition of the first characteristic had by said concept being conjured by said user but not by said second concept represented by said second cntexxt and stating a benefit due to presence of said characteristic;

xx. the definition of the first characteristic had by said concept being conjured by said user but not by said second concept represented by said second cntexxt and stating a differentiated value due to presence of said characteristic;

xxi. the definition of the first characteristic had by said concept being conjured by said user but not by said second concept represented by said second cntexxt and stating a benefit due to presence of said characteristic and a differentiated value due to presence of said characteristic;

xxii. a citing of an occurrence relevant to said concept being conjured by said user but not relevant to any other context within said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said occurrence is considered relevant to said first cnxpt and not relevant to any third cnxpt within the second cntexxt absent another characteristic;

xxiii. a citing of an occurrence not relevant to said concept being conjured by said user but relevant to all other contexts within said second concept represented by said cntexxt or presently considered as relevant to said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said occurrence is not considered relevant to said first cnxpt and relevant to all third cnxpts within the second cntexxt absent another characteristic;

xxiv. a vote to establish an association info-item participated in by said concept being conjured wherein the association info-item is not relevant to any other context within said second concept represented by said cntexxt or by said second concept represented by said cntexxt, this indication by association valid only while said association connects to said first cnxpt and not relevant to any third cnxpt within the second cntexxt;

xxv. a vote to exclude said concept being conjured from an association info-item participated in by all other siblings of said concept being conjured;

xxvi. a citing of a trait held by said first cnxpt representing said concept being conjured by said user but not held by any other context within said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said trait is held by said first cnxpt and not relevant to any third cnxpt within the second cntexxt absent another characteristic;

xxvii. a citing of a trait not held by said first cnxpt representing said concept being conjured by said user but held by all other fourth cnxpts representing concepts within said second concept represented by said cntexxt or presently considered as held by said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said trait is not held by said first cnxpt and is held by all third cnxpts within the second cntexxt absent another characteristic;

xxviii. a citing of a time frame relevant to said concept being conjured by said user or where said concept being conjured by said user was valid for but is not precisely the same time frame of any other context within said second concept represented by said cntexxt or no other said second concept represented by said cntexxt was valid for, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said time frame is considered relevant to said first cnxpt and not relevant to any third cnxpt within the second cntexxt absent another characteristic;

xxix. a citing of a purlieu relevant to said concept being conjured by said user or where said concept being conjured by said user was valid for but is not precisely the same purlieu of any other context within said second concept represented by said cntexxt or no other said second concept represented by said cntexxt was valid for, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only where said purlieu is considered relevant to said first cnxpt and not relevant to any third cnxpt within the second cntexxt absent another characteristic;

xxx. a citing of a time frame that is not relevant to said concept being conjured by said user or during which said concept being conjured by said user was not valid but that is missing from all other contexts within said second concept represented by said cntexxt and not precisely excluded from encompassing the present time frame of said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only while said time frame is considered not relevant to said first cnxpt and is relevant to all third cnxpts within the second cntexxt absent another characteristic; and

xxxi. a citing of a purlieu that is not relevant to said concept being conjured by said user or during which said concept being conjured by said user was not valid but that is missing from all other contexts within said second concept represented by said cntexxt and not precisely excluded from encompassing the present purlieu of said second concept represented by said cntexxt, the differentiation stating a first characteristic and optionally stating a benefit due to presence of said characteristic and optionally stating a differentiated value due to presence of said characteristic, the characteristic valid only where said purlieu is considered not relevant to said first cnxpt and is relevant to all third cnxpts within the second cntexxt absent another characteristic;

whereby a description explaining differentiation is provided.

135. The method of claim 1 to search for and obtain wisdom, wherein:

a. searching by a search method to find wisdom to ingest, said search method selected from the group of;

i. searching by background crawling of web pages to obtain results;

ii. searching by background crawling of documents to obtain results;

iii. searching by accessing of databases to synchronize for structure by external marking and to ingest data;

iv. searching by search query specification re-execution to obtain revised results;

v. searching by background crawling of any external commonplace by search query specification re-execution with reapplication of prior culling to obtain results;

vi. searching by background crawling of any external source of wisdom by search query specification re-execution with reapplication of prior culling to obtain results;

vii. searching inside of found source objects to extract information before map generation to isolate elements common to sources and traits at binding points of concepts for differentiating cnxpts representing concepts, said binding point representing any conceptual meaning, said binding point for attachment of features characterizing the who, what, why, how, or how often said conceptual meaning is, do, appear, occur, perform, assembled, fit in, or participate, said binding point for attachment of time frame characterizing the when, attachment of location purlieu characterizing the where, ordering, or duration said conceptual meaning is relevant to, said elements selected from the group of;

word, phrase, string, time, purlieu, semantic feature, link, relationships to common target, locations in external categorizations, provenance, authority, element of law, jurisdiction, common context, title, data set name, table name, entity name, attribute name, section title, account, accounts payable item, accounts receivable item, address, agreement, answer, asset, attribute, author, bank, belief, benefits, bookmark, budget item, case, chapter title, character, citation, claim, classification category, communication, communication meta-data property, compensation, concept, concern, concordance entry, contact, context, cost, definition, description, diary entry, docket entry, document characterization, editor, endnote, estimate, event, evidentiary item description, expense, fact, figure, finding, footnote, goods, group, human resource, identity, index entry, informal citation, inventory control, inventory issuance, invoice, issue, journal entry, law, location, logistical detail, managed relationship, meaning, meta-data value, name, object, object meta-data, open question, opinion, orders, organization, originator, owner, page description, page text, participant, party, payroll, performance rating, person, position, precedent, prediction, price, products, project, projection, quality rating, quotation, quote, receipt, relationship description, request for information, request for proposal, requirement, reviewer, role, routing, rule, section text, section title, semantic token, service, shipment, shipping document, skill, statement, story, strategy, table, table of authorities entry, table of contents entry, table of figures entry, task, theory, thing, duration, equation, outcome, prediction, note, problem, reference, ordering, period, color, size, explicit differentiation, usage, proportion, assembly, subassembly, texture, pattern, instruction, placement, time, to do item, descriptive element, topic, type description, type identity, volume title, work effort, work requirement, and other descriptive term;

viii. searching by extraction of a subset of the commonplace having wisdom sought;

ix. searching after display of a visualization to obtain contextualized wisdom;

x. searching for information represented only by empty spaces within a context represented by a cntexxt where the concept represented by a space is only within the mind of the user and their wisdom is imparted to the commonplace by their staking the space to encompass that wisdom;

xi. searching of external sources, from a context represented by a cntexxt represented by a cnxpt from within a visualization of an organization of knowledge from a domain of wisdom formed due to interpretation of a map specification, to impart from said context of said map and a user'"'"'s acceptance of the relevance of results after culling from within said context of said map to said result of said search the contextualization information from the criteria specifying the map, the context within the organization of knowledge to improve usability for cataloging by utilization by users;

xii. searching of external sources from a context represented by a cntexxt represented by a cnxpt to simplify addition of contextualization information for a search result, improve usability for cataloging, provide cnxpt meaning improvement, and provide goal steering;

xiii. searching of external sources by custom searches;

xiv. searching of external sources by analytic;

xv. searching of previously obtained information by analytic;

xvi. updating a map specification upon extraction or refinement to provide a domain of wisdom as a result of searching with refinement of wisdom from the crowd of other users;

xvii. searching for categorization structure information to improve ability to discriminate between concepts by more specific differentiation by category;

xviii. searching within a domain of wisdom already extracted by navigating to find more specific wisdom;

and

xix. searching within a domain of wisdom already extracted by find or findall commands to find potentially relevant wisdom;

b. refining results of searching by refinement method, said refinement method selected from the group of;

i. narrowing results by provenance by fxxt extraction;

ii. narrowing results by fxxt specification interpretation for extraction;

iii. improving results by Boolean combination of fxxts after they are created;

iv. improving results by additional querying where results are added to a fxxt after culling;

v. improving results by additional culling of result set contents, optionally accepting new entries;

vi. narrowing results by applying access right restrictions while forming a fxxt from extraction or search result inclusion;

vii. improving results by additional culling of fxxt contents, optionally accepting new info-items;

viii. navigating to an area of an organization of knowledge to hide information in other areas or less detailed or more detailed that context positioned in;

ix. presenting a result set of concepts represented by cnxpts in the form of an area of consideration for culling to an area of interest to provide information hiding and navigation;

x. presenting a combined hierarchical and flow map of concepts represented by cnxpts in an organization by categorization and model result positioning to provide information hiding and navigation;

and

xi. filtering results for information hiding by specifying filter criteria;

c. forming a differentiation between two concepts represented by cnxpts by associating different concepts embodied in results referenced by generation of differing subject identifiers reduced from concepts that are detectably different in results, wherein;

i. forming a differentiation between a concept represented by a cnxpt from its context represented by a second cnxpt by associating different concepts embodied in results referenced;

ii. forming a differentiation between two concepts represented by cnxpts by associating different concepts embodied in results referenced;

and

d. using results of a search by a result utilization pattern to cause a benefit for system use, said result utilization pattern selected from the group of;

i. forming a secondary navigable visualization to ease understanding of obtained information to contain conceptual structures as a catalog of topical information;

ii. cataloging information resources after culling;

iii. moving a goal pointer represented by a cnxpt away from its current context to a context closer in meaning to what the references are about as embodied in results referenced;

and

iv. find a context represented by a second cnxpt being sought by using a match between said second cnxpt occurrences and concepts embodied in results referenced.

136. The computer-implemented method of claim 135 to produce a map from a commonplace of information demarcating the collective rationale of a crowd, further comprising:

a. including into said structuring at least one consensus belief determinative of an a priori event likelihood wherein an a posteriori event included is conditioned on said a priori event;

whereby users obtain consensus-based knowledge by reusing the results of others participating in a wisdom of crowds sourcing process where concepts are assembled into a commonplace of information having improving depth and quality and the slicing of the categorization shows consensus regarding outcomes.

137. The computer-implemented method of claim 136 to produce a map from a commonplace of information demarcating the collective rationale of a crowd, further comprising:

a. extracting at least one first cnxpt representing, at least as a fiction, an a priori event basis being knowledge acquired prior to subsequent probabilistic deductions, at least one second cnxpt representing an a posteriori event outcome, and at least one association connecting said first cnxpt to said second cnxpt indicative of the conditionality or contingency of the a posteriori event upon the a priori event, by fxxt extraction based upon consensus voting;

and

b. depicting an interpretation selected from the group of;

i. of the nature of a deductive semantic tableau proof tree for a deductive proof where the conclusion is true or false, or an inductive proof where the conclusion is merely probable, having at least one a priori event as a first cnxpt in a graph wherein said first cnxpt represents an event determinative of an outcome represented by a second cnxpt, wherein the orientation of the depiction is selected from the group of;

01. the root serves as the first step or given information in a proof, wherein said second cnxpt is structured to be more distant from the root of the spanning tree of the graph than said first cnxpt;

and

02. the root serves as the conclusion of the proof, wherein said first cnxpt is structured to be more distant from the root of the spanning tree of the graph than said second cnxpt;

ii. of the nature of a Bayesian belief network spanning forest having at least one a priori event as a first cnxpt in a spanning tree of the graph wherein said first cnxpt represents an event determinative of an outcome represented by a second cnxpt and said first cnxpt is structured to be more distant from the root of the spanning tree of the graph than said second cnxpt;

iii. of the nature of a root cause, problem tree, or part to sub parts breakdown forest having at least one a priori event as a first cnxpt in a spanning tree of the graph wherein said first cnxpt represents an event determinative of an outcome represented by a second cnxpt and said first cnxpt is structured to be more distant from the root of the spanning tree of the graph than said second cnxpt;

and

iv. of the nature of a claim dependency tree spanning forest having at least one a priori event as a first cnxpt in a spanning tree of the spanning forest wherein said first cnxpt represents an event determinative of an outcome represented by a second cnxpt and said first cnxpt is structured to be more distant from the root of the spanning tree of the spanning forest than said second cnxpt;

whereby users obtain consensus-based knowledge by reusing the results of others participating in a wisdom of crowds sourcing process where concepts are assembled into a commonplace of information having improving depth and quality and the slicing of the categorization shows consensus regarding outcomes and showing the rationale behind the outcomes.

138. The computer-implemented method of claim 137 to produce a map from a commonplace of information demarcating the collective rationale of a crowd in a deep map, further comprising:

a. depicting at least one a priori event as a cnxpt in a directed graph wherein said cnxpt is a root in the tree and is shown on a flattened map depicting a directed graph of Bayesian network, wherein the tree is shown in a third dimension from the flattened map under said cnxpt;

whereby users obtain consensus-based knowledge by reusing the results of others participating in a wisdom of crowds sourcing process where concepts are assembled into a commonplace of information having improving depth and quality and the slicing of the categorization shows consensus regarding outcomes and showing the rationale behind the outcomes.

139. The method of claim 135 to also provide for determining a chain of a priori justifications and a posteriori justifications to determine a likelihood that a hypothesis is correct, comprising:

a. preparing, by at least one processor, an organization of knowledge of a domain of wisdom from a commonplace according to utilize collective consensus through vote tallying means;

b. determining, by at least one processor, at least one chain segment comprising of an a priori justification and an a posteriori justification according to map generation means from said organization of knowledge of at least one domain of wisdom;

c. displaying to the user a portion of said organization of knowledge of at least one domain of wisdom according to display and delivery means;

and

d. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect changes by voting;

and

iii. to request searches;

whereby subject matter organized into belief networks is utilized for developing models.

140. The method of claim 1 to also provide culling of the occurrences, further including:

a. locating information by non-associative search query;

b. representing said information as an rsxitem in a result set;

c. presenting said information'"'"'s description or content to user;

d. accepting zero or more culling commands on said result set rsxitems according to result set processes means for stating opinions regarding relevance to said searches purpose;

and

e. setting the strength of said occurrence relationship info-item to said information based upon said opinions regarding relevance.

141. The method of claim 1 to update a map, further comprising:

a. re-rendering, dynamically, the display being viewed by said user of a visualization to adapt the displayed depiction to a change made to a cnxpt or association in the commonplace to conform the display to the result of changes made.

142. The method of claim 1 to improve quality of a generated map, further comprising:

a. deriving a consensus based on interactions of the generated validation of map by users;

and

b. modifying the map based on the derived consensus.

143. The method of claim 1 to also provide an engagement platform in a wisdom of crowds process where concepts are accessed, added, or refined in a commonplace of information, further comprising:

a. defining a cntexxt from a cnxpt instance on a conceptual level wherein said cntexxt is but what appears to be a vessel for the meaning of the cnxpt instance;

b. providing a display rendering of a depiction of a plurality of cntexxts as delineated areas of the depiction;

c. displaying a delineated cntexxt in a shape selected from the group of;

a circle, a sphere, a box, a chosen shape, and an avatar;

d. displaying a plurality of cntexxts on the display;

e. displaying a structure generated on a basis selected from the group of;

a categorization, a precedence ordering, a process flow, a decision making workflow, a decision tree, a Bayesian network, an ordered list, a directed graph, a random placement, an associative map, and an undirected graph;

f. showing cntexxt membership by depicting the delineated area of the depiction of a first cnxpt instance that is a member of a set represented by a cntexxt as being within and encompassed by said cntexxt;

g. arranging the plurality of cntexxts according to the structure generated selected from the group of;

i. a structure generated according to a categorization, the cnxpt instances within a cntexxt according to the strength of similar of cnxpt instances including the cnxpt instances external to the cntexxt wherein conceptually similar objects are in closer proximity than less similar objects;

ii. a structure generated according to a conditionality, dependence, or other directed graph basis, a first cnxpt instance in a position along an ordering line in a chosen aspect, the ordering implied by the directedness of the graph, with a second cnxpt instance wherein the second cnxpt instance is a subsequent cnxpt instance to the first cnxpt instance in the basis of the structuring;

and

iii. a combination of a plurality of structures generated wherein the structures are compounded and depicted as one by making useful interrelationships between the elements of the structurings to combine the aspects presented;

and

h. accepting navigation of and other user interaction commands related to the objects of the depictions displayed.

144. The method of claim 1 further comprising:

a. accepting and responding to a command selected from the group of;

i. command to add a definition of an instance of a model stating a calculation specification and rules for its information base;

ii. command to add a definition of a what-if value analysis scenario tuned to operate on a predetermined fxxt;

iii. command to add a definition of a data fault handler mechanism for a predetermined analytic, model, or prediction stating an error indication;

iv. command to define a belief distribution function;

v. command to display a property of an info-item and the current value of the property;

vi. command to display the properties of an info-item and the current calculation specification of a property of the info-item;

vii. command to display the sources of information prescribed by the current calculation specification of a property of an info-item;

viii. command to vote that a calculation specifications of a property is a different specification;

ix. command to add a property of an info-item;

x. command to set defaults for a property of an info-item;

xi. command to vote to remove a property of an info-item;

xii. command to obtain calculation results from a modeling analytic tuned to operate on said commonplace;

xiii. command to initiate processing of calculation specifications of a predetermined set of info-items;

xiv. command to initiate a methodology or workflow;

and

xv. command to initiate a what if modeling.

145. The method of claim 1 to also provide action workflows to user, further including:

a. providing task management and document management analytics for controlling workflows, and suggesting actions, the management enabled by a map;

b. initiating requests for action, with attached description of action, to a user according to methodology workflow specification step;

c. initiating alerts, with attached description, to a user according to an alert specification generation rule;

d. initiating methodologies according to said methodology templates;

and

e. initiating workflows according to said workflow templates.

146. The method of claim 1 to present knowledge in a visualization understandable as a map of concepts by a user, wherein:

a. generating a visualization selected from the group of;

i. map of technologies structured to visually represent that genealogical paradigm of incremental innovation wherein a more modern technology is depicted as an offshoot of an older technology and said more modern technology is thought of as a child of the older technology;

ii. map of technologies structured to visually represent that genealogical paradigm of incremental innovation wherein a more modern technology is depicted as a member of a set of technologies each member being differentiated from a concept seen as a progenitor of said member, said more modern technology also being thought of as a child of said progenitor;

iii. map of technologies structured to visually represent that differentiation paradigm of incremental innovation wherein a more modern technology is depicted as a member of a set of technologies each member being more specifically defined than a cntexxt representing the common features of all the members, said more modern technology also being thought of as a child of said cntexxt representing the common features;

iv. map of concepts structured to visually represent differentiation wherein a more specific concept is depicted as a member of a set of concepts each member being more specifically defined than a cntexxt representing the common attributes of all the members, said more specific concept also being thought of as a child of said cntexxt representing the common attributes;

v. map of legal doctrinal rules structured to visually represent differentiation wherein a more specific legal rule is depicted as a member of a set of rules each member of which being more specific and applying to a fact set of more specific definition than a cnxpt representing the general rule of said doctrine, said more specific rule also being thought of as a child of said cnxpt representing the general rule and said more specific rule being shown in a cntexxt filled by specific rules;

vi. map of legal doctrinal rules structured to visually represent differentiation wherein a more specific legal rule is depicted as a member of a set of rules each member of which being more specific and applying to a fact set of more specific definition than a cnxpt representing the general rule of said doctrine, said more specific rule also being thought of as a child of said cnxpt representing the general rule and said more specific rule being shown in a cntexxt filled by specific rules;

vii. map of legal fact sets structured to visually represent differentiation wherein a more specific fact set is depicted as a member of a set of fact sets each member of which being differentiated from its siblings and from a more general context by at least one legally differentiable fact, said more general context provides a simplified fact set definition generalized from the set of specific fact sets it contains and for which a general rule is stated and wherein the more general context states the set of facts against which the elements of said general rule would be applied and said more specific fact set also being thought of as a child of said more general context;

viii. map of occurrence sets structured to visually represent differentiation wherein a more specific occurrence set is depicted as a member of a set of occurrence sets each member of which being differentiated from its siblings and from a more general context by at least one additional or different occurrence wherein said more general context provides a smaller occurrence set all of which being related to the concept represented by said more general context and all occurrences of said more general context apply to all specific occurrence sets but each more specific occurrence set fails to properly characterize said concept represented by said more general context and each said more specific occurrence set is also to be thought of as a child of said more general context;

and

ix. a visualization of a structuring of concepts.

147. The method of claim 1 to also manage files, further including:

a. collecting a reference to an information resource or internal resource serving as an information resource into said commonplace and creating an irxt info-item to represent said information resource;

b. forming occurrence relationships between said irxt info-item and one or more cnxpts;

c. accepting categorizations and changes to categorizations of an information resource or internal resource serving as an information resource by a user administering file management;

and

d. providing fxxt specification templates for organizing said cnxpts into categorizations specified by said fxxt specification that thus also organizes said related information resource or internal resource serving as an information resource.

148. The method of claim 1 to manage the growth of knowledge, further comprising:

a. harmonizing categorizations by selecting connective hierarchical associations in forming a skeletal structure, giving priority to those associations whose accumulated weights of votes for use is highest to form an extracted categorization based upon a consensus view regarding the organization of knowledge;

whereby a more easily agreed upon, effective, efficient, or simpler structure is formed according to a collected consensus of opinions.

149. The method of claim 1 to also provide for managing a commonplace of information for research and discovery, further comprising:

a. controlling continuous processing and managing add-in function modules to calculate consensus and impute associations according to utilize collective consensus through vote tallying means;

b. providing coordinated access to analytics selected from the group of;

i. data extraction analytics for carrying out computer database searching, data extraction, transformation, translation, and loading;

ii. document management analytics for controlling, storing, accessing, and displaying electronically stored information resource documents;

and

iii. task management and document management analytics for controlling workflows, determining scheduling based upon workflow priorities, and suggesting task assignments;

c. providing an organization of knowledge, the knowledge selected from the group of;

i. regarding a study, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a issue;

ii. regarding the study, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a topic, concept, or sub-topic;

iii. regarding people and organizations, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, zero or more said cnxpts representing a person or an entity;

iv. regarding highly relevant and important information, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, zero or more said cnxpts representing desired to indicate a proof of a theory;

v. regarding events, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, zero or more said cnxpts representing an event capable of having a timeframe involved;

and

vi. regarding locations, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, zero or more said cnxpts representing a location;

d. loading of said commonplace with structural information defining a knowledge model;

e. initiating execution of continuous processing functions according to continuous processing means, the functions selected from the group of;

i. extraction of each source object'"'"'s identity, descriptive information, origination, and provenance meta-data to generate a source info-item with attached descriptive information, said type of source object selected from the group of;

an info-item from an external commonplace, a concept represented by a cnxpt from an external commonplace, data set, meta-data, file, information resource, statement, communication, template, decision, docket, story, transcript, and document;

said source info-item to be used as the authority control base for said source object and related to a new fxxt by a source relationship, said fxxt termed a source object provenance authority fxxt;

ii. extraction, for each source object that is a structured data set having data set elements, of all data set elements of said source object selected from the group of;

table description, entity type description, column description, attribute description, relationship info-item type descriptive information, table procedure description, object method description, and data rule description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said data set elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, said all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

iii. extraction, for each source object that is a structured data set having data set elements, of all data rule descriptions of said source object to generate, for each, a concept represented by a cnxpt with attached descriptive information, said cnxpt to be used as curation reference base, said cnxpt termed a source data rule authority cnxpt;

iv. extraction, for each source object that is unstructured data, of all descriptive elements of said source object selected from the group of;

object meta-data, citation, page description, foot or end note, volume title, section title, chapter title, book mark, section text, page text, type description, definition, index entry, part, table of contents entry, author, editor, table, figure, character, precedent, quotation, topic, issue, finding, opinion, test, question, hypothesis, experiment, sample, batch, and description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said descriptive elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, said all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

v. extraction, for each source object that is unstructured data, a cited information resource irxt info-item for any information resource not existing in said commonplace of information;

and

vi. extraction of topical elements from said source object, said topical element selected from the group of;

term, timeframe, thing, feature, link, status, originator, event, party, participant, person, owner, address, location, organization, reviewer, rule, test run, experiment, object, relationship info-item description, type identity, question, hypothesis, experiment, sample, batch, part, law, citation, claim, belief, strategy, concern, position, document characterization, communication, communication meta-data property, fact, missing information, statement, opinion, issue, case, docket entry, story, theory, semantic token, name, statement, precedent, attribute, identity, evidentiary item description, concept, context, classification category, meta-data value, and other description;

each said topical element to be used as a base for deriving commonalty and similarity scores for said source object, wherein a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, said all instances of said coding key cnxpt of a type are assigned a single fxxt based upon said source object provenance authority fxxt and the type of coding key;

f. ingesting a plurality of source objects;

g. determining zero or more metrics for characterizing a source object, the metric selected from the group of;

i. relevance of said source object to a search objective stated as a search query specification step wherein said source object is a result set item in a search result set;

ii. pertinence of said source object for a domain of wisdom extraction objective stated as a fxxt specification step wherein said source object is an info-item of any type applicable to said fxxt specification step;

iii. pertinence of said source object for a prioritization rule of a methodology workflow specification step wherein said source object is an info-item of any type applicable to said methodology workflow specification step;

and

iv. pertinence of said source object for an alert generation rule of an alert specification wherein said source object is an info-item of any type applicable to said alert specification generation rule;

h. executing the means for categorizing said commonplace by performing map generation, wherein a computer performs management of said commonplace, and prepares at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means wherein said organization of knowledge of at least one domain of wisdom includes said source object provenance authority fxxt and also includes any additional portion of said commonplace against which categorization or comparison or curation is to occur;

i. building at least one visualization for display to users based upon said organization of knowledge of at least one domain of wisdom to use as an organizing base for initial viewing;

j. initiating zero or more workflow functions selected from the group of;

i. requests for action, with attached description of action, to a user according to methodology workflow specification step;

ii. alerts, with attached description, to a user according to an alert specification generation rule;

iii. methodologies according to said methodology templates;

and

iv. workflows according to said workflow templates;

k. providing zero or more template aids selected from the group of;

i. search query procedure templates for searching for source objects to determine relevance;

ii. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

and

iii. providing methodology and workflow templates for project management of searching for and reviewing source obj ects to determine relevance to a stated meaning or issue;

l. providing prediction analytics establishing commonalty and similarity scores for source objects;

m. computing a predicted weighted ranking of a source object likely relevance to a coding key cnxpt as specified;

n. computing a predicted weighted rejection ranking of a source objects according to rules for rejection as irrelevant or privileged;

o. accepting data rule descriptions as concepts represented by cnxpts with attached descriptive information, said cnxpts to be used as curation reference bases, said cnxpts termed source data rule authority cnxpts;

p. accepting culling commands in manual review to categorize source objects according to said concepts and contexts as represented by cnxpts;

q. accepting culling commands in manual review to re-prioritize source objects for further review according to specified workflow rules or to remove them from further review or from collection of source objects in commonplace of information;

and

r. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effecting change;

iii. to navigate around a visualization of said commonplace;

iv. to request a search for wisdom;

v. to enter a fxxt specification involving extraction by meta-data and search queries to meet criteria for project;

vi. to accept a workflow task;

vii. to specify search query specifications, workflow task assignment and document passing specifics to meet criteria for project;

viii. to initiate operation of data extraction, document management, and prediction analytics;

ix. to initiate continuing retrieval of source objects based on the criteria according to search query specifications;

x. to establish a commonplace of information for the purposes of a specific dispute or study, termed a discovery preparation set;

xi. to ingest into said discovery preparation set commonplace of information a source object set;

xii. to grant access to a source object to a different user for the purposes of a specific dispute or study, the accumulation of said grants termed a discovery production set;

xiii. to categorize source objects into workflow contexts;

xiv. to allocate resources according to specified workflow rules for assignment or workflow rules for task acceptance;

xv. to refine search query specifications, categorizations, and priorities for review;

xvi. to specify relevance prediction weightings;

xvii. to notify a supervisory level regarding a source object'"'"'s importance;

xviii. to specify details for workflow structure and categorizations by establishing contexts for work tasks represented by cnxpts and workflow transitions represented by relationships to meet criteria for project;

xix. to alter a workflow based upon quality checks produced by workflow and methodology;

xx. to alter a workflow based upon review of metrics produced by workflow and methodology;

xxi. to generate a report or data set of the data set catalog, provenance, production cost, and consensus regarding relevance weights of said discovery preparation set or said discovery production set;

xxii. to generate an extract data set of said discovery preparation set;

and

xxiii. to generate an extract data set of said discovery production set;

whereby search retrieval and information organization are applied to the discovery review process.

150. The method of claim 1 to also provide for improving user learning efficiency, comprising:

a. providing to a learner the ability to connect new information with relevant preexisting topics or propositions in the learner'"'"'s own cognitive structure as provided by a map wherein a learner can assimilate new topics represented by ttxs and propositions implemented as relationship info-items into their existing cognitive structures;

b. empowering serendipitous learning to learn of known topics represented by ttxs that a user had previously not studied or known about individually through browsing within ttx categories or subject areas and increasing the likelihood of discovering resources that are tangentially related to said known topics;

c. empowering incremental explorative browsing alongside other techniques to look for something specific by traversing from a context represented by a first cnxpt to a more detailed context represented by a second cnxpt;

and

d. providing visual devices to heighten the mental excitement as would occur in game program to keep the speed of learning high.

151. The method of claim 1 to produce lists of prior art in the technology domain, further including:

a. forming a query for parents of a tcept in an organization of knowledge based upon incremental innovations;

and

b. listing the results of the query;

whereby a roadmap of prior innovations is produced.

152. The method of claim 151 to compute a value for a product or technology, wherein:

a. identifying an association instance between a first cnxpt instance and a second cnxpt instance in a commonplace of information wherein said first cnxpt instance comprises a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt instance;

and

b. summing said property of each first cnxpt instance having a relationship represented by an association with said second cnxpt instance to form a value for said second cnxpt instance according to primary tcept value prediction means by at least one of simple addition, an analytic or other summing algorithm as specified in additional specification;

whereby a value imputed from a forest of cnxpts is used in modeling and to obtain a prediction.

153. The method of claim 152 to compute a value for a product or technology, wherein:

a. forming a timeline by ordering conceptual meanings by a time point associated with said constraint, said time point selected from the group of;

initial recognition of constraint, mid-point, point at which said constraint is anticipated to become obsolete, point at which products based upon said constraint are anticipated to be altered or replaced to conform to new constraint, median of distribution, mean of distribution, and any other specified constraint summarizer, wherein the form of said timeline is of the group of;

a list, a graphical composite of durations, and other specified visual form wherein conceptual meanings are shown;

b. determining effectiveness of each cnxpt according to said timeline by determining the timeframe between when said cnxpt begins to be viable and when said cnxpt will no longer be viable;

and

c. prorating the values imputed from other forests based upon the timeframe of effectiveness of said second cnxpt and each said first cnxpt;

whereby a value imputed from a forest of cnxpts is used in modeling and to obtain a prediction of value under competitive scenarios.

154. The method of claim 1 to also provide a registry for claiming of ownership of ideas, further comprising:

a. locating a cntexxt within which a user believes a cnxpt may properly be created as a subdivision;

b. creating a cnxpt within the cntexxt by stating a differentiation of the cnxpt with respect to the cntexxt;

and

c. registering a right to a portion of a cntexxt occupied by the cnxpt, the scope of the right selected from the group of;

scope limited to the cnxpt as an innovation with regard to the cntexxt, scope limited to the cnxpt as an innovation with regard to the cntexxt and other cntexxts wherein the same right has been claimed by the same user, and scope limited to the cnxpt as an innovation without regard to the cntexxt.

155. The computer-implemented method of claim 154, further comprising determining a rights policy of that represented by a cnxpt as a function of a rights policy of a cnxpt info-item.

156. The method of claim 155, wherein the ownership right comprises zero or more rights selected from the group of:

a creation right, a use right, and a commercial right.

157. The method of claim 1 to also form a value estimate of an appcept, further comprising:

a. calculating total space consumed by the two-dimensional area occupied by an appcept taken over all appcepts shown on a map of appcepts at a given depth of said map;

b. calculating total value of appcepts shown on the map of appcepts at the given depth of said map by adoption of an estimate for the depth, a model, or an imputation;

and

c. calculating value of the appcept based upon proportion of space by dividing the area of the appcept by the total space consumed on a map of appcepts at a given depth of said map and multiplying it by the total calculated value for the depth.

158. The method of claim 157 to also form a value estimate of a tcept, further including:

a. calculating total space consumed by the two-dimensional area occupied by a tcept taken over all tcepts shown on a map of tcepts at a given depth of said map;

b. calculating by estimate, model, or imputation the total value of tcepts shown on the map of tcepts at the given depth of said map;

and

c. calculating value of a tcept based upon proportion of space by dividing the area of the tcept by the total space consumed on a map of tcepts at the depth of the map and multiplying it by the total calculated value.

159. The method of claim 157 to also form a value estimate of a tcept, further comprising:

a. calculating, by imputation of a summed value from appcepts in the second organization of knowledge that have time-based estimates of value and are related by a satisfaction of need relationship to a tcept in the first organization of knowledge, the total value of a tcept;

whereby prediction by time horizon of applications of technology is imputed to determine values of technologies satisfying the requirements of a set of applications.

160. The method of claim 157 to also form a value estimate of a cnxpt, further comprising:

a. calculating, by imputation of a summed value of the space occupied by appcepts in the second organization of knowledge that are related by a satisfaction of need relationship to a tcept in the first organization of knowledge, the total value of a tcept;

whereby prediction by space of applications of technology is imputed to determine values of technologies satisfying the requirements of a set of applications.

161. The method of claim 1, further including:

a. protecting the description of a novel new idea;

b. providing tools for preparing provisional patent applications describing said novel new idea recently entered into said commonplace;

c. generating text for said patent application describing the context of said idea based upon its position in a categorization of technology ideas and the descriptions of said categories, the metadata regarding said novel new idea, and any description entered for said novel new idea;

and

d. providing tools for submission of said provisional patent application.

162. The method of claim 161, further comprising:

a. assisting the owner of a newly entered cnxpt in completing a description of the invention based upon the idea represented by the cnxpt instance by methods selected from the group of;

i. providing the prior art for the innovation taken from the categorization of the new cnxpt in a map where the root of the tree of each tree where the cnxpt instance is placed is the oldest entered technology within each family the inventor has found to be where the new idea should be related as an off-shoot;

ii. providing the user with a form for gathering and recording information needed for a provisional patent in the jurisdiction decided upon;

iii. providing a space on the form for entry of one or more sentences describing the innovation represented by the new cnxpt instance beyond the description provided by the information describing the categories providing the context of the new cnxpt instance;

iv. providing a path to additional assistance by listing resources including at least links to the patent office desired, books, forms, and patent agents;

and

v. providing the option for the inventor to submit electronically or by printed forms to the patent office the information collected, and completing the chosen process upon the decision to do so by the inventor.

163. The method of claim 1, further including:

a. providing a marketplace for requesting problem solutions, requesting idea extension, selling rights to ideas, requesting expertise, and offering expertise;

b. providing online communities based upon specific concepts;

and

c. providing a communal innovation process allowing others to join to work on ideas in a protected environment on an access controlled basis.

164. The method of claim 72 to also provide for collaboratively developing technologies related to concepts within a commonplace of information, further comprising:

a. providing an interface for users to view, navigate and enter commands to interface with said commonplace;

b. preparing at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means;

c. granting or rejecting access to said commonplace for a given type of interaction;

d. offering an agreement with terms for connection and collaboration;

e. forming a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt in one or more phases selected from the group of;

i. selecting an object of wisdom to act upon;

ii. requesting contact with at least one person knowledgable regarding a cnxpt representing a concept within a context, the cnxpt of said domain of wisdom;

iii. requesting making contact with a listed person, project consortia, or organization;

iv. requesting display of a result set for culling;

v. requesting purchase of a listed item;

vi. scheduling specified participation;

vii. requesting investment in a listed project consortia, pool, or organization;

viii. stating an opinion;

ix. stating completion status of a task;

x. stating interest;

xi. offering an incentive;

xii. offering a funding incentive;

xiii. requesting vetting information or access to vetting information;

xiv. requesting consideration for funding;

xv. stating an evaluation;

xvi. requesting consideration for pool graduation;

xvii. stating consortia formation;

xviii. publicizing for consortia participation;

xix. negotiating for consortia participation;

xx. negotiating for deliverable acceptance;

xxi. negotiating for assignment;

xxii. negotiating for investment pool graduation;

xxiii. requesting display of a structural view of cntexxts based upon wisdom found;

and

xxiv. requesting the navigating to a cntexxt based upon wisdom found;

and

f. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect change;

iii. to navigate around a visualization of said commonplace;

and

iv. to request a search for wisdom.

165. The method of claim 164 to also collect commercialization status information, further including:

a. collecting interest information based upon user navigation to cnxpts in a visualization, changing of information related to a cnxpt, or searching where a cnxpt is a result of said search;

b. accepting plug-in methodology or workflow definitions;

and

c. accepting answers to survey questions presented to said user as provided for in a methodology or workflow;

wherein said methodologies or workflows both assist a user in their commercialization endeavor by providing step by step information on relevant topics as after the idea education and idea development direction, but also provide team management and commercialization process measurement to collect information to prove up that idea is making progress toward real usefulness.

166. The method of claim 1 to also provide providing tools for competing in innovating, further including:

a. providing tools for commercializing, and analyzing concepts;

b. collecting information regarding the progression of commercialization of a technology concept;

c. collecting vetting information for companies seeking funding;

d. preparing the history of commercialization progress vetting information for release for due diligence by funding sources;

e. obtaining consent of the owner to release said information;

and

f. releasing said information to a funding source.

167. The method of claim 166 to also manage investment pools, further including:

a. providing tools for managing said investment pool and participants according to innovation investment pools means;

and

b. providing procedures and tools to the parties involved in transactions involving investment pools, the procedures and tools selected from the group of;

i. providing tools for defining an investment pool'"'"'s legal and operational structure, purpose, entry incentives, termination rules, progress rewards, its entry term sheet criteria and graduation guidelines;

ii. accepting accounting of funds;

iii. providing tools for defining entrant due diligence information requirements as a methodology or workflow;

iv. accepting information from entrant candidates for application for entry and for due diligence;

v. preparing notices offering entry to qualified startups;

vi. providing tool for making a market by negotiating a graduation to sell a held stake to another pool or a funding source according to innovation investment pools means;

vii. enabling an investment pool graduation process between the entities by automatically generating contract terms based on a negotiation between the parties;

viii. enabling a workflow for decision guidance for the negotiation process between two entities wherein decisions made and information provided associated with a decision guidance are taken together to produce a contract term for use in a contract between the parties;

ix. managing multi-sided auction process, the tool to accept and act as match maker based upon statements selected from the group of;

offer for acceptance into a pool from interested investment pool, offer for direct investment from interested investor, showing of interest to be added into an investment pool by a consortium, offer for merger from interested consortium or investment pool, showing of interest to be merged into a consortium by a consortium, interest statement providing the criteria an investment pool has set for qualifying a consortium, interest statement providing the criteria an investor has set for qualifying a consortium for investment, interest statement providing the criteria a consortium has set in seeking investment, interest statement providing the criteria a consortium has set in seeking graduation from an investment pool, interest statement providing the criteria an owner has set in seeking buyer for share of ownership, policy constraint on transaction, track record information regarding consortium, track record information regarding investment pool, track record information regarding investor, investigation result, credit report, intellectual property report, financial report, product assessment, competitive intelligence report, recommendation, ownership report, ownership changes, restructuring plans, investigation report, verification report, and conflict of interest information report;

x. defining progress information requirements as a methodology or workflow;

xi. accepting progress reporting information for enrollee startups;

xii. providing tool for evaluating enrollee startups;

xiii. providing tool for preparing startup progress report;

xiv. providing tool for suggesting enrollees for termination;

xv. managing job board matchmaking auction process for enlisting and placement into consortium roles, the tool to accept and act as match maker based upon statements selected from the group of;

skill requirement criteria by a consortium, skill and ability and criteria resume by a role candidate, showing of interest to take role in consortium, offer to take role from a consortium, policy constraint on transaction, track record information regarding consortium, track record information regarding consortium, track record information regarding candidate, investigation result, credit report, intellectual property report, financial report, product assessment, competitive intelligence report, recommendation, ownership report, ownership changes, restructuring plans, investigation report, verification report, and conflict of interest information report;

xvi. providing tool for enforcing rules and confidentiality;

xvii. managing the tracking of status in a workflow;

xviii. accounting for the transaction agreed to by the parties;

xix. providing notice of upcoming workflow event;

xx. storing an immutable copy of the transaction data structure in a secured location;

and

xxi. summarizing value of said pool and generating reports.

168. The method of claim 1 to also provide for organizing opportunity matching, further including:

a. capturing new concepts;

b. organizing said new concepts into categories;

c. providing a marketplace for wisdom regarding ideas;

d. granting access to said commonplace;

e. providing search facilities for finding said new concepts in said categories;

f. collecting user interest information;

g. providing a marketplace for ideas;

h. providing facilities for organizing participation by a user in collaboration regarding said new concepts in said categories;

and

i. providing tools for managing potential and realized valuable results of said collaboration regarding said new concepts in said categories.

169. The method of claim 168 to also provide for obtaining transactions fees on the basis of collecting new concepts into a commonplace, further comprising:

a. capturing new concepts;

b. granting access to commonplace of information;

c. providing a marketplace for wisdom regarding ideas;

d. collecting user interest information;

e. providing a marketplace for ideas;

f. providing a marketplace for data related to specific concepts;

g. collecting fees associated with matching opportunities according to negotiated collaboration terms;

h. providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas;

and

i. accepting a request to search for wisdom.

170. The method of claim 1 to enable verifiable and secure transactions regarding ideas, further comprising:

a. providing a value creation structure comprises;

i. generating ownership rights for a set of one or more ideas represented by one or more cnxpts, wherein;

01. encapsulating, for each ownership right, origination data related to the ownership right and the corresponding cnxpt within a transactional data structure, termed a registry;

and

02. accepting stating of a claim of ownership of an idea represented by one or more cnxpts, termed staking;

ii. detecting a first transaction that involves a change in ownership over an idea represented by one or more cnxpts;

iii. adding first transaction data related to the first transaction in the transactional data structure;

and

iv. granting access to a user of the one or more cnxpts representing an idea only according to the then-current ownership right where one exists;

whereby purported ownership for specific idea is delineated according to a staked claim.

171. The method of claim 170, further comprising deriving a chain of ownership changes based on the transaction data structure.

172. The method of claim 171, further comprising encapsulating origination data related to the ownership right and the corresponding cnxpt within a transactional data structure that is temper-proof.

173. The method of claim 172, further comprising encrypting data within the transaction data structure before distributing the transactional data structure.

174. The method of claim 172, further comprising accepting a first transaction involving a first entity acquiring from a second entity at least one item selected from the group of:

the cnxpt, access to the cnxpt, access to a communication regarding the cnxpt, control over access to the cnxpt, addition of a new member to the cntexxt defined by the cnxpt in a map, and the set of objects represented by the cnxpt.

175. The method of claim 1 to also manage legal information for attorneys, further including:

a. accepting legal information into said commonplace as an information resource or internal resource serving as an information resource;

b. accepting classifications of said legal information into categories stated as cnxpts;

and

c. applying a fxxt to rearrange said information for use in preparing for one of one or more litigation purposes.

176. The method of claim 175 to manage a commonplace of legal information, further including:

a. creating a fxxt to establish a domain for legal rules;

b. creating a fxxt to establish a domain for factual situations or fact sets;

c. establishing a cnxpt to represent a fact;

d. establishing a cnxpt to represent an article of evidence, said cnxpt having zero or more occurrences referencing a tangible entity;

e. establishing a cnxpt to represent a rule;

f. establishing a cnxpt to represent an element of a rule having one or more traits stating a traits of an element of a rule;

g. establishing a plurality of associations between cnxpts representing rules and cnxpts representing elements of rules to define the tests needing to be satisfied to apply a law;

h. establishing a characteristic on a cnxpts to represent a fact;

i. establishing a plurality of associations between cnxpts representing facts and cnxpts representing elements of rules to apply facts to law;

j. categorizing precedent and statutes over time by issues as well as citation;

k. searching for pertinent law by a large number of attorneys is an expert level crowd sourcing wisdom of crowds operation already;

l. representing issues by cnxpts;

m. representing legal doctrines by cnxpts;

n. representing specific opinion text by cnxpts;

o. representing opinion texts, court orders, trial documents, statutes, and other documents are represented by information resource info-items. connecting opinion text by cnxpts;

p. establishing a plurality of associations between cnxpts representing fact sets or disputed issues and cnxpts representing opinion text, elements of rules to apply facts to law;

and

q. granting access to subsequent users interested in an issue.

177. The method of claim 175 to also provide for finding the case on point in legal research by weighted categorization, further comprising:

a. finding similarities between two concepts selected from a group of;

i. a first fact from a first case and a second fact from a second case where the similarity of said first fact and said second fact causes an extrapolated belief that said first case is related by fact similarity to said second case and thus the legal issues or sub-issues involved in said first case are related to or resemble the legal issues or sub-issues involved in said second case;

ii. a first element or sub-element of a first law and a second element or sub-element from a second law where the similarity of said first element or sub-element and said second element or sub-element causes an extrapolated belief that said first law is related by element or sub-element similarity to said second law and thus the evidentiary and doctrinal legal issues or sub-issues involved in said first law are related to or resemble the evidentiary and doctrinal legal issues or sub-issues involved in said second law;

iii. a first element or sub-element of a first law and a second fact from a second case where the satisfaction of said first element or sub-element by said second fact causes an extrapolated belief that said first law is to some degree applicable at least in part to said second case and also that the evidentiary burden and doctrinal legal issues or sub-issues involved in said first element or sub-element of said first law are relevant to establishing satisfaction of said first element or sub-element by evidence in said second case;

and

iv. a first element or sub-element of a first law of a first jurisdiction and a second fact from a second case in said first jurisdiction where the satisfaction of said first element or sub-element by said second fact causes an extrapolated belief that said first law is highly applicable at least in part and to a determinable degree to said second case and also that the evidentiary burden and doctrinal legal issues or sub-issues involved in said first element or sub-element of said first law are relevant to and establish requirements for establishing satisfaction of said first element or sub-element by evidence in said second case under the constraints imposed by evidentiary rules for such an element or sub-element and doctrinal legal precedent found in a prior decision in a third case in said first jurisdiction involving said first law.

178. The method of claim 175 to also provide for evidence discovery and presentation management, further comprising:

a. breaking down law to elements;

b. establishing occurrences to cnxpts representing facts;

c. categorizing elements or sub-elements of laws to be associated with law, a cnxpt representing an element, a cnxpt representing a sub-element, a cnxpt representing a law;

d. categorizing elements of precedent, contract, legal opinion, other elements, or doctrine in one or more hierarchical organizations of cnxpts;

e. establishing associations between facts and elements of a pertinent law to apply facts to law;

f. associating an issue or sub-issue or opinion text cnxpt to categorize said issue or sub-issue by associations between cnxpts by the searching or manual operations as discussed below;

g. making available result sets developed by a first interested user to subsequent user to enable efficient searching to said subsequent user and then also to said first interested user;

and

h. accepting associative searching to track issue or sub-issue development.

179. The method of claim 178 to also provide for legal case planning, further comprising:

a. categorizing cnxpts representing legal information selected from the group of;

fact, cause, legal theory, statute, precedent, issue, general rule, rule element, and sub-element to obtain a structuring;

b. forming more specific instances of a rule element or sub-element where differentiations have been cited by precedent or legal theory, associating the more specific instance to the more general by hierarchical association;

c. associating incidences of similar legal information to retain understanding of the logical similarity;

and

d. connecting a fact represented by a cnxpt to a law element or sub-element represented by a cnxpt by association between fact cnxpt and rule element or sub-element cnxpt.

180. The method of claim 175 to also provide determination of legal clarity, further comprising:

a. generating a commonplace regarding technology concepts, intellectual property, and contracts, each represented by cnxpts;

b. defining one or more fxxts for marking information in the commonplace;

c. generating one or more maps describing technology derivations;

d. generating zero or more maps describing intellectual property transactions;

e. generating zero or more maps describing legal precepts;

f. accepting entry of additions to the content of the commonplace;

g. accepting entry of votes relating beliefs regarding the content of the commonplace;

h. allowing searches relating to the topics of the commonplace;

i. accepting information from a user needed for filing a patent application, and causing the automated filing of the patent application;

j. utilizing the context into which a user classifies their potentially patentable idea to generate a listing of prior art for the idea from a map, and adding the list to a patent application to be filed;

k. accepting classification from a user to contextualize a potentially patentable idea;

l. determining by crowd wisdom a meaning arguably more objective than any single opinion expressing a definition of the meaning of a topic represented by a cnxpt, the consensus determination using a map;

m. detecting divergence of opinions on a topic represented by a cnxpt, by detecting non-consensus to show a failure of praxis;

n. showing sources of information regarding topics and issues represented by cnxpts cataloged by topic or issue;

o. showing topics and issues side by side other similar topics and issues represented by cnxpts;

p. presenting an associative view of cnxpts in each classification map to speed user understanding and search;

q. providing dynamically organized indices for classification to improve efficiency of index maintenance;

r. providing dynamically organized indices for classification of ideas represented by cnxpts based upon collective intelligence to remove costs from index maintenance;

s. providing dynamically organized indices for classification of documents to improve efficiency of document management;

t. providing dynamically organized indices for classification of documents based upon collective intelligence to remove costs from index maintenance;

u. refining a meaning for a topic from the expressing of opinion regarding said meaning by accepting a plurality of user movements of a visual object representing said topic to a different context on a map;

v. predicting the actual meaning of a topic from the expressing of opinion regarding said meaning by a plurality of users;

w. predicting the actual meaning of a topic from the moving a visual object representing said topic to a different context on a map and forming a consensus determination regarding the proper context;

x. retaining and updating the research work of a user by automatically re-querying searches used as subject identifiers;

y. combining the results from several sources to amalgamate an organization of a body of knowledge requested by a user as shown in a map where the information needed for classification is sparse;

z. providing an associative platform for viewing the law based upon resolved precedence and prospective use of precedents and the prior work by others in a plurality of highly coalesced organizations each shown on a map for navigation and eliciting serendipitous recognition of issues, alternative viewpoints, and alternative theories regarding a matter to expand yet organize and summarize what others considered in situations rather than merely on their results in court opinions;

and

aa. predicting the strength of an argument based upon the ranking of issues, applicability of precedent, and weights of facts where prior success as shown by positions of parties in prior cases could be assessed for similarity or gauged by an attorney given a similar fact pattern;

whereby a map can decrease an inventor'"'"'s time to file for patent protection;

whereby a map can reduce the cost to file for patent protection;

whereby a map showing prior art can reduce the burden on an inventor to explain best mode and the possibility of non-public inventorship;

whereby the common understanding of the issues and topics represented by cnxpts as recorded by others in legal matters, research papers, and documents can be improved with a map;

whereby the common understanding people have regarding definitions of a topic represented by a cnxpt can be improved by use of subject identifier searching and associative positioning in a map; and

whereby providing depersonalized expression of opinions on definitions of a topic represented by a cnxpt and its categorization, by intermediation by a commonplace manager operating on consensus determination and by introduction of one or more maps as the vehicle of communication, removes stress and provides a better evidentiary body.

181. The method of claim 175 to also provide for classification by types of authority in legal research by weighted categorization, further comprising:

a. finding similarities between a first opinion regarding an element or sub-element of a first law of a first jurisdiction and a second opinion regarding a similar second element or sub-element of a second law in a second jurisdiction and imputing a relationship info item with a weight depending upon the degree of similarity of said element, the degree of similarity of said law, and the nature of the authority as mandatory and binding or persuasive and non-binding or not applicable and the level of the courts of said first and said second jurisdictions;

b. accepting a characterization of a first jurisdiction'"'"'s authority relative to a second jurisdiction'"'"'s authority as mandatory authority or persuasive authority;

c. accepting a characterization of a first jurisdiction'"'"'s opinion relative to a second jurisdiction as mandatory or persuasive;

and

d. accepting a characterization of a first jurisdiction'"'"'s opinion relative to a second jurisdiction as followed or not followed but considered, with one or more citations to opinions of said second jurisdiction, said one or more citations to opinions of said second jurisdiction describe the reasoning specifically regarding said first jurisdiction'"'"'s opinion.

182. The method of claim 1 to also provide tool for competitive innovation analysis and research document management, further including:

a. providing an environmental scanning process workflows for managing the collection of competitive data according to map generation means and according to alter information through visualization means;

b. providing competitive analysis workflows tuned to operate on said commonplace;

c. providing modeling tools for competitive analysis what if value analysis tuned to operate on said commonplace according to map generation means;

d. providing competitive product analysis information repository commonplace standards for managing and sharing competitive information on an access controlled basis;

and

e. accepting commands from a user to initiate a map generation and to utilize a map according to alter information through visualization means.

183. The method of claim 182 to also provide assistance in creativity, further including:

a. analyzing gaps in knowledge toward solutions according to generate prediction of innovation gap means;

b. generating suggested matchings between traits according to generate commonality relationships means;

c. generating roadmaps of cnxpts according to assisted creativity means, according to map generation means, and according to forming predictions means;

d. showing state of obsolescence of a cnxpt;

and

e. generating suggestions of differentiations of a cnxpt possibly usable form a new cnxpt according to generate TRIZ based candidate suggestions.

184. The method of claim 182, to structure competitive intelligence use of concepts collected into a commonplace, further comprising:

a. determining, by at least one processor, at least one visualization of a map for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

b. displaying to said user a portion of said organization of knowledge of at least one domain of wisdom according to display and delivery means;

c. estimating timings for states of product obsolescence in competitive areas;

d. providing modeling tools for competitive analysis what if value analysis;

e. providing information repository structures for managing and sharing competitive information on an access controlled basis;

f. processing zero or more environmental scanning process methodologies;

g. managing the collection of competitive data;

and

h. accepting and processing a command and effecting changes therefrom, said command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect change;

iii. to navigate around the visualization of said commonplace;

iv. to request a search for wisdom;

v. invoke a crawling task;

vi. to initiate a workflow;

vii. to initiate a methodology;

viii. to define a belief distribution function;

ix. to initiate a what if modeling;

x. to invoke repetitive searching for semi-automatically refreshing;

xi. to specify a liquidity scenario for an investment pool;

xii. to invoke procedures for protecting a cnxpt;

xiii. to invoke procedures for commercializing a cnxpt;

xiv. to show information stemming from predictions regarding an info-item;

xv. to enter a shared information collection and analysis effort;

xvi. to specify a methodology or workflow to train;

xvii. to initiate a collective;

xviii. to initiate collective information controls involving at least one of;

business plans, consortium documents, company formation documents, founder profiles, consortium management information, negotiation documents, competitive company profiles, requirements of technology, application requirements, consortium product line plans, investment analysis, development progress, crowdfunding information, and associate compensation agreements;

xix. to initiate a financial transaction;

xx. to define a competitive analysis methodology;

xxi. to define a methodology instance;

xxii. to define a competitive analysis effort;

xxiii. to define a commonality determination rule,

and

xxiv. to define a commonality determination rule stating an enrolling of a modeling tool for competitive analysis by what if value analysis tuned to operate on said commonplace and said categorizations produced according to map generation means;

whereby a platform for examining existing, competitive products is provided to identify competitor plans, market strategies, alternatives analyses for assessing a feature change or market strategy.

185. The method of claim 1 to also extract data sets, further:

a. structuring said commonplace to extract content;

b. detailing a fxxt specification defining at least one said extraction to perform for said fxxt;

c. defining a map specifying inclusion of at least said fxxt;

d. detailing by said fxxt said commonplace by marking zero or more info-items selected from the group of;

cnxpt instance, cnxpt class, association instance, association class, info-item instance, and info-items class;

as members of the resulting said named derived ontology of said map;

e. interpreting said map definition to extract fxxts from said commonplace by marking cnxpt instances and association instances as members of said fxxt;

and

f. packaging the resulting said named derived ontology for said map as a data set.

186. The method of claim 185 to also form a categorization data set, further including:

a. detailing a map specification defining at least one said categorization;

b. generating a map instance based upon said map definition;

and

c. exporting said map packaged as an extract data set.

187. The method of claim 186, to determine a multi-dimension mining extraction of predetermined set of characteristics of cnxpts into a data package, further comprising:

a. executing one or more cnxpt sub-setting operations selected from the group of;

a query, a reduction, a derived ontology, a fxxt extraction, a flow extraction, execution of an analytic, selection of a data set, selection of a portfolio, selection of a uniquely identified categorization, selection of a uniquely identified clump extract set, a filter application, a query in a map resulting in an area, a query in a map resulting in a result set of cnxpts, or a user ad hoc selection set of cnxpts to obtain a set of cnxpts resulting from each of said sub-setting operations wherein each said set of cnxpts defines a cube dimension for extraction into said data package;

b. forming a set of intersection identifying tuples wherein each tuple is an ordered tuple of dimensionality set by the number of dimensions obtained by said sub-setting operations and wherein each tuple is constructed by selecting one cnxpt from each set of cnxpts defining a dimension to hold a tuple position associated with the dimension identified by the order of said position in the tuple;

c. forming a subset of said intersection identifying tuples by extracting associations according to apply fxxt specification means based upon zero or more fxxt markings wherein only tuples where the cnxpts of the tuple are fully connected by said extracted associations are included in said subset of said intersection identifying tuples;

d. applying zero or more filters determining inclusion based upon characteristics of cnxpts named in a valid intersection tuple to eliminate one or more intersection identifying tuples;

and

e. generating a multi-dimension data package from the mining extraction results in said intersection identifying tuples according to prepare export DataSet means.

188. The method of claim 186 to also provide for providing categorization services to customers, further comprising:

a. managing a commonplace for distributing information content extracted from, and by collecting information to be added to said commonplace to and from a user;

b. initiating execution of application software information management tools forming model layer framework structures and data structures for data set cataloging, tracking provenance, controlling access, and collecting voting on veracity of data added to said commonplace;

c. ingesting a source object of said plurality of source objects into said commonplace;

d. defining at least one source object provenance authority fxxt to identify in the catalog of said commonplace said source object;

e. ingesting a plurality of info-items into said commonplace from said source object;

f. ingesting a plurality of relationships into said commonplace from said source object;

g. initiating execution of the means for categorizing said commonplace by performing map generation, and prepare at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means wherein said organization of knowledge of at least one domain of wisdom includes said source object provenance authority fxxt and also includes any additional portion of said commonplace against which categorization or comparison or curation is to occur;

h. updating said data structures for source object access control;

i. updating said data structures for source object cataloging, tracking provenance, by controlling access, by collecting voting on veracity of data;

j. extracting a data set from said commonplace according to a fxxt specification, considering state of said data structures for data set cataloging, tracking provenance, controlling access, and collected voting on veracity of data;

k. presenting extracted data sets as subject matter for other processes;

and

l. processing commands for controlling user interface functions and performing automated tasks resulting from user actions.

189. The method of claim 1 to ensure consistency of re-imported data, further including:

a. calculating quality corrections according to prediction correction mechanism;

whereby imported data is cross checked by comparison of result maps.

190. The method of claim 1 to also provide export of extracted data sets, further including:

a. marking said data as a part of a data offering selected from the group of;

a data snippet according to mark data snippet as part of DD-DataSet, a packaged resultant-DataSet, a packaged TTX-DataSet, and a packaged Interest-DataSet;

according to purchase disaggregated data set subscription means;

b. providing default and data fault mechanisms for analytic, modeling, and prediction structures to ensure that users may obtain appropriate results even if said data is unavailable;

c. presenting extracted data sets as subject matter for other application software according to local or distributed processes means;

d. informing users of availability of said granular data when said analytic, model, or prediction attempts to access it, but cannot, allowing said user to purchase said access;

e. accepting purchases of subscriptions to said data offerings according to purchase disaggregated data set subscription means;

and

f. accounting for said information access transactions.

191. The method of claim 1 to obtain disaggregated data for subscription, sale, or licensing, further including:

a. accepting submissions of data for a characteristic of a txo info-item, the characteristic selected from the group of;

i. a property of the txo according to selling value of database means;

ii. a DD-DataSet according to create a ttx by offering data means;

iii. a packaged TTX-DataSet according to create a ttx by offering data means;

iv. a packaged resultant-DataSet according to create a ttx by offering data means;

v. an Interest-DataSet according to create a ttx by offering data means;

vi. an access right according to purchase of access right means;

vii. a registration right according to purchase of access right means;

viii. a methodology according to data commerce means;

ix. an analytic according to data commerce means;

x. a model according to data commerce means;

xi. an execution of a methodology according to data commerce means;

xii. an execution of an analytic according to data commerce means;

xiii. an execution of a model according to data commerce means;

xiv. a license according to purchase of access right means;

xv. a subscription according to purchase of access right means;

xvi. a common mental map system component according to purchase of access right means;

and

xvii. a viewing of a list of at least one dataset packages for a selected ttx element or category according to subscribe to dataset means;

b. marking said data as proprietary according to mark data as fee for use means;

c. providing default mechanism and data fault mechanism for analytic, modeling, and prediction structures to ensure that users may obtain appropriate results even if said information is unavailable;

d. controlling access to said granular data marked as fee for use to allow access only to those having purchased said subscription rights for access;

e. informing users of availability of said granular data when said analytic, model, or prediction attempts to access it, but cannot, allowing said user to purchase said access;

f. accepting purchases of subscriptions to said data offerings according to sell packaged DataSets and purchase disaggregated data set subscription means;

g. accounting for said information access and compensation transactions;

and

h. providing transaction based compensation to users providing information to said commonplace based upon the accessing of said information by other users;

whereby even very small quantities of very valuable data may be added to the commonplace to be sold when used in modeling, competitive intelligence, valuing an asset, planning projects, and other needs of one or more customers;

whereby disaggregated data may be submitted for sale or lease under consignment; and

whereby very valuable data obtained from well placed and trusted sources may be charged to many users who share in payment to allow profitability for the source.

192. The method of claim 1 to also provide user interest collection regarding each concept, further including:

a. collecting counts of unique and secondary views of ideas represented by cnxpts and categories of ideas, the categories represented by cntexxts, by a user according to navigation based relevance and interest collection means;

b. preparing interest statistics regarding user interest shown in an idea;

c. offering predictions about the future value of metrics regarding specific concepts;

d. offering for sale said interest information;

and

e. delivering said interest information;

wherein predictions of future value are based in part on said statistics taken regarding interest shown;

wherein data collected regarding what a user views during querying or navigation of said commonplace is made a business resource.

193. The method of claim 1, to perform operations to manage product strategy, product families, product features, product configuration, and product comparison, further including:

a. providing an organization of knowledge regarding organizations involved in products, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a product planning component for an entity;

b. accepting map definitions selected from the group of;

i. defining a product management map describing the product line as a breakout from management areas;

ii. defining a market management map describing the geography agnostic market segments as a breakout from management areas;

iii. defining a market management map describing the geography based market segments as a breakout from management areas;

and

iv. defining a market competition map describing the geography agnostic market segments as a breakout from competitors;

c. accepting product related knowledge and map definitions selected from the group of;

i. providing an organization of knowledge regarding product strategies, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a product strategy for an entity or a product line objective, including interfaces selected from the group of;

01. defining a product strategy map describing the components of the product strategy as a breakout from the product strategy;

and

02. defining a product strategy flow map describing the timing of solutions for specific applications of planned and existing products for specific market segments;

ii. providing an organization of knowledge regarding underlying technology for products, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a technology having zero or more features or a service having zero or more features, including interfaces selected from the group of;

01. defining a technology strategy map describing the components of the product line as a breakout from the areas of corporate technical expertise;

and

02. defining a technology strategy flow map describing the timing of incorporation of technologies for specific planned and existing products;

iii. providing an organization of knowledge regarding products, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a product family or a product having zero or more features, including interfaces selected from the group of;

01. defining a product features map describing the features breakout of each product;

and

02. providing a knowledge definition structure for differentiation between products represented by cnxpts, each such product to address an application of technology represented by an appcept, based upon fitness and effectiveness criteria regarding zero or more product features addressing an application requirement, for matching technologies represented by tcepts to appcepts and tcepts to products represented by cnxpts.

and

iv. providing an organization of knowledge regarding applications of technologies, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a market need for application of technologies to solve a problem, each said need having zero or more requirements for technology or services, including interfaces selected from the group of;

01. providing a knowledge definition structure for differentiation between applications of technologies represented by appcepts based upon requirement criteria;

02. defining a market strategy map describing the segments of markets defined as a breakout from the areas of the product line;

03. defining a market strategy flow map describing the timing of products addressing specific applications;

and

04. defining a market applications map describing the applications of technology defined as a breakout from the market segments, and the requirements for each application of technology;

d. providing product management tools selected from the group of;

i. providing knowledge-based configurations selected from the group of;

01. determining market segments by requirements;

02. determining inter-company and intra-company product line comparators;

and

03. determining market sizes by market segment;

ii. providing specific commonalities machine learning analytics for determining similarities between cnxpts and commonalities based on the matching of a property of one type of cnxpt to a property of another type, the analytics selected from the group of;

01. for indicating commonalities and variabilities between concepts represented by cnxpts;

02. for indicating commonalities and variabilities between products represented by cnxpts;

03. for indicating commonalities and variabilities between technologies represented by cnxpts;

and

04. for indicating commonalities and variabilities between cnxpts representing technologies used in products and product lines for comparison of existing products by technologies used or not used in the implemented product or product line;

iii. specifying staff work packages for information gathering actions, the work packages selected from the group of;

01. accepting votes into maps regarding modeling information of a type selected from the group of;

development stage of product, completion status, value of market, size of market, investment availability, opportunity window, critical time constraints, competitive constraints, cost of capital, source of capital, priority of development, cost of customer acquisition, cross-effect of development on other strategy elements, cross-effect and competitive effects of products at market, product bundling, externalities of products, market sizes, what-if and probabilistic estimations, constraints, assumptions, decisions made, decisions needed, issues and impacts, analysis patterns to be applied, sensitivity constraints, outcomes, alternative strategies, alternative scenarios for development or market approach, and differentiated treatment for analysis of products;

02. accepting votes into maps regarding competitive products, competitive technologies, adjunct market opportunities, linkage between a product and technologies for the product, relationships between requirements and technology advantages, relationships between requirements and product advantages, relationships between requirements and other requirements, relationships between technology and technology alternatives, timing of technology availabilities, resource requirements and relationships between resource and technology, competitor strategies, competitor activities, assets of competitor related to strategy, and competitor product plan timing;

03. accepting refinement, by votes into maps, of modeling information and relationships regarding product roadmaps;

04. accepting descriptive information about product and market issues and solution strategies;

05. accepting descriptive information regarding appcept constraints and requirements including form factors, interfacing, quality determinations, customer behavior patterns, required performance envelopes and quality, product behavior accommodation features, and applicable regulations and standards;

06. comparing product features across products, product lines, time frames, strategies, divisions, and competitive entities;

and

07. generating zero or more surveys for obtaining specific information for analyzing product feature acceptance and user requirements;

iv. specifying analysis work packages for planning studies and management actions, the work packages selected from the group of;

01. accepting ideation;

02. accepting product issue modeling information for internal and competitor development and marketing efforts;

03. accepting planning oriented votes showing implementation and evolution of products and product lines where relationship votes indicate product feature changes made to address appcept specific requirements;

04. accepting planning oriented votes showing implementation and evolution of products and product lines where relationship votes changes in product line where feature changes cause altered product concepts and application of different tcepts;

05. accepting votes stating changes to organization of tcepts by managing component;

06. accepting votes stating changes to organization of product strategy element by managing component;

07. accepting votes stating changes to development phasing of products;

08. accepting product road map;

and

09. accepting product production plans;

e. executing continuous processing;

f. executing analytics;

g. generating defined maps;

h. performing modeling calculations to report product, company, and competitor posture against evaluation criteria for competitive strength and weakness determination;

i. calculating value changes and impact for what-if analysis of product candidates;

j. providing data sets for analytic use and reporting regarding products;

and

k. generating comparative reports based upon methodologies to assist product line managers, competitive analysts, management, and investors.

194. The method of claim 1 to also provide the ability to find a classification for an idea not well defined, the method further comprising:

a. defining a map to be organized by semantic classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. displaying the map on a first portion of the display screen, the plurality of cntexxts of the map as a network display;

d. displaying simultaneously sub-contexts of at least one context in the subset of the plurality of contexts;

e. creating a goal, stating zero or more properties of said goal, the goal representing the concept the user has in their mind or is forming, ideating, or conjuring;

f. accepting one or more user commands causing the goal to be classified into a different context identified by a cntexxt, the intent of the move being to narrow the set of contexts where said user might find the concept being conjured, the movement of the goal caused by a method selected from the group of;

i. executing a search query of said goal, the query defined or redefined by the user, the query causing movement of said goal to the cntexxt closest matching to the query results of the goal query;

and

ii. navigating to traverse the goal to a next cntexxt;

g. accepting a user command indicating that the concept being conjured and represented by the goal should be within the context moved to, the meaning of the user command a response to the status of the idea in the context, the command selected from the group of;

i. as the concept is not in the located context but should be, wherein;

01. finalizing said goal by converting said goal to a cnxpt with the same properties;

02. associating said cnxpt hierarchically to the context by a hierarchical association, said cnxpt a differentiable offshoot of the context;

03. accepting a command to stake a claim for the idea the user identified, reified from the goal, and allowed to concretize;

and

04. generating, if said search goal has a result set other than of cnxpts, occurrence relationships between said cnxpt and each relevant result set item information txo or irxt found;

and

ii. as the concept is in the located context represented by a cnxpt, abandon the goal, allowing the user to set properties of the found cnxpt according to those on the goal if not conflicting with existing properties in the found cnxpt;

whereby the user is given an ability to locate a context best suited to holding an idea;

whereby rather than a decision tree classification the user is given the option of extending decision tree branches by locating an appropriate parent and then creating a new leaf;

whereby the new cnxpt can fill white space of the parent;

whereby the user is given the option to set properties of the new idea that differentiate it from the context and siblings within the context although the user may be reticent to expose the idea; and

whereby the differentiation may be by timeframe where the new cnxpt should be the parent rather than the child.

195. The method of claim 1 to relate instances of an in-common info-item type having no significant differential in meaning in a specific use case, wherein:

a. defining a map to be organized by semantic classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. integrating closeness of semantic meaning of a concept represented by a second cnxpt instance to a concept represented by a first cnxpt instance already situated in a categorization by semantic meanings, comprising;

i. accepting a choice of a metric between zero and one to be used as a threshold for combining cnxpts wherein when the threshold value is surpassed by the effective weight of a summary association info-item to be used as a determinant of entity similarity the endpoint cnxpts be considered to be representing the same entity, the summary selected from the group of;

ii. summarizing by a count the associations of one or more stated types between said first cnxpt and said second cnxpt;

iii. summarizing by a count the associations between said first cnxpt and said second cnxpt, each association marked by a default or one or more fxxts matching a parameter;

iv. summarizing weights of associations of one or more stated types between said first cnxpt and said second cnxpt;

v. summarizing weights of associations between said first cnxpt and said second cnxpt, each association marked by a default or one or more stated fxxts matching a parameter;

vi. summarizing, as a coefficient specified for the association type times the value given by a weight attribute of the association or default value, the associations between said first cnxpt and said second cnxpt, each association marked by a default or one or more stated fxxts matching a parameter according to utilize collective consensus through vote tallying means;

vii. summarizing, as a coefficient specified for the matching fxxt times the value given by a weight attribute of the association or default value, the associations between said first cnxpt and said second cnxpt, each association marked by a default or one or more stated fxxts matching a parameter according to utilize collective consensus through vote tallying means;

and

viii. determining effective weights for summary associations between cnxpts summarizing all associations to be used as a determinant of entity similarity between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means.

196. The method of claim 1, to position a first set of cnxpt instances of a first forest into a first precedence graph map orientation with respect to a second set of cnxpt instances of a second forest into a second categorization hierarchical map orientation where at least one third member cnxpt of said first set of cnxpt instances is also a member of said second set of cnxpt instances, each third member cnxpt termed an intersecting cnxpt, further comprising:

a. defining a map to be organized by semantic classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. accepting a choice of slice level to establish a plane across said second forest for slicing said second categorization hierarchical map orientation selected from the group of;

i. no slice selected to slice at the level of the highest root of said second categorization hierarchical map;

ii. slice level selected as stated by a value translatable to an integer indicating the depth of a hierarchy level in the context of said second categorization hierarchical map, such integer is interpreted as a depth from the highest root of said second categorization hierarchical map to slice at the level in the hierarchy given by said depth from the highest root of said second categorization hierarchical map;

and

iii. slice level selected for an intersecting cnxpt as stated a value translatable to an integer indicating the depth of a hierarchy level in the context of said second categorization hierarchical map, such integer interpreted as a depth from the intersecting cnxpt as the root of a subtree in said second categorization hierarchical map to establish a plane across said subtree rooted at the intersecting cnxpt in said second forest by level of hierarchy from the intersecting cnxpt;

d. accepting a choice of slice level to establish a plane across said first forest for slicing said first forest of said first precedence graph map orientation selected from the group of;

i. no slice selected to establish a plane across said first forest at the level of the earliest antecedent of said first forest of said first precedence graph map orientation;

ii. slice level selected as stated by a value translatable to an integer indicating, in the context of said first forest, the distance from the earliest antecedent as a precedence graph depth from the earliest antecedent of said first forest of said first precedence graph map orientation to establish a plane across said first forest at the level in the precedence graph given by said depth;

and

iii. slice level selected as stated by a value type selected from the group of;

a state of completion of a task, a state of completion of an event, a state of completion of a proof, a date, a purlieu, a location, a status, a planning horizon, an indication of a horizon with the domain of wisdom, a border between an a priori and an a posteriori event shown in said first forest, a testing point, a branch point, a time marker, a checkpoint, a serialization point, a commitment point, a dependency point, a claim in a claim tree, a split point defined by a user suitable in a specific domain of wisdom, and a value translatable to a distance from the earliest antecedent;

the value a precedence graph depth from the earliest antecedent of said first forest of said first precedence graph map orientation;

e. deriving, for initial positioning only, a position of a root cnxpt in an extracted forest of extracted trees of cnxpts based on relationships of the root cnxpt with other root cnxpts;

f. determining a position for cnxpts at or above the hierarchical forest depth to place the parent of cnxpts having ancestors in the hierarchical map and all siblings of said parent to correspond with said precedence graph map orientation;

and

g. determining positions and visibility of the remaining cnxpts in each orientation.

197. The method of claim 1 to also provide multiple representations of relationship structuring, further including:

a. defining a map to be organized from directed associations, wherein similar concepts are in closer proximity than dissimilar concepts;

b. creating at least one hierarchical association stating existence of a relationship between a parent info-item and a child info-item and setting positioning and sizing to connote the relative logical relationship in a map according to said map generation means, the relationship selected from the group of;

i. a first cnxpt instance marked as parent and a second cnxpt instance to indicate a type selected from the group of;

01. the first cnxpt instance as a category and the second cnxpt instance to represent a member of the category in a presentation substantially of the nature of a categorization;

02. the first cnxpt instance as a predecessor and the second cnxpt instance to represent a successor to the first cnxpt instance as representing a predecessor in a presentation substantially of the nature of a graphical network or directed graph or precedence model;

03. the first cnxpt instance as an independent event and the second cnxpt instance to represent a dependent event of the first cnxpt instance as representing an independent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation;

04. the first cnxpt instance as a dependent event and the second cnxpt instance to represent a dependent event of the first cnxpt instance as representing a dependent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation;

05. the first cnxpt instance as a predecessor task and the second cnxpt instance to represent a successor or dependent task in a presentation substantially of the nature of a project model presentation;

06. the first cnxpt instance as an independent claim and the second cnxpt instance to represent a dependent claim of the independent claim in a presentation substantially of the nature of a claim tree presentation;

07. the first cnxpt instance as a dependent claim and the second cnxpt instance to represent a dependent claim of the dependent claim in a presentation substantially of the nature of a claim tree presentation;

08. the first cnxpt instance as an authority or opinion or theory of the case or issue or doctrine or statute or law and the second cnxpt instance to represent a document or statement relying on the concept represented by the first cnxpt instance in a presentation substantially of the nature of a legal analysis;

09. the first cnxpt instance as a technology and the second cnxpt instance to represent a technology derived from the concept represented by the first cnxpt instance in a presentation substantially of the nature of a technological progression;

10. the first cnxpt instance as an application of technology and the second cnxpt instance to represent an application of technology derived from the concept represented by the first cnxpt instance in a presentation substantially of the nature of a technology requirement progression;

11. the first cnxpt instance as an assembly and the second cnxpt instance to represent a part used in the assembly in a presentation substantially of the nature of a parts breakdown or assembly diagram;

and

12. the first cnxpt instance as a logical or mathematical equation and the second cnxpt instance to represent a component of the equation in a presentation substantially of the nature of a derivation presentation;

ii. a third cnxpt instance marked as parent and a fourth cnxpt class to indicate a type selected from the group of;

01. the third cnxpt instance as a category and the fourth cnxpt class to represent a member of the category in a presentation substantially of the nature of a categorization,

02. the third cnxpt instance as a category and the fourth cnxpt class to represent a class of members of the category in a presentation substantially of the nature of a categorization,

03. the third cnxpt instance as a predecessor and the fourth cnxpt class to represent a successor to the third cnxpt instance as representing a predecessor in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

04. the third cnxpt instance as a predecessor and the fourth cnxpt class to represent a class of successors to the third cnxpt instance as representing a predecessor in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

05. the third cnxpt instance as an independent event and the fourth cnxpt class to represent a dependent event of the third cnxpt instance as representing an independent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

06. the third cnxpt instance as an independent event and the fourth cnxpt class to represent a class of dependent events of the third cnxpt instance as representing an independent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

07. the third cnxpt instance as a dependent event and the fourth cnxpt class to represent a dependent event of the third cnxpt instance as representing a dependent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

08. the third cnxpt instance as a dependent event and the fourth cnxpt class to represent a class of dependent events of the third cnxpt instance as representing a dependent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

09. the third cnxpt instance as a predecessor task and the fourth cnxpt class to represent a successor or dependent task in a presentation substantially of the nature of a project model presentation,

10. the third cnxpt instance as a predecessor task and the fourth cnxpt class to represent a class of successor or dependent tasks in a presentation substantially of the nature of a proj ect model presentation,

11. the third cnxpt instance as an independent claim and the fourth cnxpt class to represent a dependent claim of the independent claim represented by the third cnxpt instance in a presentation substantially of the nature of a claim tree presentation,

12. the third cnxpt instance as an independent claim and the fourth cnxpt class to represent a class of dependent claims of the independent claim represented by the third cnxpt instance in a presentation substantially of the nature of a claim tree presentation,

13. the third cnxpt instance as a dependent claim and the fourth cnxpt class to represent a dependent claim of the dependent claim represented by the third cnxpt instance in a presentation substantially of the nature of a claim tree presentation,

14. the third cnxpt instance as a dependent claim and the fourth cnxpt class to represent a class of dependent claims of the dependent claim represented by the third cnxpt instance in a presentation substantially of the nature of a claim tree presentation,

15. the third cnxpt instance as an authority or opinion or theory of the case or issue or doctrine or statute or law and the fourth cnxpt class to represent a document or statement relying on the concept represented by the third cnxpt instance in a presentation substantially of the nature of a legal analysis,

16. the third cnxpt instance as an authority or opinion or theory of the case or issue or doctrine or statute or law and the fourth cnxpt class to represent a class of documents or statements relying on the concept represented by the third cnxpt instance in a presentation substantially of the nature of a legal analysis,

17. the third cnxpt instance as a technology and the fourth cnxpt class to represent a technology derived from the concept represented by the third cnxpt instance in a presentation substantially of the nature of a technological progression,

18. the third cnxpt instance as a technology and the fourth cnxpt class to represent a class of technologies derived from the concept represented by the third cnxpt instance in a presentation substantially of the nature of a technological progression,

19. the third cnxpt instance as an application of technology and the fourth cnxpt class to represent a technology derived from the concept represented by the third cnxpt instance in a presentation substantially of the nature of a technology requirement progression,

20. the third cnxpt instance as an application of technology and the fourth cnxpt class to represent a class of applications of technology derived from the concept represented by the third cnxpt instance in a presentation substantially of the nature of a technology requirement progression,

21. the third cnxpt instance as an assembly and the fourth cnxpt class to represent a part used in the assembly in a presentation substantially of the nature of a parts breakdown or assembly diagram,

22. the third cnxpt instance as an assembly and the fourth cnxpt class to represent a class of parts used in the assembly in a presentation substantially of the nature of a parts breakdown or assembly diagram,

23. the third cnxpt instance as a logical or mathematical equation and the fourth cnxpt class to represent a component of the equation in a presentation substantially of the nature of a derivation presentation,

24. the third cnxpt instance as a logical or mathematical equation and the fourth cnxpt class to represent a class of components of the equation in a presentation substantially of the nature of a derivation presentation,

25. the third cnxpt instance as a category and the fourth cnxpt class to represent a member of the category in a presentation substantially of the nature of a class-obj ect presentation, and

26. the third cnxpt instance as a category and the fourth cnxpt class to represent a class of members of the category in a presentation substantially of the nature of a class-object presentation;

iii. a fifth cnxpt class marked as parent and a sixth cnxpt instance to indicate a type;

01. the fifth cnxpt class as a category and the sixth cnxpt instance to represent a member of the category in a presentation substantially of the nature of a categorization,

02. the fifth cnxpt class as a set of categories each a member of the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a category instance member of the class of the fifth cnxpt class also in the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a categorization,

03. the fifth cnxpt class as a predecessor and the sixth cnxpt instance to represent a successor to the fifth cnxpt class as representing a predecessor in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

04. the fifth cnxpt class as a set of predecessors each a successor to the predecessor represented by the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a predecessor member of the class of the fifth cnxpt class and a successor to the predecessor if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

05. the fifth cnxpt class as an independent event and the sixth cnxpt instance to represent a dependent event of the fifth cnxpt class as representing an independent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

06. the fifth cnxpt class as a set of independent events each within the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an independent event member of the class of the fifth cnxpt class and a dependent event within which the fifth cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

07. the fifth cnxpt class as a dependent event and the sixth cnxpt instance to represent a dependent event of the fifth cnxpt class as representing a dependent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

08. the fifth cnxpt class as a set of dependent events each a dependent event in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an independent event member of the class of the fifth cnxpt class and a dependent event within which the fifth cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

09. the fifth cnxpt class as a predecessor task and the sixth cnxpt instance to represent a successor or dependent task in a presentation substantially of the nature of a project model presentation,

10. the fifth cnxpt class as a set of predecessor tasks each a successor to the predecessor represented by the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a predecessor task member of the class of the fifth cnxpt class and a successor task to any predecessor task represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a project model presentation,

11. the fifth cnxpt class as an independent claim and the sixth cnxpt instance to represent a dependent claim of the independent claim represented by the fifth cnxpt class in a presentation substantially of the nature of a claim tree presentation,

12. the fifth cnxpt class as a set of independent claims each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an independent claim member of the class of the fifth cnxpt class and an independent claim in the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

13. the fifth cnxpt class as a dependent claim and the sixth cnxpt instance to represent a class of dependent claims of the dependent claim in a presentation substantially of the nature of a claim tree presentation,

14. the fifth cnxpt class as a set of dependent claims each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a dependent claim member of the class of the fifth cnxpt class and a dependent claim in the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

15. the fifth cnxpt class as an authority or opinion or theory of the case or issue or doctrine or statute or law and the sixth cnxpt instance to represent a document or statement relying on the concept represented by the fifth cnxpt class in a presentation substantially of the nature of a legal analysis,

16. the fifth cnxpt class as a set of authorities or opinions or theories of the case or issues or doctrines or statutes or laws each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a conceptual member of the class of the fifth cnxpt class and a similar typed concept relying upon the authority and within the category represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a legal analysis,

17. the fifth cnxpt class as a technology and the sixth cnxpt instance to represent a technology derived from the concept represented by the fifth cnxpt class in a presentation substantially of the nature of a technological progression,

18. the fifth cnxpt class as a set of technologies each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a technology member of the class of the fifth cnxpt class and an offshoot of the technology if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a technological progression,

19. the fifth cnxpt class as an application of technology and the sixth cnxpt instance to represent an application of technology derived from the concept represented by the fifth cnxpt class in a presentation substantially of the nature of a technology requirement progression,

20. the fifth cnxpt class as a set of applications of technology each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an application of technology member of the class of the fifth cnxpt class and an offshoot of the application of technology if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a technology requirement progression,

21. the fifth cnxpt class as an assembly and the sixth cnxpt instance to represent a part used in the assembly in a presentation substantially of the nature of a parts breakdown or assembly diagram,

22. the fifth cnxpt class as a set of assemblies each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an assembly member of the class of the fifth cnxpt class and an assembly to the larger assembly if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a parts breakdown or assembly diagram,

23. the fifth cnxpt class as a logical or mathematical equation and the sixth cnxpt instance to represent a component of the equation in a presentation substantially of the nature of a derivation presentation,

24. the fifth cnxpt class as a set of logical or mathematical equations each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent an equation member of the class of the fifth cnxpt class and a portion of the equation if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a derivation presentation,

25. the fifth cnxpt class as a category and the sixth cnxpt instance to represent a member of the category in a presentation substantially of the nature of a class-object presentation,

and

26. the fifth cnxpt class as a set of types each in the context within which the fifth cnxpt class is located and the sixth cnxpt instance to represent a type member of the class of the fifth cnxpt class and a sub-type to the type if any represented by the context within which the fifth cnxpt class is located in a presentation substantially of the nature of a class-object presentation;

and

iv. the seventh cnxpt class marked as parent and the eighth cnxpt class to indicate a type selected from the group of;

01. the seventh cnxpt class as parent to indicate a class and the eighth cnxpt class to represent a sub-class in a segment of a presentation the segment substantially of the nature of a class-object presentation,

02. the seventh cnxpt class as a category and the eighth cnxpt class to represent a member of the category in a presentation substantially of the nature of a categorization,

03. the seventh cnxpt class as a set of categories each a member of the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a category member as instance of the class of the seventh cnxpt class also in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a categorization,

04. the seventh cnxpt class as a set of categories each a member of the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a category sub-class of the class of the seventh cnxpt class also in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a categorization,

05. the seventh cnxpt class as parent to indicate a class that may be considered a category and the eighth cnxpt class to represent a member of the category in a presentation substantially of the nature of a class-obj ect presentation,

06. the seventh cnxpt class as parent to indicate a class as well as a category and the eighth cnxpt class to represent a sub-class and the seventh cnxpt class to represent a member of the category in a segment of a categorization presentation the segment substantially of the nature of a class-object presentation,

07. the seventh cnxpt class as a predecessor and the eighth cnxpt class to represent a successor to the seventh cnxpt class as representing a predecessor in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

08. the seventh cnxpt class as a set of predecessors each a successor to the predecessor represented by the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a predecessor member of the class of the seventh cnxpt class and a successor to the predecessor if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

09. the seventh cnxpt class as a set of predecessors each a successor to the predecessor represented by the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a successor to the predecessor if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a graphical network or directed graph or precedence model,

10. the seventh cnxpt class as a class and the eighth cnxpt class to represent a member of the class of the seventh cnxpt class as representing a predecessor in a presentation substantially of the nature of a class-object presentation,

11. the seventh cnxpt class as parent to indicate a class as well as a predecessor and the eighth cnxpt class to represent a sub-class of the predecessor and the seventh cnxpt class to represent a successor of the predecessor seventh cnxpt class in a segment of a graphical network or precedence presentation the segment substantially of the nature of a class-object presentation,

12. the seventh cnxpt class as an independent event and the eighth cnxpt class to represent a dependent event of the seventh cnxpt class as representing an independent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

13. the seventh cnxpt class as a set of independent events each within the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an independent event member of the class of the seventh cnxpt class and a dependent event within which the seventh cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

14. the seventh cnxpt class as a set of independent events each within the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a dependent event within which the seventh cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

15. the seventh cnxpt class as parent to indicate a class as well as an independent event node and the eighth cnxpt class to represent a sub-class and the seventh cnxpt class to represent a dependent event node in a segment of a dependence or conditionality presentation the segment substantially of the nature of a class-object presentation,

16. the seventh cnxpt class as a dependent event and the eighth cnxpt class to represent a dependent event of the seventh cnxpt class as representing a dependent event in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

17. the seventh cnxpt class as a set of dependent events each a dependent event in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an independent event member of the class of the seventh cnxpt class and a dependent event within which the seventh cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

18. the seventh cnxpt class as a set of dependent events each a dependent event in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a dependent event within which the seventh cnxpt class is located in a presentation substantially of the nature of a dependency model or decision tree or conditionality presentation,

19. the seventh cnxpt class as parent to indicate a class as well as a dependent event node and the eighth cnxpt class to represent a sub-class and the seventh cnxpt class to represent a dependent event node in a segment of a dependence or conditionality presentation the segment substantially of the nature of a class-object presentation,

20. the seventh cnxpt class as a predecessor task and the eighth cnxpt class to represent a successor or dependent task in a presentation substantially of the nature of a project model presentation,

21. the seventh cnxpt class as a set of predecessor tasks each a successor to the predecessor represented by the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a predecessor task member of the class of the seventh cnxpt class and a successor task to any predecessor task represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a project model presentation,

22. the seventh cnxpt class as a set of predecessor tasks each a successor to the predecessor represented by the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a successor task to any predecessor task represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a project model presentation,

23. the seventh cnxpt class as an independent claim and the eighth cnxpt class to represent a dependent claim of the independent claim represented by the seventh cnxpt class in a presentation substantially of the nature of a claim tree presentation,

24. the seventh cnxpt class as a set of independent claims each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an independent claim member of the class of the seventh cnxpt class and an independent claim in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

25. the seventh cnxpt class as a set of independent claims each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and an independent claim in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

26. the seventh cnxpt class as a dependent claim and the eighth cnxpt class to represent a class of dependent claims of the dependent claim in a presentation substantially of the nature of a claim tree presentation,

27. the seventh cnxpt class as a set of dependent claims each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a dependent claim member of the class of the seventh cnxpt class and a dependent claim in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

28. the seventh cnxpt class as a set of dependent claims each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a dependent claim in the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a claim tree presentation,

29. the seventh cnxpt class as a claim preamble and the eighth cnxpt class to represent an integer of the claim of the dependent claim in a presentation substantially of the nature of a claim tree presentation,

30. the seventh cnxpt class as a Markush clause of an integer of a claim and the eighth cnxpt class to represent a sub-integer of the Markush clause of the claim in a presentation substantially of the nature of a claim tree presentation,

31. the seventh cnxpt class as an authority or opinion or theory of the case or issue or doctrine or statute or law and the eighth cnxpt class to represent a document or statement relying on the concept represented by the seventh cnxpt class in a presentation substantially of the nature of a legal analysis,

32. the seventh cnxpt class as a set of authorities or opinions or theories of the case or issues or doctrines or statutes or laws each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a conceptual member of the class of the seventh cnxpt class and a similar typed concept relying upon the authority and within the category represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a legal analysis,

33. the seventh cnxpt class as a set of authorities or opinions or theories of the case or issues or doctrines or statutes or laws each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a similar typed concept relying upon the authority and within the category represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a legal analysis,

34. the seventh cnxpt class as a statute or law and the eighth cnxpt class to represent an element of the statute or law in a presentation substantially of the nature of a legal analysis,

35. the seventh cnxpt class as a technology and the eighth cnxpt class to represent a technology derived from the concept represented by the seventh cnxpt class in a presentation substantially of the nature of a technological progression,

36. the seventh cnxpt class as a set of technologies each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a technology member of the class of the seventh cnxpt class and an offshoot of the technology if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a technological progression,

37. the seventh cnxpt class as a set of technologies each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and an offshoot of the technology if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a technological progression,

38. the seventh cnxpt class as an application of technology and the eighth cnxpt class to represent an application of technology derived from the concept represented by the seventh cnxpt class in a presentation substantially of the nature of a technology requirement progression,

39. the seventh cnxpt class as a set of applications of technology each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an application of technology member of the class of the seventh cnxpt class and an offshoot of the application of technology if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a technology requirement progression,

40. the seventh cnxpt class as a set of applications of technology each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and an offshoot of the application of technology if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a technology requirement progression,

41. the seventh cnxpt class as an assembly and the eighth cnxpt class to represent a part used in the assembly in a presentation substantially of the nature of a parts breakdown or assembly diagram,

42. the seventh cnxpt class as a set of assemblies each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an assembly member of the class of the seventh cnxpt class and an assembly to the larger assembly if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a parts breakdown or assembly diagram,

43. the seventh cnxpt class as a set of assemblies each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and an assembly to the larger assembly if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a parts breakdown or assembly diagram,

44. the seventh cnxpt class as a logical or mathematical equation and the eighth cnxpt class to represent a component of the equation in a presentation substantially of the nature of a derivation presentation,

45. the seventh cnxpt class as a set of logical or mathematical equations each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent an equation member of the class of the seventh cnxpt class and a portion of the equation if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a derivation presentation,

46. the seventh cnxpt class as a set of logical or mathematical equations each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a portion of the equation if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a derivation presentation,

47. the seventh cnxpt class as a category and the eighth cnxpt class to represent a member of the category in a presentation substantially of the nature of a class-object presentation,

48. the seventh cnxpt class as a set of types each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a type member of the class of the seventh cnxpt class and a sub-type to the type if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a class-object presentation, and

49. the seventh cnxpt class as a set of types each in the context within which the seventh cnxpt class is located and the eighth cnxpt class to represent a sub-class of the class of the seventh cnxpt class and a sub-type to the type if any represented by the context within which the seventh cnxpt class is located in a presentation substantially of the nature of a class-object presentation;

c. accepting navigation in a visualization of said map based upon the presence of a hierarchical association stating belief that a relationship between a parent info-item and a child info-item exists;

and

d. providing said information relevant to a cnxpt as a member of a category through said cnxpt.

198. The method of claim 1, to position cnxpts on a map visualization being generated, further comprising:

a. deriving a position of an initial cnxpt without children in an extracted structuring of cnxpts based on associations of the initial cnxpt with other cnxpts without children;

b. deriving a position of a parent cnxpt in an extracted structuring of cnxpts based on associations of the parent cnxpt with cnxpts selected from the group of;

child cnxpt of the parent cnxpt, a nephew cnxpt of the parent cnxpt, and a sibling cnxpt of the parent cnxpt;

and

c. modifying the organization of knowledge of the map based on the positioning of the cnxpt.

199. The method of claim 1 to also provide for discussion specific to a narrow context within a commonplace of information, further comprising:

a. receiving a user command to request a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt;

b. forming a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt in one or more phases selected from the group of;

i. connection opportunity offered;

ii. connection requested;

iii. connection requested for survey completion, with optional compensation;

iv. connection fee, if any, being negotiated;

v. connection fee, if any, paid;

vi. connection offered and accepted;

vii. connection scheduled;

viii. connection in progress;

ix. connection in progress with content tracking in effect;

x. connection in progress with content tracking off;

xi. connection in progress and related to contract negotiation with content tracking in effect;

xii. connection in progress and related to contract negotiation with content tracking off;

xiii. connection in progress and being timed with content tracking in effect;

xiv. connection in progress and being timed with content tracking off;

xv. connection for tracked deliverable delivery;

xvi. connection for tracked deliverable acceptance negotiation;

xvii. connection time exhausted;

xviii. connection completed;

xix. connection content delivered;

and

xx. connection content retained;

and

c. accepting and processing communications related to the connection.

200. The method of claim 1 to also provide a marketplace for data related to specific concepts and sale of disaggregated data, further including:

a. accepting submissions of granular data for a property of a txo info-item according to selling value of database means;

b. marking said data as proprietary according to mark data as fee for use means;

c. marking said data as a part of a data offering according to mark data snippet as part of DD-DataSet means;

d. providing default mechanism and data fault mechanism for analytic, modeling, and prediction structures to ensure that users may obtain results even if said property information is attached to only some txo instances of the same type and so that said user has a proper understanding of the basis where data is unavailable;

e. controlling access to said granular data marked as fee for use to allow access only to those having purchased said subscription rights for access;

f. providing transaction based compensation to users providing information to said commonplace based upon the accessing of said information by other users;

g. accounting for said compensation transactions;

h. informing users of availability of said granular data when said analytic, model, or prediction attempts to access it, but cannot, allowing said user to purchase said access;

i. accepting purchases of subscriptions to said data offerings according to sell packaged TTX-DataSets and purchase disaggregated data set subscription means;

and

j. accounting for said information access transactions.

201. The method of claim 1 to also provide adding a new technology innovation including staking a claim to the intellectual property, further including:

a. defining a map to be organized by technology classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. accepting the addition of a new technology innovation idea represented by a differentiated cnxpt within the context of an existing prior technology innovation idea as narrowing the scope of the enclosing idea;

and

d. accepting a user request selected from the group of;

i. to stake a claim on said new technology innovation idea by stating ownership;

ii. to add provenance information on said differentiated cnxpt;

iii. to withhold release of said differentiated cnxpt existence information;

iv. to withhold release of said differentiated cnxpt descriptive information;

v. to add further description of said new technology innovation idea represented by said differentiated cnxpt;

vi. to publish said new technology innovation idea wherein other users may retrieve information about said new technology innovation idea or view it in context;

vii. to offer said new technology innovation idea for sale;

viii. to offer said new technology innovation idea for collaborative development;

ix. to offer said new technology innovation idea for investment;

x. to seek intellectual property protection on said new technology innovation idea;

xi. to retain negotiation information and status regarding any offer pertaining to said new technology innovation idea;

xii. to retain development plans and status information regarding any efforts pertaining to said new technology innovation idea;

xiii. to constrain access to information pertaining to said new technology innovation idea;

xiv. to constrain access to particular portions of information pertaining to said new technology innovation idea;

xv. to track user interest as shown by retrieving information pertaining to said new technology innovation idea;

xvi. to accept votes regarding characterization of said new technology innovation idea;

xvii. to accept offers regarding said new technology innovation idea;

xviii. to accept information regarding said new technology innovation idea and adding said information to said differentiated cnxpt as a vote regarding said differentiated cnxpt or associated relationships, information resources or internal resources serving as information resources, or traits;

xix. to add modeling equations regarding said differentiated cnxpt;

xx. to provide or constrain access to personal information related to said new technology innovation idea'"'"'s originator;

xxi. to accept categorization requests from a second user situating said differentiated cnxpt as pertinent to a category of said second user'"'"'s choice as represented placement of said differentiated cnxpt within the context of the category as represented by a fourth cnxpt;

and

xxii. accepting categorization requests from a second user situating said differentiated cnxpt as pertinent to a category of said second user'"'"'s choice.

202. The method of claim 1 to also provide establishing control over owned intellectual property, further comprising:

a. providing a value creation structure comprises specifying a right of some nature to one or more cnxpts, the nature selected from the group of;

i. the right of control over changes to a cnxpt;

ii. the right of control over placement changes to a cnxpt;

iii. the right to add a new cnxpt as a derivative or child of the cnxpt in any perspective;

iv. the right to add a new cnxpt as a derivative or child of the cnxpt in a specified perspective;

v. the right to read information regarding a cnxpt;

vi. the right to utilize a method of a cnxpt;

vii. the right to utilize a property of a cnxpt;

viii. the right to originate communications regarding the cnxpt representing any concept;

ix. the right to originate ownership change transactions regarding the cnxpt representing any concept;

x. the right to originate transactions regarding the cnxpt representing any concept;

xi. the right to control release of the existence of the cnxpt representing an idea;

xii. the right to control release of the existence of the cnxpt representing an idea to only those others later stating a similar idea;

xiii. the right to assign a right to the cnxpt;

xiv. the right to create a right for the cnxpt and specify the authorities and access rights of the created right;

xv. the right of ownership of the concept represented by the cnxpt;

and

xvi. the right to control release of information regarding the concept represented by the cnxpt;

b. providing a transaction based facility to track actions and to convey information regarding a valuable cnxpt, further including;

i. generating ownership rights for a first cnxpt;

ii. generating a transaction stream identity to identify a transaction stream related to the first cnxpt and authorized by ownership right granted to a first user requesting the transaction stream wherein the stream may effect communication or logging;

iii. authorizing a second user origination rights for transactions based upon ownership rights granted for the second user for the cnxpt;

iv. adding information regarding the transaction to the first transaction into the transactional data structure;

v. encapsulating for each ownership right and originating second user appropriate origination data related to the ownership right and second user and the corresponding cnxpt identity within any transactional data structure placed into the transactional stream;

and

vi. distributing the transactional data structure through the transaction stream;

and

c. providing for ownership changes regarding a cnxpt by transaction;

further including;

i. detecting a second transaction that involves a change in ownership over the first cnxpt affecting a third user and a fourth user where the fourth user may substantially be a new and ill-defined party given an identity as if a user;

ii. altering as required access and transactional rights to said third user for accessing or controlling said first cnxpt and for origination transactions appropriate to the change in ownership and according to the ownership rights authorized by said second user with respect to the cnxpt and the transaction stream holding the first transaction;

and

iii. granting as required access and transactional rights to said fourth user for accessing or controlling said first cnxpt and for origination transactions appropriate to the change in ownership and according to the ownership rights authorized by said second user with respect to the cnxpt and the transaction stream holding the first transaction.

203. The method of claim 202 to also provide for registration of ownership rights, further comprising:

a. providing a value creation structure comprises a right to a cnxpt created within a cntexxt by;

i. generating ownership rights for the cnxpt within the cntexxt;

ii. encapsulating, for each ownership right, origination data related to the ownership right and the corresponding cnxpt within a transactional data structure;

iii. detecting a first transaction that involves a change in ownership over a cnxpt with respect to cntexxt;

iv. adding first transaction data related to the first transaction in the transactional data structure;

v. distributing the transactional data structure;

and

vi. granting access to a user of the cnxpt only according to the then-current ownership right with respect to cntexxt;

whereby ownership for specific use or application is delineated according to a cntexxt of a structuring of knowledge.

204. The method of claim 1 to identify conceptual differentiations, further including:

a. accepting zero or more indications of how said concretized conjuring represented by said third cnxpt is differentiable from said first concept represented by said first cntexxt represented internally by said first cnxpt;

i. accepting at least one indication of how said concept being conjured by said user is differentiable from said first concept represented by said cntexxt, the indication selected from the group of;

01. a textual entry;

02. a selection from a list of differentiation types;

03. a selection of a list of characteristics of said first concept represented by said cntexxt and also setting a differentiated value for said characteristic;

04. a selection of another cnxpt and also selecting an entry from a list of how said another cnxpt describes the differentiation of said concept being conjured by said user from said first concept represented by said cntexxt;

05. the stating of one or more words describing a differentiation type not listed;

06. the definition of a characteristic had by said concept being conjured by said user but not by said first concept represented by said cntexxt and stating a value for said characteristic;

07. citing an occurrence relevant to said concept being conjured by said user but not relevant to any other context within said first concept represented by said cntexxt;

08. citing an occurrence not relevant to said concept being conjured by said user but relevant to all other contexts within said first concept represented by said cntexxt or presently considered as relevant to said first concept represented by said cntexxt;

09. citing a relationship info-item that said concept being conjured by said user should participate in but is not participated in by any other context within said first concept represented by said cntexxt or by said first concept represented by said cntexxt;

10. citing a relationship info-item that said concept being conjured by said user should not participate in but that is participated in by all other contexts within said first concept represented by said cntexxt or presently participated in by said first concept represented by said cntexxt;

11. citing a trait held by said concept being conjured by said user but not held by any other context within said first concept represented by said cntexxt;

12. citing a trait not held by said concept being conjured by said user but held by all other contexts within said first concept represented by said cntexxt or presently considered as held by said first concept represented by said cntexxt;

13. citing a time frame relevant to said concept being conjured by said user or where said concept being conjured by said user was valid for but is not precisely the same time frame of any other context within said first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for;

14. citing a location relevant to said concept being conjured by said user or where said concept being conjured by said user was valid for but is not precisely the same location of any other context within said first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for;

15. citing a time frame that is not relevant to said concept being conjured by said user or during which said concept being conjured by said user was not valid but that is missing from all other contexts within said first concept represented by said cntexxt and not precisely excluded from encompassing the present time frame of said first concept represented by said cntexxt.

and

16. citing a location that is not relevant to said concept being conjured by said user or during which said concept being conjured by said user was not valid but that is missing from all other contexts within said first concept represented by said cntexxt and not precisely excluded from encompassing the present location of said first concept represented by said cntexxt.

205. The method of claim 1 to ingest external wisdom, wherein:

a. providing a user interface capable of empowering a user to find external data by indicating a source given by at least one selection of the group of;

i. a source of data in record form and a sufficient query;

ii. a source of data to be crawled and a sufficient scoping of the crawl;

iii. a query able to produce or refresh a result set of irxts;

iv. a data batch of citation rich documentation;

b. processing the action requested by the user to find external data;

c. processing any newly found external data, further including;

i. collecting information into a data set to be compared against, new information is detected and then added to said commonplace;

ii. cataloging said data set by associating with a new fxxt said source info-item by a source relationship to assign a single fxxt to ingested information for provenance and authority control of ingested information,

iii. broadening base of knowledge by ingesting as a source object said data set into said commonplace of knowledge;

iv. ingesting a plurality of info-items into said commonplace;

v. ingesting a plurality of relationship info-items into said commonplace;

vi. ingesting a plurality of association info-items into said commonplace;

vii. ingesting a plurality of occurrence info-items into said commonplace;

viii. integrating said info-items directly extracted from the information in said data set into said commonplace by generating relationships between said info-items based upon relationships in said data set by connecting ingested wisdom to existing knowledge in said commonplace of knowledge;

ix. integrating said info-items directly extracted from the information in said data set into said commonplace by generating associations between said info-items that are cnxpts based upon relationships in said data set by connecting ingested wisdom to existing knowledge in said commonplace of knowledge;

x. cataloging, on a logical typing level, batches of external or internally held information resources or internal resources serving as information resources by said fxxt;

xi. cataloging, on a logical grouping level, batches of external or internally held information resources or internal resources serving as information resources by irxts;

xii. creating classification relationships between the generated categories represented by the new cnxpts and the cnxpts in the clusters;

xiii. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

xiv. accepting a choice of zero or more relationship info-item types to be used as propositional relationships for determining a categorization represented by hierarchical association instances from the relationship info-item types of those relationships having directionality and relating said entity types to be considered as instances of said cnxpt type either already existing within said commonplace or in said data set to prepare for categorizing and visualizing appropriate to said use case;

xv. accepting a choice of zero or more relationship info-item types to be used as a determinant of meaning categorization as represented by hierarchical association instances from the relationship info-item types of those relationships having directionality and having one or more of said chosen term ttx instances as endpoints to be considered as instances of term ttx meaning hierarchy relationships for the purpose of similarity illustration within said commonplace;

xvi. accepting a choice of zero or more relationship info-item types to be used as a determinant of meaning categorization as represented by affinitive association instances from the relationship info-item types of those relationships to represent similarity between cnxpts within said commonplace;

xvii. generating a fxxt for the purpose of the instant similarity illustration;

xviii. computing a weighted consensus from opinions according to utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

xix. determining weights of said all associations to be used as a determinant of categorization, said relationships already existing within said commonplace are retained and weights of said added source object info-items are calculated as a coefficient specified by the user times the value given in an attribute present for said relationship info-item or a specified default value according to utilize collective consensus through vote tallying means;

xx. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all associations to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

xxi. extracting a spanning forest of cnxpts and interrelationships where each of said cnxpts of said cnxpt type are taken as categories and arranged based upon said summary relationships according to map generation means;

and

xxii. forming said organization of knowledge having at least one domain of wisdom from said added wisdom, wherein any additional portion of said commonplace is included to serve as a base reference in an operation selected from the group of;

a prediction, a model differentiation, a categorization, a comparison, and a curation;

according to map generation means;

d. building at least one visualization for display to users based upon said organization of knowledge of at least one domain of wisdom to use as an organizing base for initial viewing;

e. learning from users the inconsistencies and redundancies in said ingested wisdom where connected to existing knowledge in said commonplace of knowledge;

f. removing knowledge exactly matching other knowledge by content;

g. accepting culling commands in manual review to categorize said source object according to concepts and contexts as represented by existing cnxpt;

h. accepting culling commands in manual review to re-prioritize said source object for further review according to pre-specified workflow rules or to remove said source object from further review or from a collection of source objects in said commonplace of information;

and

i. requesting, accepting, and controlling manual review of ingested information.

206. The method of claim 1, wherein each association between a pair of cnxpts in the commonplace includes a weight indicating a strength of the association between the pair of cnxpts;

wherein generating a visualization from a map is based upon combining the weights of the associations between unique cnxpt pairs wherein the associations are obtained by interpreting the definition of the map and any fxxts in the set of fxxts referenced in the map definition, further comprising;

a. accepting a command regarding a map definition from a user selected from the group of;

an info-item addition command defining a new map without parameters stated, an info-item addition command defining a new map along with stated parameters, and an info-item change command refining a map definition along with stated parameters;

b. accepting with said command regarding a map definition a map identity value of type selected from the group of;

a lack of value specifying to use a system generated identity, a parameter value acceptable as an identity, a form fill-in value acceptable as an identity, and a value acceptable as an identity that is acceptable to the user interface;

c. accepting with said command regarding a map definition a set of zero or more result sets;

d. accepting with said command regarding a map definition a set of zero or more temporary derived ontologies;

e. accepting with said command regarding a map definition zero or more fxxt identity values of type selected from the group of;

a lack of value specifying to use a system default identity, a lack of value specifying to use a system generated identity, a lack of value specifying to use a system generated identity for the specific user defining the map, a lack of value specifying to use a system generated identity for the organization of which the user is a part, a lack of value specifying to use a system generated identity for identifying to the map search results passed as a specific parameter to the map upon map invocation, a lack of value specifying to use a system generated identity for identifying to the map search results obtained by a search query associated with a fxxt specification, a lack of value specifying to use an identity earlier specified by a user to be used as a default, a parameter value acceptable as an identity, a form fill-in value acceptable as an identity, and a value acceptable as an identity that is acceptable to the user interface;

f. accepting with said command regarding a map definition, for each fxxt included in the map definition, zero or one fxxt weighting coefficient indicating a proportionality of impact value indicating a strength of consideration of associations that are marked by the fxxt listed in the map definition, each value of type selected from the group of;

a lack of value specifying to use a previously set value already displayed, a lack of value specifying to use a system default value of 1, a lack of value specifying to use a system default value other than 1, a parameter value, a form fill-in value acceptable as a coefficient value, and a value acceptable as a coefficient value that is acceptable to the user interface;

g. accepting with said command regarding a map definition, for each fxxt included in the map definition, zero or one fxxt weighting coefficient indicating a proportionality of impact value indicating an importance of consideration of cnxpts that are marked by the fxxt listed in the map definition or serve as endpoints of associations that are marked by the fxxt listed in the map definition, each value of type selected from the group of;

a lack of value specifying to use a previously set value already displayed, a lack of value specifying to use a system default value of one, a lack of value specifying to use a system default value other than 1, a parameter value, a form fill-in value acceptable as a coefficient value, and a value acceptable as a coefficient value that is acceptable to the user interface;

h. accepting with said command regarding a map definition zero or more parameters of a type selected from the group of;

display name, display title, access rights, mode settings, custom settings, extension settings, comments, general-association-acceptance-for-affinities mode indication, extract-classes mode indication, expand-classes mode indication, extract-uninstantiated-classes mode indication, explode-able-classes mode indication, treat-as-trigger-able indication, info-item type inclusion parameter, trigger-able-during-forest-extraction mode indication, trigger-able-after-forest-extraction mode indication, and fxxt-free mode indication;

whereby a map definition prescribing a set of fxxt specifications used in an extraction process for extracting a set of cnxpt instances and association instances from a commonplace is specified;

whereby generating the visualization from the map organization of knowledge utilizes a combination, calculated pairwise by unique cnxpt pair, of the weights of the associations that are marked by fxxts in the set of fxxts listed in the map definition.

207. The method of claim 1 to rationalize terms, further including:

a. accepting a choice of one or more of said new term ttx instances or said existing term ttx instances for meaning similarity illustration;

b. marking said choices of said term ttx instances as cnxpts for the purpose of similarity illustration;

c. marking a plurality of instances of affinity associations and term ttx meaning hierarchical associations having one or more of said chosen term ttx instances as endpoints as having a fxxt for the purpose of the instant similarity illustration;

d. marking a plurality of cnxpts serving as endpoints of affinity associations and term ttx meaning hierarchical associations marked with said fxxt for the purpose of the instant similarity illustration to also belong to said fxxt for the purpose of the instant similarity illustration;

e. broadening the illustration of similarity, to a predetermined degree of association info-item distance by including into said fxxt additional instances of affinity associations and term ttx meaning hierarchical associations having one or more of said marked term cnxpts as endpoints and marking said instances of affinity associations and term ttx meaning hierarchical associations as having said fxxt for the purpose of the instant similarity illustration, and then marking a plurality of cnxpts serving as endpoints of said newly marked associations as also having said fxxt for the purpose of the instant similarity illustration;

f. determining effective weights and directions for summary associations to be used as a determinant of categorization between cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

and

g. illustrating effective term similarity by positioning of terms.

208. The method of claim 1 to also provide assisted resource serving, further including:

a. defining a map to be organized by semantic classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. invoking a metasearch interceptor software analytic to catch relevant search results from one or more search tools during a user query according to finding, searching, query and retrieval means and according to goal based searching means;

d. forming a query for submission to said search tools;

e. forming a goal if said query is a first query toward said goal;

f. adding said query to said goal if query is a continuation of searching of said goal;

g. obtaining from said user'"'"'s returned result of said query one or more locators for an information resource or internal resource serving as an information resource from one or more heterogeneous repositories;

h. obtaining said information resource or internal resource serving as an information resource'"'"'s metadata from a heterogeneous repository location provided by said locator;

i. creating, for an information resource or internal resource serving as an information resource not already related to an irxt, a new irxt info-item into said commonplace for each collected information resource or internal resource serving as an information resource and setting its properties to have said locator and said metadata of said information resource or internal resource serving as an information resource as values to indicate the characteristics of said information resource or internal resource serving as an information resource as defined by said information resource or internal resource serving as an information resource'"'"'s metadata to obtain an index to said information resource or internal resource serving as an information resource according to import collateral information resource means, or internal resource serving as an information resource, or according to enter information resource for a ttx means to enter information resource or internal resource serving as an information resource for a ttx, and according to create irxt means;

j. forming a result set for said query for said goal according to result set processes means and according to create result set means;

k. forming an rsxitem representing said information resource or internal resource serving as an information resource in said result set for said query for said goal according to result set processes means and according to create result set means;

l. accepting a result set as chosen for culling by user by choice of a query, search, goal, cnxpt, or crawl result that formed said result set;

m. generating a visualization of the list of rsxitems of said result set providing a culling perspective according to extract and generate ordering for taxonomy from result set for culling means, using a chosen fxxt if set;

n. presenting said rsxitem'"'"'s said information resource or internal resource serving as an information resource'"'"'s content to user by de-referencing said locator;

o. accepting culling commands on said result set rsxitems according to result set processes means to obtain an assessment by user of the propriety of said rsxitem to said result set as a measure of the relevance of an rsxitem primarily to the ttx in his mind and secondarily to said query, or search having said result set;

p. summarizing said result set into query independent result set for goal, setting summarized relevance rankings according to result set conversion to properties, occurrences, and categorizations means;

and

q. determining a plurality of cntexxts in said map that said search goal could be associated with by comparing said search results with relevant information of existing cnxpts in said map to reposition said goal according to said result set into the best cntexxt according to result set evaluation for positioning means.

209. The method of claim 1 to also provide characterizations of law by jurisdiction in legal research by weighted categorization, further comprising:

a. accepting at least one characterization selected from the group of;

i. a first jurisdiction'"'"'s law or opinion relative to a second jurisdiction as good law, with zero or more citations to opinions of said second jurisdiction wherein said zero or more citations to statutory proceedings or legislative history regarding laws or court opinions of said second jurisdiction would have described the reasoning specifically regarding said first jurisdiction'"'"'s law or opinion if it had been considered because said law or opinion of said second jurisdiction addressed a similar issue or sub-issue as said first jurisdiction'"'"'s law or opinion;

ii. a case as a cnxpt representing said case as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

iii. a secondary source as an occurrence of a cnxpt representing the issue or sub-issue for which the source is relevant;

iv. a theory of a case as a cnxpt representing said case'"'"'s theory as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

v. a fact as a cnxpt representing said fact as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits, said cntexxt a member of the cntexxt representing the fact set of the case;

vi. an element or sub-element of law as a cnxpt representing said element or sub-element of law as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

vii. evidence available for proving facts as a cnxpt representing said evidence as a concept of a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits, said cnxpt having occurrences referencing physical objects or files of an electronic nature said objects or said files being actual evidence;

viii. a party as a cnxpt representing said party, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

ix. an involved other person as a cnxpt representing said other person, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

x. a case'"'"'s status or a docket entry as a cnxpt representing said case'"'"'s status as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits, said cnxpt having occurrences referencing physical objects or files of an electronic nature said objects or said files being presentation material or other objects, children of said cnxpt as representatives, as mere examples said representatives selected from the group of;

material for presentation, foundation information, stipulations, theories to be addressed, specific issues, specific precedent, specific testimony, specific persuasive material, objections, specific witnesses, matters to raise, documents to file, negotiation material, discussion material, tactical or strategic plans, statutes, legislative history information, receipts, court procedures and rules, appellate strategies, issues to preserve, pictures, recordings, movies, helpful multi-media, transcripts, indices by issue, citations, citatory results, descriptions of doctrine, treatments of elements or sub-elements of law, treatments of issues or sub-issues of doctrine or the case, notes, electronic files for presentation, status material, responsible team members, accounting information, concerns, deposition preparation, discovery material, prior court opinions, status on law of the case rulings, rebuttal information, rebuttal presentations, police reports, expert opinions, affidavits, probation reports, administrative rulings, helpful documents, helpful material, helpful contact information, helpful collaborative status information, counter-strategies expected of opponent, and variations of orderings of presentation for specific circumstances;

xi. a case issue as a cnxpt representing said case issue as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

xii. a concept as a cnxpt representing said concept as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits, said concept selected from the group of;

presentation sections, foundation information groups, stipulation topics, theories to be addressed, specific issues, specific precedent, specific testimony topics, specific persuasive material topics, objections, specific witnesses, matters to raise, document groupings by purpose, filing outlines, negotiation outlines, discussion outlines, tactical or strategic plans, concepts shown by statute, receipt pockets, topics regarding court procedures and rules, appellate strategies by issue, issues to preserve, groupings of pictures, recordings, movies, or other multi-media,

xiii. the concept of a set of zero or more documents or physical objects or files of an electronic nature as a cnxpt representing said concept as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits, said cnxpt having occurrences referencing objects of the nature of said zero or more documents or physical objects or files of an electronic nature, mere examples of said objects selected from the group of;

material for presentation, foundation information, stipulations, documents regarding theories to be addressed, documents regarding specific issues, documents regarding specific precedent, documents regarding specific testimony, specific persuasive material, documents regarding objections, documents regarding specific people or organizations, documents regarding objections, documents regarding specific witnesses, documents regarding matters to raise, documents to file, negotiation material, discussion material, documents regarding tactical or strategic plans, documents regarding statutes, documents regarding legislative history information, receipts, court procedures and rules, documents regarding appellate strategies, documents regarding issues to preserve, pictures, recordings, movies, helpful multi-media, transcripts, indices by issue, citations and digests, citatory results, descriptions of doctrine, documents regarding treatments of elements or sub-elements of law, documents regarding treatments of issues or sub-issues of doctrine or the case, notes, electronic files for presentation, documents regarding status material, documents regarding responsible team members, documents regarding accounting information, documents regarding concerns, deposition preparation materials, discovery material, prior court opinions, documents regarding status on law of the case rulings, documents regarding rebuttal information, rebuttal presentations, police reports, documents regarding expert opinions, affidavits, probation reports, administrative rulings, helpful documents, helpful material, helpful contact information material, helpful collaborative status information material, documents regarding counter-strategies expected of opponent, and documents regarding variations of orderings of presentation for specific circumstances;

xiv. a litigant'"'"'s objective as a cnxpt representing said litigant'"'"'s objective as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

xv. an attorney presentation outline for a case as a cnxpt representing said attorney presentation outline as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

xvi. the status of a statute or regulation, indicating whether they have been amended or repealed as a cnxpt representing said status of a statute or regulation as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

and

xvii. a position based upon any legal issue or sub-issue being researched as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

and

b. generating an organization of knowledge and visualization of map providing cross-indices of at least one item selected from the group of;

by issue, citation topics, doctrinal topics, elements or sub-elements of law, issues or sub-issues of doctrine or the case, notes by topic, groupings for files, groupings for statuses, groupings for responsibilities, groupings for files accounting information, concerns, groupings for files depositions, discovery topics, groupings for prior court opinions, groupings for topics regarding status on law of the case rulings, groupings for rebuttal information, groupings for rebuttal presentations, groupings for police reports, expert opinion topics, groupings for affidavits, groupings for probation reports, groupings for administrative rulings, groupings for contact information, groupings for collaborative status information, groupings for counter-strategies expected of opponent, and groupings for orderings of presentation for specific circumstances.

210. The method of claim 1 to also provide a managed commonplace of legal information for research and legal discovery, further comprising:

a. providing an organization of knowledge regarding legal matters, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a legal issue;

b. providing an organization of knowledge regarding law, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing an element or sub-element of a law;

c. providing an organization of knowledge regarding people and organizations, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a person or an entity;

d. providing an organization of knowledge regarding purported evidence, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing a piece of evidence real or desired to prove a theory;

e. providing an organization of knowledge regarding events, within a domain of wisdom in said commonplace for holding and categorizing cnxpts with evolving attached descriptive information, at least one said cnxpt representing an event capable of having a timeframe and a location involved;

f. loading of said commonplace with structural information defining a knowledge model;

g. providing task management and document management analytics for controlling workflows, determining scheduling based upon workflow priorities, and suggesting task assignments;

h. ingesting a plurality of source objects;

i. initiating continuous extraction of each source object'"'"'s identity, descriptive information, origination, and provenance meta-data to generate a source info-item with attached descriptive information, said type of source object selected from the group of;

an info-item from an external commonplace, a concept represented by a cnxpt from an external commonplace, data set, meta-data, file, information resource, statement, communication, template, legal decision, docket, story, transcript, and document;

said source info-item to be used as the authority control base for said source obj ect and related to a new fxxt by a source relationship, said fxxt termed a source object provenance authority fxxt;

j initiating continuous extraction, for each source object that is a structured data set having data set elements, of all data set elements of said source object selected from the group of;

table description, entity type description, column description, attribute description, relationship info-item type descriptive information, table procedure description, object method description, and data rule description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said data set elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, wherein all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

k. initiating continuous extraction, for each source object that is a structured data set having data set elements, of all data rule descriptions of said source obj ect to generate, for each, a concept represented by a cnxpt with attached descriptive information, said cnxpt to be used as curation reference base, said cnxpt termed a source data rule authority cnxpt;

l. initiating continuous extraction, for each source object that is unstructured data, of all descriptive elements of said source object selected from the group of;

object meta-data, citation, page description, foot or end note, volume title, section title, chapter title, bookmark, section text, page text, type description, definition, index entry, table of contents entry, author, editor, table, figure, character, precedent, quotation, topic, issue, finding, opinion, and description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said descriptive elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, wherein all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

m. initiating continuous extraction, for each source object that is unstructured data, a cited information resource irxt info-item for any information resource not existing in said commonplace of information;

n. initiating continuous extraction of topical elements from said source object, said topical element selected from the group of;

term, timeframe, thing, feature, link, status, originator, event, party, participant, person, owner, address, location, organization, reviewer, rule, object, relationship info-item description, type identity, law, citation, claim, belief, strategy, concern, position, document characterization, communication, communication meta-data property, law, fact, statement, opinion, issue, case, docket entry, story, theory, semantic token, name, statement, precedent, attribute, identity, evidentiary item description, concept, context, classification category, meta-data value, and other description;

each said topical element to be used as a base for deriving commonalty and similarity scores for said source object, wherein a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, wherein all instances of said coding key cnxpt of a type are assigned a single fxxt based upon said source object provenance authority fxxt and the type of coding key;

o. determining relevance of said source object to a search objective stated as a search query specification step wherein said source object is a result set item in a search result set;

p. determining pertinence of said source object for a domain of wisdom extraction objective stated as a fxxt specification step wherein said source object is an info-item of any type applicable to said fxxt specification step;

q. determining pertinence of said source object for a prioritization rule of a methodology workflow specification step wherein said source object is an info-item of any type applicable to said methodology workflow specification step;

r. determining pertinence of said source object for an alert generation rule of an alert specification wherein said source object is an info-item of any type applicable to said alert specification generation rule;

s. initiating execution of the means for categorizing said commonplace by performing map generation, wherein a computer performs management of said commonplace, and prepares at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means wherein said organization of knowledge of at least one domain of wisdom includes said source object provenance authority fxxt and also includes any additional portion of said commonplace against which categorization or comparison or curation is to occur;

t. building at least one map instance and visualization for display to users based upon said organization of knowledge of at least one domain of wisdom to use as an organizing base for initial viewing;

u. displaying to said user a portion of said commonplace is displayed according to display and delivery means;

v. initiating requests for action, with attached description of action, to a user according to methodology workflow specification step;

w. initiating alerts, with attached description, to a user according to an alert specification generation rule;

x. initiating methodologies according to said methodology templates;

y. initiating workflows according to said workflow templates;

z. providing search query procedure templates for searching for source objects to determine relevance;

aa. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

bb. providing methodology and workflow templates for project management of searching for and reviewing source objects to determine relevance to a stated meaning or issue;

cc. providing prediction analytics establishing commonalty and similarity scores for source objects;

dd. computing a predicted weighted ranking of a source object likely relevance to a coding key cnxpt as specified;

ee. computing a predicted weighted rejection ranking of a source objects according to rules for rejection as irrelevant or privileged;

ff. accepting data rule descriptions as concepts represented by cnxpts with attached descriptive information, said cnxpts to be used as curation reference bases, said cnxpts termed source data rule authority cnxpts;

gg. accepting culling commands in manual review to categorize source objects according to said concepts and contexts as represented by cnxpts;

hh. accepting culling commands in manual review to re-prioritize source objects for further review according to specified workflow rules or to remove them from further review or from collection of source objects in commonplace of information;

and

ii. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effecting change;

iii. to navigate around a visualization of said commonplace;

iv. to request a search for wisdom;

v. to enter a fxxt specification involving extraction by meta-data and search queries to meet criteria for project;

vi. to accept a workflow task;

vii. to specify search query specifications, workflow task assignment and document passing specifics to meet criteria for project;

viii. to initiate operation of data extraction, document management, and prediction analytics;

ix. to initiate continuing retrieval of source objects based on the criteria according to search query specifications;

x. to establish a commonplace of information for the purposes of a specific dispute or matter, termed a discovery preparation set;

xi. to ingest into said discovery preparation set commonplace of information a source object set;

xii. to grant access to a source object to a different user for the purposes of a specific dispute or matter, the accumulation of said grants termed a discovery production set;

xiii. to categorize source objects into workflow contexts;

xiv. to allocate resources according to specified workflow rules for assignment or workflow rules for task acceptance;

xv. to refine search query specifications, categorizations, and priorities for review;

xvi. to specify relevance prediction weightings;

xvii. to notify a supervisory level regarding a source object'"'"'s importance;

xviii. to specify details for workflow structure and categorizations by establishing contexts for work tasks represented by cnxpts and workflow transitions represented by relationships to meet criteria for project;

xix. to alter a workflow based upon quality checks produced by workflow and methodology;

xx. to alter a workflow based upon review of metrics produced by workflow and methodology;

xxi. to generate a report or data set of the data set catalog, provenance, production cost, and consensus regarding relevance weights of said discovery preparation set or said discovery production set;

and

xxii. to generate an extract data set of said discovery production set.

211. The method of claim 1 to also provide determining of categorization quality of dissection for ingesting against an exemplar, further including:

a. updating the consensus organization of each comparison categorization from said commonplace augmented by all info-items generated from said plurality of members of a returned set of information each a source object suggesting a meaning according to utilize collective consensus through vote tallying means;

b. determining a proper placement of said dissection cnxpt in each said comparison categorization augmented by all info-items generated from said plurality of members of a returned set of information each a source object suggesting a meaning according to map generation means, wherein if a predetermined system setting is set to a first predetermined value said map generation does not alter the positioning of cnxpts existing before performing a search resulting in plurality of members of a returned set, wherein if a predetermined system setting is set to a second predetermined value said map generation does alter the positioning of cnxpts existing before performing a search resulting in plurality of members of a returned set;

c. determining a normalized relevance score for relevance of said dissection concept represented by a dissection cnxpt to each said basis cnxpt, from a predefined formula to compute a sum across all said comparison categorizations wherein a predetermined coefficient based upon the comparison categorization is multiplied against a factor determined from the distance in said comparison categorization of the placement of said dissection cnxpt against each basis cnxpt in a vicinity of a predetermined size from said dissection cnxpt, said relevance score is attached to said binding point info-item for each said derived source object suggesting a meaning for said dissection concept represented by a dissection cnxpt;

d. determining a cumulative relevance score for each said result set item info-item by summing all said relevance scores attached to said binding point info-items for each said derived source object suggesting a meaning stemming from said dissecting of said source object suggesting a meaning;

e. determining, optionally, a normalized value for each said cumulative relevance score for said result set;

f. assigning the order property of each created result set item info-item in said result set to a value converted from said relevance strength assigned wherein the most relevant rsxitems will be sorted to appear at the top of a result set display for culling;

g. making said result set active for culling by displaying result set in an editable format;

h. defining a map to be organized by a classification, wherein similar concepts are in closer proximity than dissimilar concepts;

i. generating a map instance for said map;

and

j. calculating quality corrections according to prediction correction mechanism, wherein;

i. determining, as a first error metric value, the lack of quality of a positioning of cnxpts in a scope of a positioning of at least one of;

over all cnxpts, all cnxpts at a level, or all cnxpts within a category by determining the cumulative total of distances for said cnxpts in a scope of a positioning, by centroids, from an exemplar cnxpt positioning for the same cnxpt if both the positioned map and the exemplar contain the same cnxpt;

ii. determining, as an additional error metric value, the lack of quality of fxxt inclusion by the difference between the total number of cnxpts in the exemplar and the number of cnxpts of the map that match cnxpts in the exemplar, divided by the number of cnxpts in the exemplar;

iii. determining, as an additional error metric value, the lack of quality of a positioning of non-cnxpts in a scope of a positioning of at least one of;

over all non-cnxpts, all non-cnxpts at a level, or all non-cnxpts within a category by determining the cumulative total of distances for said non-cnxpts in a scope of a positioning, by centroids, from an exemplar non-cnxpt positioning for the same non-cnxpt if both the positioned map and the exemplar contain the same non-cnxpt;

iv. determining, as an additional error metric value, the lack of quality of a structuring of cnxpts by averaging the differences between the total number of cnxpts in the exemplar for the level having depth j from the root and the number of cnxpts of the map at depth j from the root that match cnxpts in the exemplar for depth j from the root, divided by the number of cnxpts in the exemplar for the level at depth j from the root, for all j less than or equal to the greatest depth for which an exemplar is available;

v. determining, as an additional error metric value, the lack of quality of a modeling result against an expected value as stated by an exemplar for that result;

and

vi. summing, with predetermined coefficient values for each error metric as a cost function, the error metric values as multiplied by the coefficients, to obtain the amount of correct structure present in the more optimal but lost in the present codebook exemplar data as represented by the totaled cost of the error.

212. The method of claim 1, to determine whether improvement of recommendation scoring is needed based upon the measurement of quality of recommended choices against actual choices by comparison to an exemplar, further including:

a. generating a map instance from a map definition given a domain of wisdom to form a positioned organization of knowledge by the generation, encompassing recommendations regarding the importance to the user of cnxpts organization of knowledge by positioning the principal children centrally in the context defined by the cntexxt represented by the parent cnxpt of the children, by sizing cnxpts by their importance, and by providing other indicators to speed the user'"'"'s review of the material shown in the map instance;

b. generating, as a pre-viewing exemplar of the map, zero or more recommendation score estimate tuples for each first cnxpt in the map, wherein each recommended action tuple comprises;

the action, the identifier of a second cnxpt visited or subject to an action or null, a type descriptor for the second cnxpt or null, the identifier of the first cnxpt, a type descriptor for the first cnxpt, an ordinal number n, and the estimated conditional likelihood that the second cnxpt would be found to be at least tied as the nth best choice of a next destination cnxpt to visit in the map by an intended audience for the recommendation given prior choices leading to the visit of the first cnxpt;

wherein the likelihood that such a navigation from the first cnxpt to the second cnxpt would occur in use of the map instance is greater than a pre-set parameter value, the estimated conditional likelihood computed from the recommender algorithm for the map, a type descriptor comprising a tuple of zero or more characteristics for a cnxpt that the recommender is trained to consider, the navigation or action of a type selected from the group of;

i. the first cnxpt a parent of the second cnxpt;

ii. the second cnxpt a parent of the first cnxpt;

iii. the first cnxpt a parent ancestor cnxpt of the second cnxpt;

iv. the second cnxpt a parent ancestor cnxpt of the first cnxpt;

v. the first cnxpt an uncle of the second cnxpt;

vi. the second cnxpt an uncle of the first cnxpt;

vii. the first cnxpt a sibling of the second cnxpt;

viii. the first cnxpt a cousin of the second cnxpt;

ix. the first cnxpt having a type matching, by its properties at the time of the visit to the second cnxpt, a first type descriptor that the recommender is trained to consider and the second cnxpt having a type matching, by its properties at the time of the visit to the second cnxpt a second type descriptor that the recommender is trained to consider, for a pre-established set of scenarios regarding the properties of the first cnxpt and the second cnxpt;

x. an action taken at the first cnxpt that affects the second cnxpt other than navigation to the second cnxpt;

and

xi. an action taken at the first cnxpt other than navigation to a second cnxpt;

c. accepting, as post-viewing actuals, during user accessing of the map instance, a plurality of statistical samplings, each sample a choice of a navigation by a user from a first cnxpt to a second cnxpt, the choice with the knowledge that a recommendation was available and indicated for a navigation from the first cnxpt under similar conditions in the organization of knowledge, wherein for convenience the samples as tuples comprising;

the identifier of the second cnxpt, the type descriptor of the first cnxpt at the time of the visit to the second cnxpt, the identifier of a first cnxpt, the type descriptor of the second cnxpt at the time of the visit to the second cnxpt, the count of possible next choices at the time that the second cnxpt was chosen, a history with k entries giving the last k cnxpts visited prior to the second cnxpt and their type descriptors at the time of the visit to the second cnxpt, where k is a pre-set parameter value;

d. determining, based upon the data collected, per recommendation and for all recommendations overall, the lack of quality of the set of recommendations of cnxpts by the likelihood that the choices actually made for actions or navigation to next cnxpts under presence of an indication of recommendation were commensurate with the estimated likelihoods of the exemplar, taken over all cnxpts scored, to estimate the amount of error in the recommender calculations in the pre-viewing estimation, the determining based upon combined results of application of multiple tests, the tests applied to data collected of a type selected from the group of;

i. the position of the cnxpt in the positioned organization of knowledge of the map instance to provide an approximate matching by distance;

ii. the extended tracking histories for indicating navigation order from a first cnxpt;

iii. the discrete, recommender defined, pre-tagged characteristics for cnxpts visited;

iv. the important actions taken when visiting a cnxpt;

and

v. the basic statistics of counts of matches of visiting sequence from a first cnxpt to a second cnxpt;

and

e. altering the basis of recommender scoring calculation by a change of a metric, said metric chosen from the list of;

a coefficient applied in the calculation of a component structure of said organization of knowledge, a weight applied to a user'"'"'s or analytic'"'"'s generated votes, a weight applied to a user'"'"'s interest shown by navigating or actions taken, a weight applied to the interest shown by similar users by navigating or actions taken, the set of users considered similar to said user, a weight applied to a calculation for determining the set of users considered similar to said user, an authoritativeness weight applied to the rankings of users or analytics voting or showing interest by navigating or taking action, a length or importance metric applied to periods used for calculation based upon navigating or taking action that are based upon time periods or volumes, a coefficient applied to the interest shown metrics for navigating or taking action collected from a fxxt where multiple organizations of knowledge are used for prediction of likelihood of action by cnxpt, a weight applied to a specific commonality term importance in forming the basis for analytic based generation of imputed relationship info-items, a weight applied to a set of commonality terms for importance in forming the basis for analytic based generation of imputed relationship info-items where the terms are grouped by language, locale, dialect, technical field, source, provenance, purpose, or formality, and a weight applied to a type of imputed relationship info-item from said commonality determinations;

to improve the quality of recommendations for the organization of knowledge;

whereby the recommendations as embodied in the positioning and sizing of the cnxpts for a map may prove to be wrong based upon one or more users'"'"' actual behavior of visiting cnxpts and would not be improved if it was left to the users to proactively change positions or sizing;

whereby the user'"'"'s behavior of visiting cnxpts is used to improve algorithms as well as for generating interest votes;

whereby the user'"'"'s past behavior of visiting cnxpts is compared to similar decisions made by other users;

whereby the past behavior of like users visiting cnxpts based upon a series of discrete, pre-tagged characteristics of a cnxpt navigated to given a series of discrete, pre-tagged characteristics of a cnxpt being navigated from is used as a basis to determine quality of recommendations of navigation destinations;

whereby the model based technique provides the structure for inclusion of effects of combining knowledge from one or more added domains of knowledge encompassed by other connected maps; and

whereby the quality at each level of a hierarchical recommender may be calculated and quality corrections may be made to the prediction correction modeling mechanism.

213. The method of claim 1 to also provide ingesting of relevant information, further comprising:

a. defining a map to be organized by a classification, wherein similar concepts are in closer proximity than dissimilar concepts;

b. generating a map instance for said map;

c. forming at least one organization of knowledge having at least one concept, said concept termed a basis concept represented by a basis cnxpt, said basis cnxpt also representing a cntexxt representing a context;

d. ingesting a first document to be referenced by said commonplace by forming at least one binding point for said first document, each said binding point created as a first cnxpt termed a dissection cnxpt;

e. dissecting said first document into a plurality of parsed parts resulting from one or more analytics, ingesting the plurality of parsed parts by forming at least one binding point for each of the plurality of parsed parts, each said binding point for each of the plurality of parsed parts created as an additional dissection cnxpt;

f. registering text of each of the plurality of parsed parts into the commonalities of said commonplace as a comparator token with a reference connection to said first document, said reference connection given a predetermined weight;

g. imputing association info-items from said commonalities;

h. updating a consensus of the associations connected to one or more dissection cnxpts in said commonplace as augmented by all associations generated from said plurality of documents and said dissection cnxpts, according to utilize collective consensus through vote tallying means;

i. performing map generation for each said at least one organization of knowledge including said augmented info-items to position the plurality of cnxpts based upon the updated said consensus of said commonplace as augmented according to map generation means, each specific member of the set of said at least one organization of knowledge including said augmented info-items termed a comparison map;

j. determining a normalized relevance score for relevance for each loaded document to each second said basis cnxpt, including all documents from prior loadings if any, further including;

i. determining a disaggregated normalized relevance score for relevance of a third differentiated concept represented by a third dissection cnxpt stemming from a first document in a vicinity of said second basis cnxpt by normalizing the result of a determination from the distance in said comparison map from the center of the placement of said third dissection cnxpt to the center of said second basis cnxpt if the distance is less than a predetermined size based upon the size of the map visualization, normalizing across all such disaggregated normalized relevance scores for relevance of a differentiated concept, each such score termed a new load disaggregated scoring;

ii. determining a disaggregated normalized relevance score for relevance of each fourth document from any prior loading as reflected in relevance score listed for a result set item indicating said forth document in a result set attached to said second basis cnxpt if any, normalizing across all such scores, each such score termed an old load disaggregated scoring by fourth document;

iii. determining a combined disaggregated normalized relevance score for relevance of said first documents from a predefined formula to compute a sum across all said comparison maps and said first document in regard to said second basis cnxpt, by summing all fifth old load disaggregated scorings regarding said second basis cnxpt wherein said fifth old load disaggregated scoring involves a dissection cnxpt stemming from said first document, each such score termed a new load aggregated scoring by first document;

iv. determining a combined aggregated normalized relevance score for relevance of said first and fourth documents from a predefined formula to compute a sum across all said comparison maps and said first and fourth documents in regard said second basis cnxpt, by summing a factor computed by multiplying a predetermined first coefficient for new loads times said new load aggregated scoring by first document for said first document and said second basis cnxpt and adding a factor computed by multiplying a predetermined fourth coefficient for old loads times said old load disaggregated scoring by fourth document for said fourth document and said second basis cnxpt and adding, if said first document is the same as said fourth document, the factors, normalizing all such combined aggregated normalized relevance scores for, if a predetermined system parameter is set to a predetermined value, said second basis cnxpt, or, if said predetermined system parameter is not set to said predetermined value, all such combined aggregated normalized relevance scores, said score termed a normalized document relevance for a document-cnxpt pair;

v. creating, if the normalized document relevance for a document-cnxpt pair involving said first document and said second basis cnxpt is greater than a pre-determined value and no result set item exists for said first document and said second basis cnxpt, a result set item in a result set attached to said second basis cnxpt referencing said first document and having a relevance score equal to said combined aggregated normalized relevance score involving said first document and said second basis cnxpt, or assigning, if the normalized document relevance for a document-cnxpt pair involving said first or fourth document and said second basis cnxpt exists and a result set item exists for said first or fourth document and said second basis cnxpt, to the result set item in a result set attached to said second basis cnxpt referencing said first or fourth document a relevance score equal to said combined aggregated normalized relevance score involving said first or fourth document and said second basis cnxpt;

and

vi. reordering said result set items of said result set attached to said second basis cnxpt according to said result set item relevance scores;

k. delivering to said user for review a result set for said search associated with said cnxpt of a user'"'"'s choice listing links to documents listed as result set items potentially satisfying said user'"'"'s actual intended search requirements;

l. accepting zero or more culling commands from said user wherein one of said documents is viewed, deleted, marked as relevant, or selected for navigation, or reordered in the result set attached to said cnxpt of a user'"'"'s choice;

and

m. assigning a new relevancy score and order for said user of said one of said documents based upon the culling command entered by said user wherein a deletion command causes a value representing not relevant no matter when entered and will override any prior command for said document, a coding of relevant causes a value representing relevant, a viewing causes a value representing possibly relevant, a relevance vote is recorded stating the final relevance values for said user for said cnxpt of a user'"'"'s choice replacing his prior relevance votes for said cnxpt of a user'"'"'s choice, a navigation command causes no change in the relevance score but causes a finalization of a relevance vote for said user and said cnxpt of a user'"'"'s choice.

214. The method of claim 1 to control the process of ingesting knowledge, wherein:

a. accepting a request to discover data source objects existing in or external to an organization of a type selected from the group of;

b. accepting a request to locate and ingest a data source object existing in or external to an organization of a type selected from the group of;

i. structured data from a data base;

ii. structured data from a data set;

iii. unstructured information resource web page from the internet;

iv. unstructured information resource file from a file system;

v. unstructured information resource document from a document store of files containing electronically encoded documents;

vi. structured data of a collection of unstructured data;

and

vii. unstructured information resource document electronically encoded from a scanning operation;

c. ingesting said source object by an operation selected from the group of;

i. registering said source object provenance, registering definition of structure of structured data in said source object, and ingesting data of said structured data in said source object;

ii. registering said source object provenance, registering definition of structure of structured data in said source object wherein said source object is a collection of information resources, and ingesting information resources of said structured data in said source object;

and

iii. registering said source object provenance, and ingesting information resource wherein said source object is an information resources;

d. registering said source object'"'"'s provenance by extraction of each source object'"'"'s identity, descriptive information, origination, and provenance meta-data to generate a source info-item in said commonplace with attached provenance cataloging descriptive information;

said type of source object selected from the group of;

an info-item from an external commonplace, a concept represented by a cnxpt from an external commonplace, data set, meta-data, file, information resource, statement, communication, template, legal decision, docket, story, transcript, physical object, artifact, electronic object, custom object, and document;

said source info-item to be used as the authority control base for said source object;

said provenance cataloging information stating at least one identifying fact selected from the group of;

a unique identification of said source object, where said source object resides, who is responsible for said source object, said source object'"'"'s purpose, said source object'"'"'s trustworthiness, custom pre-defined combination of information regarding source object, and said source object'"'"'s format;

said source info-item termed a source object provenance authority source info-item;

e. creating a fxxt info-item in said commonplace to represent the provenance of the source object, setting its authority, usability, quality, and expertise of originator, said fxxt termed a source object provenance authority fxxt;

f. adding a source relationship info-item from said source object provenance authority fxxt to said source info-item to be used as the authority control base for said source object;

g. generating, if a predetermined system parameter is set to a predetermined value;

a first irxt to represent as an information resource said data source obj ect;

said first irxt given an identity indicator value from a predetermined combination of said source info-item properties;

said first irxt filled with properties selected from the group of;

said source object'"'"'s authority, said source object'"'"'s usability, said source object'"'"'s quality, and expertise of originator;

said first irxt to reference said source object provenance authority source info-item of said data source object;

assigning to said first irxt representing said information resource said source object provenance authority fxxt;

said first irxt termed a source object provenance authority irxt;

h. generating, if a predetermined system parameter is set to a predetermined value;

a first cnxpt to represent the concept of the data set as defined by the purpose of the source object or the description of said source object;

an occurrence attached to said first cnxpt;

a relationship info-item of a predetermined weight based between said occurrence and said source object provenance authority irxt;

said first cnxpt given at least one identity indicator value resulting from a predetermined formulation of a value from the descriptive information of said source obj ect;

said first cnxpt given properties filled by a predetermined set of elements selected from the group of;

said source object'"'"'s authority and descriptive information;

said generated occurrence of said first cnxpt related to said first irxt;

said cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said cnxpt;

said first cnxpt termed a source object level cnxpt;

i. converting said source object'"'"'s data format to the format required for ingesting;

j converting said source object'"'"'s data element'"'"'s format to the format of a commonplace info-item of a predetermined equivalent type;

k. generating, if said source object contains one or more structured data set tables of the nature of rows of identifiable entity instances with identifiable associated attributes and if a predetermined system parameter is set to a predetermined value, for each table in the set;

a second irxt to represent as an information resource said table;

said second irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said source object, and the descriptive information of said table;

said second irxt given properties filled by a predetermined set of elements selected from the group of;

said table'"'"'s identity, the descriptive information of said table, said source object'"'"'s authority, usability, quality, row identity, and expertise of originator, and said source object'"'"'s descriptive information;

each said second irxt to reference said source object provenance authority source info-item, wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said second irxt and said source object provenance authority irxt if existing, each said second irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said second irxt, said second irxt termed a source data table information resource irxt;

l. generating, if said source object contains one or more structured data set tables of the nature of rows of identifiable entity instances with identifiable associated attributes, for each table in the set;

a new concept represented by a second cnxpt with attached descriptive information from said table'"'"'s description;

an occurrence attached to said second cnxpt;

a relationship info-item of a predetermined type and of a predetermined weight between said occurrence and said source object provenance authority irxt;

wherein;

said second cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said table, the descriptive information of said source object, and the descriptive information of said table;

said second cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said table and said source object'"'"'s authority and descriptive information;

wherein a child to parent relationship info-item of a predetermined type and of a predetermined weight is generated between said second cnxpt and said source object level cnxpt if existing;

wherein an additional occurrence is attached to said second cnxpt if said source data table information resource irxt exists for said table and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight is also formed between said additional occurrence and said source data table information resource irxt if existing;

said second cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said second cnxpt;

said second cnxpt to be used as a curation control base for said table;

said second cnxpt termed a source data table description authority cnxpt;

m. generating, if said source object contains one or more structured data set tables for which a second source data table description authority cnxpt was generated and if a predetermined system parameter is set to a predetermined value, for each table and each of said table'"'"'s columns of the nature of an entity'"'"'s attributes;

a fourth cnxpt to represent the attribute of the entity of said data set table;

an occurrence attached to said fourth cnxpt;

a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt;

said fourth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said table, the descriptive information of said source object, said table identity indicator and unique identity indicators of said attribute, and the descriptive information of said attribute of the entity of said data set table;

said fourth cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said table and said source object'"'"'s authority and descriptive information, the descriptive information of said attribute of the entity of said data set table;

wherein a child to parent relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said information resource in said table is generated between said fourth cnxpt and said source data table description authority cnxpt if existing, or otherwise to said source object level cnxpt if existing, said relationship info-item of a predetermined weight assigned said source object provenance authority fxxt if said fxxt is not already assigned to said relationship info-item;

wherein an additional occurrence is attached to said fourth cnxpt if said source data table information resource irxt exists for said table and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight based upon the number of references found of said information resource in said table is also formed between said additional occurrence and said source data table information resource irxt if existing;

said fourth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fourth cnxpt;

said fourth cnxpt to be used as a curation control base for said attribute of the entity of said data set table;

said fourth cnxpt termed a source data table column description authority cnxpt;

n. generating, if said source object contains one or more structured data set tables for which a second source data table description authority cnxpt was generated and if a predetermined system parameter is set to a predetermined value, for each data set table row of the nature of an instance of an entity with attributes;

a fifth irxt to represent as an information resource said table row;

said fifth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said table, the descriptive information of said source object, the descriptive information of said table, said table'"'"'s identity indicator and unique identity indicators of said data set table row;

said fifth irxt given properties filled by a predetermined set of elements selected from the group of;

said source object'"'"'s authority, usability, quality, expertise of originator, row identity, said table identity indicator, and unique identity indicators of said data set table row;

each said fifth irxt to reference said source object provenance authority source info-item;

wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said fifth irxt and said source object provenance authority irxt if existing;

wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said fifth irxt and said source data table information resource irxt for said table if existing, said relationship info-item assigned said source object provenance authority fxxt if said fxxt is not already assigned to said relationship info-item;

each said fifth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fifth irxt;

said fifth irxt termed a source data table row information resource irxt;

o. generating, if said source object contains one or more structured data set tables for which a second source data table description authority cnxpt was generated, for each table and each of said table'"'"'s data set table rows of the nature of an instance of an entity with attributes;

a fifth cnxpt to represent the instance of the entity of said data set table row;

an occurrence attached to said fifth cnxpt;

a relationship info-item of a predetermined weight is generated between said occurrence and said source object provenance authority irxt;

said fifth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

said table identity indicator and unique identity indicators of said data set table row;

said fifth cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said table, said source object'"'"'s authority and descriptive information and the attribute values of said data set table row;

wherein a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said fifth cnxpt and said source data table description authority cnxpt if existing, or otherwise to said source object level cnxpt if existing;

wherein an additional occurrence is attached to said fifth cnxpt if said source data table information resource irxt exists for said table and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight based upon the number of references found of said information resource in said table is also formed between said additional occurrence and said source data table information resource irxt if existing;

wherein an additional occurrence is attached to said fifth cnxpt if said source data table row information resource irxt exists for said table row and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight based upon the number of references found of said information resource in said table row is also formed between said additional occurrence and said source data table row information resource irxt if existing;

wherein each attribute of said data set table row is translated into a characteristic of predetermined type for said fifth cnxpt;

wherein an irxt termed an enclosed information resource irxt is generated for each attribute of said data set table row that is an information resource;

forming a part-of relationship info-item of a predetermined type and of a predetermined weight between said enclosed information resource irxt and said source object provenance authority irxt if existing;

forming a part-of relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said information resource in said table, between said enclosed information resource irxt and said source data table information resource irxt for said table if existing;

forming a part-of relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said information resource in said table row between said enclosed information resource irxt and said source data table row information resource irxt for said table if existing;

marking said enclosed information resource irxt by the identity of said provenance authority fxxt if said fxxt is not already assigned to said enclosed information resource irxt;

wherein all info-items generated from said source object are assigned said source object provenance authority fxxt, and;

if a predetermined system parameter is set to a predetermined value, said information resource is stored outside of said commonplace rather than as a property of said fifth cnxpt;

wherein each relationship between said data set table row as identified by an attribute containing a foreign key reference to a different data set table row in the data set is translated into a new relationship info-item of predetermined type and predetermined weight and like directionality between said fifth cnxpt and the cnxpt stemming from said different data set table row replacing any considered relationship of endpoint count greater than two by an equivalent set of relationship info-items having an endpoint count of two, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item, all info-items generated from said source object are assigned said source object provenance authority fxxt;

wherein each citation in said data set table row as identified by an attribute containing an identifiable citation selected from the group of;

standard citation, non-standard but identifiable citation, uniform resource locator, case citation, international standard book number, other cross reference, and link identifiable as a citation;

wherein a predetermined system parameter is set to a predetermined value and no irxt has been generated for the information resource cited, generate a tenth irxt to represent said information resource cited, said tenth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said source object, and the descriptive information of said information resource in said identifiable citation;

said tenth irxt given properties filled by a predetermined set of elements selected from the group of;

said information resource'"'"'s identity, said source object'"'"'s authority, usability, quality, and expertise of originator, said identifiable citation, and said information resource'"'"'s descriptive information;

each said tenth irxt to reference said source object provenance authority source info-item, wherein a citing relationship info-item of a predetermined type of a predetermined weight is generated between said tenth irxt and said source object provenance authority irxt if existing, each said tenth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said tenth irxt, said tenth irxt termed a cited information resource irxt;

wherein an additional occurrence is attached to said fifth cnxpt, wherein a relationship info-item of predetermined type and predetermined weight is also formed between said additional occurrence and said cited information resource irxt, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item, all info-items generated from said source object are assigned said source object provenance authority fxxt;

said fifth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fifth cnxpt;

said fifth cnxpt to be used as a curation control base for said table row;

said fifth cnxpt to represent the concept represented by said table row;

said fifth cnxpt termed a source data table row description authority cnxpt;

p. generating, if said source object contains one or more structured data set containing name value pairs or a serialized structure of hierarchical name value pairs where names are given by markup and values are in content or tag value pairs, collectively termed name value pairs, for each such name value pair;

a seventh cnxpt to represent said name value pair;

an occurrence attached to said seventh cnxpt;

a relationship info-item between said occurrence and said source object provenance authority irxt;

said seventh cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

said source object identity indicator and unique identity indicators of said name value pair, accommodating multiple instances of name value pairs having the same name;

said seventh cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said source object'"'"'s authority and descriptive information and the value of said name value pair;

wherein a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said seventh cnxpt and said source object level cnxpt if existing;

wherein each said name value pair value of said source object data set is translated into a characteristic of predetermined type for said seventh cnxpt;

wherein a irxt termed an enclosed information resource irxt is generated for each value of said name value pair that is an information resource;

forming a part-of relationship info-item of a predetermined type and of a predetermined weight between said enclosed information resource irxt and said source object provenance authority irxt if existing; and

marking said enclosed information resource irxt by the identity of said provenance authority fxxt if said fxxt is not already assigned to said enclosed information resource irxt;

wherein all info-items generated from said source object are assigned said source object provenance authority fxxt, and;

if a predetermined system parameter is set to a predetermined value, said information resource is stored outside of said commonplace rather than as a property of said cnxpt;

wherein each relationship between said name value pair as identified by a value containing a foreign key reference to a different name value pair in the data set is translated into a new relationship info-item of predetermined type and predetermined weight and like directionality between said seventh cnxpt and the cnxpt stemming from said different name value pair, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item, all info-items generated from said source object are assigned said source object provenance authority fxxt;

said seventh cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said seventh cnxpt;

said seventh cnxpt to be used as a curation control base for said name value pair;

said seventh cnxpt to represent the concept represented by said name value pair;

said seventh cnxpt termed a source data name value pair description authority cnxpt;

q. generating, if said source object contains one or more unstructured data set elements of the nature of information resource and if a predetermined system parameter is set to a predetermined value, for each information resource in the set for which an eighth irxt to represent said information resource has been generated previously;

if a predetermined system parameter is set to a predetermined value, an update of said irxt to note a found source, different location, version, or content difference;

each said eighth irxt to additionally reference said source object provenance authority source info-item;

wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said eighth irxt and said source object provenance authority irxt if said source object provenance authority irxt exists and if no such relationship info-item already exists between said eighth irxt and said source object provenance authority irxt;

each said eighth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth irxt;

said eighth irxt termed an enclosed information resource irxt;

r. generating, if said source object contains one or more unstructured data set elements of the nature of information resource and if a predetermined system parameter is set to a predetermined value, for each information resource in the set for which no irxt has been generated an eighth irxt to represent said information resource said eighth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said source object, and the descriptive information of said information resource;

said eighth irxt given properties filled by a predetermined set of elements selected from the group of;

said information resource'"'"'s identity, said source object'"'"'s authority, usability, quality, and expertise of originator, citation, uniform resource locator, international standard book number, and said information resource'"'"'s descriptive information;

each said eighth irxt to reference said source object provenance authority source info-item;

wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said eighth irxt and said source object provenance authority irxt if existing;

each said eighth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth irxt;

said eighth irxt termed an enclosed information resource irxt;

s. generating, if said source object contains one or more unstructured data information resources for which an enclosed information resource irxt was generated or previously existed, for each such enclosed information resource in the set for which an eighth cnxpt to represent the concept embodied in said enclosed information resource was previously generated an occurrence attached to said eighth cnxpt;

a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt;

said eighth cnxpt given additional properties filled by a predetermined set of elements from the descriptive information of said source object'"'"'s authority;

wherein, if no such equal relationship info-item exists, a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source object level cnxpt if existing;

wherein, if no such equal relationship info-item exists and if said enclosed information resource was within a table, a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source data table description authority cnxpt if existing;

wherein, if no such equal relationship info-item exists and if said enclosed information resource was within a table row, a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source data table row description authority cnxpt if existing;

said eighth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth cnxpt;

said eighth cnxpt to be used as a curation control base for said enclosed information resource;

said eighth cnxpt to represent the concept represented by said enclosed information resource;

said eighth cnxpt termed a source data enclosed information resource description authority cnxpt;

t. generating, if said source object contains one or more unstructured data information resources for which an enclosed information resource irxt was generated or previously existed, for each such enclosed information resource in the set for which no cnxpt has been generated an eighth cnxpt to represent the concept embodied in said enclosed information resource;

an occurrence attached to said eighth cnxpt;

a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt;

an additional occurrence attached to said eighth cnxpt;

a relationship info-item of a predetermined weight between said additional occurrence and said enclosed information resource irxt;

said eighth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

said source object identity indicator and unique identity indicators of said enclosed information resource, accommodating multiple instances of enclosed information resources having the same name;

said eighth cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said source object'"'"'s authority, a citation, and descriptive information of said enclosed information resource;

wherein a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source object level cnxpt if existing;

wherein, if said enclosed information resource was within a table, a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source data table description authority cnxpt if existing;

wherein, if said enclosed information resource was within a table row, a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said eighth cnxpt and said source data table row description authority cnxpt if existing;

said eighth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth cnxpt;

said eighth cnxpt to be used as a curation control base for said enclosed information resource;

said eighth cnxpt to represent the concept represented by said enclosed information resource;

said eighth cnxpt termed a source data enclosed information resource description authority cnxpt;

u. generating, if said source object contains one or more structured data set tables of the nature of rows of identifiable entity instances with identifiable associated attributes and if a predetermined system parameter is set to a predetermined value, for each data rule in the set a ninth irxt to represent as an information resource said data rule said ninth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said source object, and the descriptive information of said data rule;

said ninth irxt given properties filled by a predetermined set of elements selected from the group of;

said data rule'"'"'s identity, the descriptive information of said data rule, said source object'"'"'s authority, usability, quality, row identity, and expertise of originator, and said source object'"'"'s descriptive information;

each said ninth irxt to reference said source object provenance authority source info-item;

wherein a part-of relationship info-item of a predetermined type and of a predetermined weight is generated between said ninth irxt and said source object provenance authority irxt if existing;

each said ninth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said ninth irxt;

said ninth irxt termed a source data rule information resource irxt;

v. extracting, if said source object is a structured data set having data set elements, all data rule descriptions of said source object to generate, for each a concept represented by a ninth cnxpt to represent said data rule, and an occurrence attached to said ninth cnxpt;

a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt;

said ninth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

said source object identity indicator and unique identity indicators of said data rule, accommodating multiple instances of data rules having the same name;

said ninth cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said source object'"'"'s authority and descriptive information of said data rule;

wherein a child to parent relationship info-item of a predetermined type and predetermined weight is generated between said ninth cnxpt and said source object level cnxpt if existing;

wherein an additional occurrence is attached to said ninth cnxpt if said source data rule information resource irxt exists for said data rule and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight is also formed between said additional occurrence and said source data rule information resource irxt if existing;

wherein each said data rule of said source object data set is translated into a characteristic of predetermined type for said ninth cnxpt;

wherein for each entity or table said data rule references a new constraint relationship info-item of predetermined type and predetermined weight is formed between said ninth cnxpt as child and the cnxpt stemming from said entity or table as parent if one exists, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item, all info-items generated from said source object are assigned said source object provenance authority fxxt, termed an enclosed information resource irxt is generated for each value of said data rule that is an information resource;

wherein for each column or attribute said data rule references a new constraint relationship info-item of predetermined type and predetermined weight is formed between said ninth cnxpt as child and the cnxpt stemming from said column or attribute as parent if one exists, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item, all info-items generated from said source object are assigned said source object provenance authority fxxt, termed an enclosed information resource irxt is generated for each value of said data rule that is an information resource;

said ninth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said ninth cnxpt;

said ninth cnxpt to be used as a curation reference base for said data rule;

said ninth cnxpt to represent the concept represented by said data rule;

said ninth cnxpt termed a source data rule authority cnxpt;

w. generating, if said source object contains one or more unstructured data information resources for which an enclosed information resource irxt was generated or previously existed;

for each such enclosed information resource in the set for which an identifiable citation exists that has not been extracted, extracting, for each un-extracted identifiable citation selected from the group of;

standard citation, non-standard but identifiable citation, uniform resource locator, case citation, international standard book number, other cross reference, and link identifiable as a citation;

wherein a predetermined system parameter is set to a predetermined value and no irxt has been generated for the information resource cited, generate an eleventh irxt to represent said information resource cited;

said eleventh irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

a name generated from the descriptive information of said source object, and the descriptive information of said information resource in said identifiable citation;

said eleventh irxt given properties filled by a predetermined set of elements selected from the group of;

said information resource'"'"'s identity, said source object'"'"'s authority, usability, quality, and expertise of originator, said identifiable citation, and said information resource'"'"'s descriptive information;

each said eleventh irxt to reference said source object provenance authority source info-item;

wherein a citing relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said element in said information resource is generated between said eleventh irxt and said source object provenance authority irxt if existing;

each said eleventh irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eleventh irxt;

said eleventh irxt termed a cited information resource irxt;

x. generating a citing irxt-irxt relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said element in said information resource between said enclosed information resource irxt and said eleventh irxt, marking said relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said relationship info-item;

y. imputing zero or more citing relationship info-items, said citing relationship info-items given a value of one or more types selected from the group of;

a predetermined type, a custom type, a selected type, a predetermined weight, a custom weight, a selected weight, a weight based upon the number of references found of said element in said information resource, a directionality between a citing source data enclosed information resource description authority cnxpt and a cited source data enclosed information resource description authority cnxpt according to imputation means, and a marking of said new citation relationship info-item by the identity of said provenance authority fxxt if said fxxt is not already assigned to said new citation relationship info-item;

z. generating, if said source object contains one or more enclosed information resources represented by an enclosed information resource irxt, a twelfth cnxpt to represent the topic for each identifiable topical element from said enclosed information resource, if no such cnxpt exists, or updating an existing twelfth cnxpt for said identifiable topical element;

said topical element selected from the group of;

word, phrase, string, time, purlieu, location, semantic feature, link, relationships to common target, locations in external categorizations, provenance, authority, element of law, jurisdiction, common context, title, data set name, table name, entity name, attribute name, section title, account, accounts payable item, accounts receivable item, address, agreement, answer, asset, attribute, author, bank, belief, benefits, bookmark, budget item, case, chapter title, character, citation, claim, classification category, communication, communication meta-data property, compensation, concept, concern, concordance entry, contact, context, cost, definition, description, diary entry, docket entry, document characterization, editor, endnote, estimate, event, evidentiary item description, expense, fact, figure, finding, footnote, goods, group, human resource, identity, index entry, informal citation, inventory control, inventory issuance, invoice, issue, journal entry, law, location, logistical detail, managed relationship, meaning, meta-data value, name, object, object meta-data, open question, opinion, orders, organization, originator, owner, page description, page text, participant, party, payroll, performance rating, person, position, precedent, prediction, price, products, project, projection, quality rating, quotation, quote, receipt, relationship description, request for information, request for proposal, requirement, reviewer, role, routing, rule, section text, section title, semantic token, service, shipment, shipping document, skill, statement, story, strategy, table, table of authorities entry, table of contents entry, table of figures entry, task, theory, thing, duration, equation, outcome, prediction, note, problem, reference, ordering, period, color, size, explicit differentiation, usage, proportion, assembly, subassembly, texture, pattern, instruction, placement, time, to do item, descriptive element, topic, type description, type identity, volume title, work effort, work requirement, and other descriptive term;

each said topical element to be used as a base for deriving commonalty and similarity scores for said source object; and

attaching an occurrence to said twelfth cnxpt, generating a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt of a predetermined weight based upon the number of references found of said element in said information resource;

said twelfth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group of;

said element type, said element name, said information resource identity indicator, said source object identity indicator, and said source object descriptive information;

said twelfth cnxpt given properties filled by a predetermined set of elements selected from the group of;

the descriptive information of said information resource, said source object'"'"'s authority and descriptive information, the location where the element was first identified in said information resource, and the information associated with the element identified;

wherein a child to parent relationship info-item of a predetermined type and of a predetermined weight based upon the number of references found of said element in said information resource is generated between said twelfth cnxpt and the source data enclosed information resource description authority cnxpt, if existing, generated for said information resource, or otherwise to said source object level cnxpt if existing;

wherein an additional occurrence is attached to said twelfth cnxpt if a source data table information resource irxt exists having a part-of relationship with said enclosed information resource irxt of said information resource defined in said source object, and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight based upon the number of references found of said element in said information resource is also formed between said additional occurrence and said source data table information resource irxt if existing, and if a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight is also formed between said twelfth cnxpt and the source data table description authority cnxpt, if existing, generated for the table for which said source data table information resource irxt was generated to represent;

wherein an additional occurrence is attached to said twelfth cnxpt if a source data table row information resource irxt exists having a part-of relationship with said enclosed information resource irxt of said information resource defined in said source object, and a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight based upon the number of references found of said element in said information resource is also formed between said additional occurrence and said source data table row information resource irxt if existing, and if a predetermined system parameter is set to a predetermined value, a relationship info-item of a predetermined weight is also formed between said twelfth cnxpt and the source data table row description authority cnxpt, if existing, generated for the table row for which said source data table row information resource irxt was generated to represent; and

, if a predetermined system parameter is set to a predetermined value, generating a thesaurus item for said topical element; and

, if a predetermined system parameter is set to a predetermined value, generating a concordance item for said topical element in a concordance for said information resource attached to said enclosed information resource irxt;

wherein all instances of said coding key cnxpt of a type are assigned a single fxxt based upon said source object provenance authority fxxt;

said twelfth cnxpt termed a coding key cnxpt;

aa. generating, for each identifiable instance of a cnxpt in said source object for which said commonplace holds no matching existing cnxpt, if a predetermined system parameter is set to a predetermined value, a new thirteenth cnxpt as if the information of said cnxpt in said source object had been added to said thirteenth cnxpt as votes from the originator of said source object with predetermined weights based upon authority of originator regarding the cntexxt wherein said thirteenth cnxpt is placed, and adding relationship info-items in said source object connecting to said cnxpt in said source object as relationship info-items in said commonplace, connecting to info-items existing in said commonplace if they match, or generating new thirteenth info-items to match said info-item in said source object as votes from the originator of said source object with predetermined weights based upon authority of originator regarding the context wherein said thirteenth info-item is added;

bb. generating, for each identifiable instance of a cnxpt in said source object for which said commonplace holds a matching existing cnxpt, if a predetermined system parameter is set to a predetermined value, an update of said existing cnxpt to note changes made to said matching existing cnxpt as votes from the originator of said source object with predetermined weights based upon authority of originator regarding said cnxpt;

cc. generating, for each identifiable instance of an info-item in said source object for which said commonplace holds no matching existing info-item, if a predetermined system parameter is set to a predetermined value, a new thirteenth info-item as if the information of said info-item in said source object had been added to said thirteenth info-item as votes from the originator of said source object with predetermined weights based upon authority of originator regarding the context wherein said thirteenth info-item is added, and adding relationship info-items in said source object connecting to said info-item in said source object as relationship info-items in said commonplace, connecting to info-items existing in said commonplace if they match, or generating new info-items to match said info-item in said source object as votes from the originator of said source object with predetermined weights based upon authority of originator regarding the context wherein said thirteenth info-item is added;

dd. generating, for each identifiable instance of an info-item in said source object for which said commonplace holds a matching existing info-item, if a predetermined system parameter is set to a predetermined value, an update of said existing info-item to note changes made to said matching existing info-item as votes from the originator of said source object with predetermined weights based upon authority of originator regarding said info-item;

ee. determining, where said request to locate and ingest a data source object stems from a search query specification step, relevance of said source object to a search objective stated as a search query specification step wherein said source object is a result set item in a search result set;

ff. determining pertinence of said source object for an alert generation rule of an alert specification wherein said source object is of a type applicable to said alert specification generation rule;

gg. initiating alerts, with attached description, wherein said source object is of a type applicable to said alert specification generation rule;

hh. initiating methodologies according to a methodology template wherein said source object is of a type applicable to said methodologies template;

ii. initiating workflows according to a workflow template wherein said source object is of a type applicable to said workflow template;

jj. determining pertinence of said source object for an alert generation rule of an alert specification wherein a cnxpt of a type applicable to said alert specification generation rule is generated from said source object;

kk. initiating alerts, with attached description, wherein a cnxpt of a type applicable to said alert specification generation rule is generated from said source object;

ll. initiating methodologies according to a methodology template wherein a cnxpt of a type applicable to said methodology template is generated from said source object

mm. initiating workflows according to said workflow template wherein a cnxpt of a type applicable to said workflow template is generated from said source object

nn. determining pertinence of said source object for an alert generation rule of an alert specification wherein a info-item of a type applicable to said alert specification generation rule is generated from said source object;

oo. initiating alerts, with attached description, wherein a info-item of a type applicable to said alert specification generation rule is generated from said source object;

pp. initiating methodologies according to a methodology template wherein a info-item of a type applicable to said methodology template is generated from said source object

qq. initiating workflows according to said workflow template wherein a info-item of a type applicable to said workflow template is generated from said source object;

rr. issuing a predetermined type of notice to a user that an information resource has been entered for which a manual work task is appropriate, said type of notice selected from the group of;

i. an attempt to add a source object failed and manual intervention or troubleshooting is necessary, wherein user has registered to receive intervention or troubleshooting tasks, if said user has not yet been alerted or has requested all alerts;

ii. a source object has been added for which manual review is necessary, wherein user has registered to receive review tasks for general source object ingesting, if said user has not yet been alerted or has requested all alerts;

iii. a structured data set source object has been added for which manual review is necessary, wherein user has registered to receive review tasks for structured data set source object ingesting, if said user has not yet been alerted or has requested all alerts;

iv. a status update, wherein user has registered to receive status updates for one or more ingesting tasks, if said user has not yet been alerted;

v. an information resource has been added for which manual review is necessary, wherein user has registered to receive information resource review tasks, if said user has not yet been alerted or has requested all alerts;

vi. to do list item generation for tracking a task needing effort in the system, if no such to do list item exists in any status;

vii. to do list item generation for tracking a task needing effort in the system for review or curation and alerting a responsible user of said to do list item, if no such to do list item exists in any status and if said user has not yet been alerted;

viii. initiation of a workflow and generation of a to do list item for tracking a workflow task needing effort in the system for review or curation, if no such workflow exists and if no such to do list item exists in any status;

ix. initiation of a workflow and a to do list item generation for tracking a workflow task needing effort in the system for review or curation and alerting a responsible user of said to do list item, if no such workflow exists and if no such to do list item exists in any status and if said user has not yet been alerted;

and

x. suggestion generation for altering topic subdivisions according to quantitative separation determination based upon interest and link analysis;

and

ss. recalculating workflow task effort, resource requirements, resource allocations, and schedule changes.

215. The method of claim 1, to add available data sets to a commonplace of information of improving scope and quality to integrate entities, further comprising:

a. collecting information into a data set to be compared against or added to said commonplace;

b. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

c. collecting all instances of said entity types from said commonplace and said data set to be considered as instances of a cnxpt type and considering them as having a single default fxxt during processing;

d. accepting a choice of one or more association types to be used as propositional associations for determining a categorization from the association info-item types having directionality and relating said entity types to be considered as instances of said cnxpt type either already existing within said commonplace or in said data set to prepare map appropriate to said use case;

e. collecting all associations to be used as a determinant of categorization wherein said associations have directionality and said association info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said associations to be added between said entity types to be considered as instances of said cnxpt type;

f. accepting a choice of one or more association types to be used as positioning associations for determining the positioning of cntexxts representing cnxpts in a map based upon concept similarity from the association info-item types indicating cnxpt similarity to prepare map appropriate to said use case;

g. collecting all associations to be used as a determinant of entity similarity wherein the association info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said associations to be added between said entity types to be considered as instances of said cnxpt type;

h. determining linkages between cnxpts according to integration mapping specifications of the determined fxxt specification basis to force an entity consolidation of said cnxpts for a particular use case;

i. accepting a choice of a metric between zero and one to be used as a threshold for combining cnxpts wherein when the threshold value is surpassed by the effective weight of a summary association info-item of said types to be used as a determinant of entity similarity the endpoint cnxpts will be considered to be the same entity instance;

j. considering said all associations to be used as a determinant of entity similarity to be between said instances of said cnxpt type;

k. considering said all associations to be used as a determinant of entity similarity between cnxpts to have said single default fxxt during processing;

l. determining weights of said all associations to be used as a determinant of entity similarity, wherein said associations already existing within said commonplace are retained and weights of said associations to be added are calculated as a coefficient specified by the user times the value given in an attribute present for said association info-item or a specified default value according to utilize collective consensus through vote tallying means;

m. determining effective weights for summary associations between cnxpts summarizing all associations to be used as a determinant of entity similarity between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

n. replacing any considered association info-item of endpoint count greater than two to an equivalent set of considered associations having an endpoint count of two;

o. considering said all associations to be used as a determinant of categorization to be between said instances of said cnxpt type;

p. considering said all associations to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

q. determining weights of said all associations to be used as a determinant of categorization, wherein said associations already existing within said commonplace are retained and weights of said associations to be added are calculated as a coefficient specified by the user times the value given in an attribute present for said association info-item or a specified default value according to utilize collective consensus through vote tallying means;

r. combining the endpoint cnxpts of said summary associations between cnxpts summarizing all associations to be used as a determinant of entity similarity where said metric between zero and one to be used as a threshold for combining cnxpts is surpassed by the effective weight of said summary association info-item of said types to be used as a determinant of entity similarity between said endpoint cnxpts to yield a set of distinguishable cnxpts wherein the set includes only the cnxpts not combined plus the cnxpts resulting from combination and to yield a revised collection of associations to be used as a determinant of categorization, wherein an endpoint of any said associations having a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

s. determining effective weights and directions for summary associations between said cnxpts of said cnxpt type summarizing all said revised collection of associations to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

t. extracting a spanning forest of cnxpts and interrelationships where each of said cnxpts of said cnxpt type are taken as categories and arranged based upon said summary associations according to map generation means;

and

u. reporting the structure of said spanning forest of cnxpts and interrelationships.

216. The method of claim 1 to also provide a management tool for document and data set ingesting with workflow assistance, wherein:

a. creating an info-item to represent a data source and assign an identity indicator value to identify said data source;

b. creating an info-item to represent a creator of said data source and assign an identity indicator value to identify said creator;

c. providing search query procedure templates for searching for source objects to determine relevance;

d. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

e. providing methodology and workflow templates for project management of searching for and reviewing source objects to determine relevance to a stated meaning or issue;

f. providing prediction analytics establishing commonalty and similarity scores for source objects, the prediction selected from the group of;

i. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group of;

specialized metrics, needed bias adjustment, needed outlier elimination, translation quality, degree of data repairing needed, cost of scripting to encode needed translations, cost of scripting to provide needed business rules, cost of resources necessary to enable needed additional discovery, cost of scripting to enforce by automatic business and quality detection rules, proportion of duplicates, width of diversity of data argument opinions, proportion of business rule violations, proportion of missing values, evaluation results of quality analytic, proportion of misaligned attributes, proportion of un-normalized values, and needed verification by domain experts according to utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

ii. computing a predicted weighted ranking of the likely relevance of said source object to a coding key cnxpt as specified;

and

iii. computing a predicted weighted rejection ranking of said source object according to rules for rejection for security rules;

g. defining a map;

h. generating a map instance for said map;

and

i. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to request a search for wisdom;

ii. to enter a fxxt specification involving extraction by meta-data and search queries to meet criteria for project;

iii. to accept a workflow task;

iv. to specify search query specifications, workflow task assignment and document passing specifics to meet criteria for project;

v. to initiate operation of data extraction, document management, and prediction analytics;

vi. to initiate continuing retrieval of source objects based on the criteria according to search query specifications;

vii. to establish a commonplace of information for purpose of a specific dispute or matter;

viii. to categorize source objects into workflow contexts;

ix. to register an opinion with quantification regarding quality metrics;

x. to register an assessment of whether a source object meets the constraints for a quality metric;

xi. to allocate resources according to specified workflow rules for assignment or workflow rules for task acceptance;

xii. to refine search query specifications, categorizations, and priorities for review;

xiii. to highlight to others a data argument issue due to the conceptual meaning of two or more similar concepts represented by cnxpts;

xiv. to specify pertinence prediction weightings;

xv. to notify a supervisory level regarding a data issue importance;

xvi. to specify details for workflow and categorizations by establishing contexts for work tasks represented by cnxpts and workflow transitions represented by relationships to meet criteria for project;

xvii. to alter a workflow based upon quality checks produced by workflow and methodology;

xviii. to alter a workflow based upon review of metrics produced by workflow and methodology;

xix. to generate a logical view, data set, or data analytics cube utilizing the categorization provided by a generated map and the results of a search query collectively termed a viewpoint, data arguing is resolved to a consensus, said categorization is appropriate to a domain of wisdom for a use case, use of different maps provides correlated categorization structuring of the same raw data, raw data is converted to consensus structured clean data and useful decision structures, various viewpoints form of correlative analysis base;

and

xx. to generate a report or data set of the data set catalog, provenance, access cost, consensus regarding data quality, and consensus regarding veracity of data making up said viewpoint.

217. The method of claim 1 to control the process of curation of duplicates and to also remove redundant data from said commonplace to improve operating efficiency, wherein:

a. compiling a set of opinions regarding the usefulness and accuracy of a first info-item;

b. determining whether a first info-item has the same meaning and the same characteristics as a second info-item of the same type in all fxxts or are equivalent to a specified standard;

c. tallying a consensus regarding said usefulness and accuracy of a first info-item;

and

d. performing an action to automatically or by approval of a user to remove information from said commonplace of information, said action selected from the group of;

i. combining said first and said second info-items having the same meaning;

ii. cleaning of data to eliminate information that makes no sense because of errors by users, typos, or nonsense entries by children or others, or is disconnected or unlinked by deletion of info-items found marked for deletion;

iii. cleaning of data to also eliminate duplicate information, or old, junk, backed up, off-topic, imprecise, or unnecessary data by deletion of info-items found marked for deletion;

iv. removing permanently zero or more redundant ttx instances, by application of one or more cleanup and summarization analytics, wherein marked fxxt of said redundant ttx instance is added as a marked fxxt on the ttx instance retained of each redundant pair of ttx instances found redundant, and wherein every relationship info-item having said redundant ttx instance as an endpoint is altered to have said ttx instance retained of each redundant pair of ttx instances found redundant as that endpoint;

v. removing permanently, by application of one or more cleanup and summarization analytics, zero or more redundant relationship info-items wherein the endpoints of said redundant relationship info-item match the endpoints of a second relationship info-item and all type and fxxt information of said redundant relationship info-item match all type and fxxt information of said second relationship info-item, combining relationship info-item weights and authority metrics according to a predetermined formula and assigning said metrics to the relationship info-item retained of each redundant pair of said relationship info-items found redundant;

vi. detecting that two siblings in a sibling cnxpt pair are no more distant then the minimal separation according to the between-category repulsor tensor as applied in a cntexxt represented by a cnxpt in a co-location map, wherein the separation between said siblings in a sibling cnxpt pair would be lower than the object distance minimum constraint if said tensor was not applied, wherein the intersection of said siblings in a sibling cnxpt pair is attributed to the parent and the differences defining the child cnxpts in the categorization forming said co-location map, indicates that said sibling cnxpt pair includes two very similar concepts, said map generated according to said application software map generation means;

vii. issuing a predetermined type of notice to a user that a differentiation between a pair of ttx terms, or coding key cnxpts, being examined for similarity illustration is smaller than a metric specified by a predefined system preference setting having a predefined value, the appropriateness of said notice determined by, wherein;

01. accepting zero or more prioritization choices of one or more of term ttx instance pair ttxs for meaning similarity illustration;

02. marking, considering any prioritization choices by a user, a term ttx instance pair for similarity illustration during continuous processing or, if sufficient resources are available and prioritized, immediate processing;

03. marking each ttx of said term ttx instance pair as a cnxpt for the purpose of similarity illustration;

04. mark all instances of similarity associations and term ttx meaning hierarchy associations having one or more of said chosen term ttx instances as endpoints as having said fxxt for the purpose of the instant similarity illustration;

05. mark all cnxpts serving as endpoints of similarity associations and term ttx meaning hierarchy associations marked with said fxxt for the purpose of the instant similarity illustration to also belong to said fxxt for the purpose of the instant similarity illustration;

06. broadening the illustration of similarity, to a predetermined degree of association distance by including into said fxxt additional instances of similarity associations and term ttx meaning hierarchy associations having one or more of said marked term cnxpts as endpoints and marking said instances of similarity associations and term ttx meaning hierarchy associations as having said fxxt for the purpose of the instant similarity illustration, and then marking all cnxpts serving as endpoints of said newly marked associations as also having said fxxt for the purpose of the instant similarity illustration;

and

07. determining effective weights and directions for summary associations between said cnxpts of said cnxpt type summarizing all associations to be used as a determinant of differentiation between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

viii. issuing a predetermined type of notice to a user that a differentiation between said sibling cnxpt pair cnxpts is appropriate to more clearly define the categorization, said type of notice selected from the group of;

01. ttx match indication to a user viewing said co-location map wherein said siblings in a sibling cnxpt pair are highlighted or otherwise indicated to direct a user'"'"'s attention to said very similar concepts;

02. ttx match alert generation to a user viewing said co-location map wherein user has registered to receive ttx match alerts, if said user has not yet been alerted or has requested all alerts;

03. to do list item generation for tracking a task needing effort in the system for curation of redundant cnxpts, if no such to do list item exists in any status;

04. to do list item generation for tracking a task needing effort in the system for curation of redundant cnxpts and alerting a responsible user of said to do list item, if no such to do list item exists in any status and if said user has not yet been alerted;

05. initiation of a workflow and generation of a to do list item for tracking a workflow task needing effort in the system for curation of redundant cnxpts, if no such workflow exists and if no such to do list item exists in any status;

06. initiation of a workflow and a to do list item generation for tracking a workflow task needing effort in the system for curation of redundant cnxpts and alerting a responsible user of said to do list item, if no such workflow exists and if no such to do list item exists in any status and if said user has not yet been alerted;

and

07. suggestion generation for altering topic subdivisions according to quantitative separation determination based upon interest and link analysis;

ix. accepting a command selected from the group of;

01. a command from a user expressing a belief that an info-item should be deleted and generating a vote accordingly;

02. a command from a user expressing a belief regarding whether an info-item represents a real world counterpart that will ever be real and generating a vote accordingly;

and

03. a command from a user expressing a belief that an info-item has veracity of a low level and generating a vote accordingly;

and

x. locating, according to continuous processing means and a system preference setting, a first info-item meeting a condition selected from the group of;

01. having a value determined by an analytic executed according to consensus determination means because of a system preference setting to trigger action by the analytic to cause the entering of an analytic vote for deletion of said first info-item when a second info-item is determined by said analytic to be identical to a sufficient level according to said value and said second info-item has all characteristics equivalent to all characteristics of said first info-item or is given the characteristics resulting from a combining algorithm of said analytic by action of the analytic;

02. having a value determined by an analytic executed according to consensus determination means because of a system preference setting to trigger action by the analytic to cause the entering of an analytic vote for deletion of said first info-item when said value is below an analytic threshold setting a minimum metric, or a vote for retention when said value is equal to or above said minimum metric;

03. having a relative degree of interest level value determined by an analytic executed according to interest summarization means because of a system preference setting to trigger action by the analytic to cause the entering of an analytic vote for deletion of said first info-item when said interest level value is below an analytic threshold setting a minimum metric, or a vote for retention when said value is equal to or above said minimum metric;

04. having a value determined according to consensus determination means concerning veracity wherein said value is below a threshold setting a minimum metric for which veracity is considered sufficient for an info-item of the type of said first info-item to be retained in said commonplace and performing an action selected from the group of;

wherein said system preference is false, not set, or is not implemented, deleting said first info-item; and

wherein otherwise, entering a system vote for deletion of said first info-item accordingly;

05. having a value determined according to existence vote summarization means concerning existence wherein said value is below a threshold setting a minimum metric for which existence is considered sufficient for an info-item of the type of said first info-item to be retained in said commonplace and performing an action selected from the group of;

wherein said system preference is false, not set, or is not implemented, deleting said first info-item; and

wherein otherwise, entering a system vote for deletion of said first info-item accordingly;

and

06. having a value determined according to consensus determination means concerning the belief that said first info-item should be deleted wherein said value is above a threshold setting a maximum metric considered sufficient to indicate a generally held belief that an info-item of the type of said first info-item should no longer be retained in said commonplace and deleting said first info-item.

218. The method of claim 1, to extract concepts of imprecise identity with similar meanings into sets based upon categorization fuzziness from a commonplace of information, further comprising:

a. collecting all associations to be used as a determinant of categorization wherein said associations have directionality and said association already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said associations to be added between said entity types to be considered as instances of said cnxpt type, said associations termed hierarchical associations;

b. considering said all associations to be used as a determinant of categorization between said cnxpt type, said associations termed hierarchical associations;

c. considering said all associations to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing, said associations termed hierarchical associations;

d. determining weights of said all associations to be used as a determinant of categorization wherein said associations already existing within said commonplace are retained and weights of said associations to be added are calculated as a coefficient specified by the user times the value given in an attribute present for said association or a specified default value according to utilize collective consensus through vote tallying means;

e. replacing any considered association of endpoint count greater than two to an equivalent set of considered associations having an endpoint count of two;

f. determining effective weights and directions for summary associations between said cnxpts of said cnxpt type summarizing all associations to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

g. determining weights of said all associations to be used as a determinant of categorization wherein said associations already existing within said commonplace are retained and weights of said associations to be added are calculated as a coefficient specified by the user times the value given in an attribute present for said association or a specified default value according to utilize collective consensus through vote tallying means;

h. combining the endpoint cnxpts of said summary associations between cnxpts summarizing all associations to be used as a determinant of entity similarity where said metric between zero and one to be used as a threshold for combining cnxpts is surpassed by the effective weight of said summary association of said types to be used as a determinant of entity similarity between said endpoint cnxpts to yield a set of distinguishable cnxpts wherein the set includes only the cnxpts not combined plus the cnxpts resulting from combination and to yield a revised collection of associations to be used as a determinant of categorization wherein an endpoint of any said associations having is a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

i. determining effective weights and directions for summary associations between said cnxpts of said cnxpt type summarizing all said revised collection of associations to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

j determining, by at least one processor, at least one user display visualization according to map generation means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

k. displaying to said user a portion of said organization of knowledge of at least one domain of wisdom is according to display and delivery means;

l. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect change;

iii. to navigate around an organization of knowledge of said commonplace;

and

iv. to request a search for wisdom;

m. comparing exported data sets to ensure the consistency of reloaded data, for the elimination of re-classified records;

n. creating a cnxpt for the ttx which is at the top of the taxonomy;

o. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group of;

specialized metrics, needed bias adjustment, needed outlier elimination, translation quality, degree of data repairing needed, cost of scripting to encode needed translations, cost of scripting to provide needed business rules, cost of resources necessary to enable needed additional discovery, cost of scripting to enforce by automatic business and quality detection rules, proportion of duplicates, width of diversity of data argument opinions, proportion of business rule violations, proportion of missing values, evaluation results of quality analytic, proportion of misaligned attributes, proportion of un-normalized values, and needed verification by domain experts;

p. calculating quality corrections according to a prediction correction mechanism selected from the group of;

i. the way that people think is inherently fuzzy. the way that we perceive the world is continually changing and to categorize by manual culling of said source object according to concepts and contexts as represented by existing cnxpt;

ii. to categorize by manual culling to re-prioritize said source object for further review according to pre-specified workflow rules or to remove said source object from further review or from a collection of source objects in said commonplace of information;

iii. to argue constructively about the meaning of a concept represented by a cnxpt by registering zero or more votes stating a suggested textual definition of said concept'"'"'s meaning in descriptive information or an identity indicator of a cnxpt;

iv. to argue constructively about the meaning of a concept represented by a cnxpt by registering a vote regarding the proper contextual placement of said cnxpt'"'"'s meaning within a categorization of such meanings;

v. to argue constructively about the meaning of a concept represented by a cnxpt by registering a vote regarding values of characteristics of said cnxpt;

vi. to argue constructively about the meaning of a concept represented by a cnxpt by registering against said cnxpt a ranking stating an opinion regarding the relevance of an information resource or internal resource serving as an information resource to said cnxpt;

vii. to argue constructively about the relatedness of a first concept represented by a first cnxpt to a second concept represented by a second cnxpt by registering a vote that said relatedness should be noted in said commonplace by a predetermined type of association from said first cnxpt to said second cnxpt;

viii. to register a vote that a concept should or should not exist in said commonplace;

ix. to generate a logical view, data set, or data analytics cube utilizing the categorization provided by a generated map and the results of a search query collectively termed a viewpoint, wherein data arguing is resolved to a consensus, wherein said categorization is appropriate to a domain of wisdom for a use case, wherein use of different maps provides correlated categorization structuring of the same raw data, wherein raw data is converted to consensus structured clean data and useful decision structures, wherein various viewpoints form of correlative analysis base;

x. to generate a report or data set of the data set catalog, provenance, access cost, consensus regarding data quality, and consensus regarding veracity of data making up said viewpoint;

xi. to generate a logical view, data set, or data analytics cube utilizing the categorization provided by a generated map and the results of a search query collectively termed a viewpoint, wherein data arguing is resolved to a consensus, wherein said categorization is appropriate to a domain of wisdom for a use case, wherein use of different maps provides correlated categorization structuring of the same raw data, wherein raw data is converted to consensus structured clean data and useful decision structures, wherein various viewpoints form of correlative analysis base;

xii. to generate a report or data set of the data set catalog, provenance, access cost, consensus regarding data quality, and consensus regarding veracity of data making up said viewpoint;

xiii. to highlight to others a data argument issue due to the conceptual meaning of two or more similar concepts represented by cnxpts;

xiv. to specify pertinence prediction weightings;

xv. to notify a supervisory level regarding a data issue importance;

xvi. to specify details for workflow structure and categorizations by establishing contexts for work tasks represented by cnxpts and workflow transitions represented by associations to meet criteria for project;

xvii. to alter a workflow based upon quality checks produced by workflow and methodology;

xviii. to alter a workflow based upon review of metrics produced by workflow and methodology;

and

xix. to generate a logical view, data set, or data analytics cube utilizing the categorization provided by a generated map and the results of a search query collectively termed a viewpoint, wherein data arguing is resolved to a consensus, wherein said categorization is appropriate to a domain of wisdom for a use case, wherein use of different maps provides correlated categorization structuring of the same raw data, wherein raw data is converted to consensus structured clean data and useful decision structures, wherein various viewpoints form of correlative analysis base;

q. removing permanently zero or more redundant ttx instances, by application of one or more cleanup and summarization analytics, wherein marked fxxt of said redundant ttx instance is added as a marked fxxt on the ttx instance retained of each redundant pair of ttx instances found redundant, and wherein every association having said redundant ttx instance as an endpoint is altered to have said ttx instance retained of each redundant pair of ttx instances found redundant as that endpoint;

r. removing permanently, by application of one or more cleanup and summarization analytics, zero or more redundant associations wherein the endpoints of said redundant association match the endpoints of a second association and all type and fxxt information of said redundant association match all type and fxxt information of said second association, combining association weights and authority metrics according to a predetermined formula and assigning said metrics to the association retained of each redundant pair of said associations found redundant;

s. detecting that two siblings in a sibling cnxpt pair are no more distant then the minimal separation according to the between-category repulsor tensor as applied in a cntexxt represented by a cnxpt in a co-location map, wherein the separation between said siblings in a sibling cnxpt pair would be lower than the object distance minimum constraint if said tensor was not applied, wherein the intersection of said siblings in a sibling cnxpt pair is attributed to the parent and the differences defining the child cnxpts in the categorization forming said co-location map, indicates that said sibling cnxpt pair includes two very similar concepts, said map generated according to said application software map generation means;

t. issuing a predetermined type of notice to a user that a differentiation between a pair of ttx terms, or coding key cnxpts, being examined for similarity illustration is smaller than a metric specified by a predefined system preference setting having a predefined value, appropriateness of said notice determined, further including;

i. accepting zero or more prioritization choices of one or more of term ttx instance pair ttxs for meaning similarity illustration;

ii. marking, considering any prioritization choices by a user, a term ttx instance pair for similarity illustration during continuous processing or, if sufficient resources are available and prioritized, immediate processing;

iii. marking each ttx of said term ttx instance pair as a cnxpt for the purpose of similarity illustration;

iv. mark all instances of similarity associations and term ttx meaning hierarchy associations having one or more of said chosen term ttx instances as endpoints as having said fxxt for the purpose of the instant similarity illustration;

v. mark all cnxpts serving as endpoints of similarity associations and term ttx meaning hierarchy associations marked with said fxxt for the purpose of the instant similarity illustration to also belong to said fxxt for the purpose of the instant similarity illustration;

vi. broadening the illustration of similarity, to a predetermined degree of association distance by including into said fxxt additional instances of similarity associations and term ttx meaning hierarchy associations having one or more of said marked term cnxpts as endpoints and marking said instances of similarity associations and term ttx meaning hierarchy associations as having said fxxt for the purpose of the instant similarity illustration, and then marking all cnxpts serving as endpoints of said newly marked associations as also having said fxxt for the purpose of the instant similarity illustration;

and

vii. determining effective weights and directions for summary associations between said cnxpts of said cnxpt type summarizing all associations to be used as a determinant of differentiation between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying means;

and

u. issuing a predetermined type of notice to a user that a differentiation between said sibling cnxpt pair cnxpts is appropriate to more clearly define the categorization, said type of notice selected from the group of;

i. ttx match indication to a user viewing said co-location map wherein said siblings in a sibling cnxpt pair are highlighted or otherwise indicated to direct a user'"'"'s attention to said very similar concepts;

and

ii. ttx match alert generation to a user viewing said co-location map wherein user has registered to receive ttx match alerts, if said user has not yet been alerted or has requested all alerts.

219. The method of claim 1 to also provide a managed ingestion mechanism with quality improvement, further comprising:

a. providing coordinated access to data extraction analytics for carrying out computer database searching, data extraction, transformation, translation, and loading;

b. providing coordinated access to document management analytics for controlling, storing, accessing, and displaying electronically stored information resource documents;

c. generating a map to prepare at least one consensus organization of knowledge of at least one domain of wisdom including a source object provenance authority fxxt and also includes any additional portion of said commonplace against which categorization or comparison or curation is to occur;

d. displaying to said user a portion of said commonplace according to display and delivery means;

e. providing one or more quality improving functions selected from the group of;

i. providing task management and document management analytics for controlling workflows, determining scheduling based upon workflow priorities, and suggesting task assignments;

ii. ingesting a plurality of source objects;

iii. initiating continuous extraction of each source object'"'"'s identity, descriptive information, origination, and provenance meta-data to generate a source info-item with attached descriptive information, said type of source object selected from the group of;

an info-item from an external commonplace, a concept represented by a cnxpt from an external commonplace, data set, meta-data, file, information resource, statement, communication, template, legal decision, docket, story, transcript, and document;

said source info-item to be used as the authority control base for said source object and related to a new fxxt by a source relationship, said fxxt termed a source object provenance authority fxxt;

iv. initiating continuous extraction, for each source object that is a structured data set having data set elements, of all data set elements of said source object selected from the group of;

table description, entity type description, column description, attribute description, relationship info-item type descriptive information, table procedure description, object method description, and data rule description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said data set elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, wherein all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

v. initiating continuous extraction, for each source object that is a structured data set having data rules, of all data rule descriptions of said source object to generate, for each, a concept represented by a cnxpt with attached descriptive information, said cnxpt to be used as curation reference base, said cnxpt termed a source data rule authority cnxpt;

vi. initiating continuous extraction, for each source object that is unstructured data, of all descriptive elements of said source object selected from the group of;

object meta-data, citation, page description, foot or end note, volume title, section title, chapter title, book mark, section text, page text, type description, definition, index entry, table of contents entry, author, editor, table, figure, character, precedent, quotation, topic, issue, finding, opinion, and description;

to generate, for each, a concept represented by a cnxpt with attached descriptive information from said descriptive elements, said cnxpt to be used as a curation control base, said cnxpt termed a source data description authority cnxpt, wherein all instances of said source data description authority cnxpts are assigned a single fxxt related to said source obj ect provenance authority fxxt;

vii. initiating continuous extraction, for each source object that is unstructured data, a cited information resource irxt info-item for any information resource not existing in said commonplace of information;

viii. initiating continuous extraction of topical elements from said source object, said topical element selected from the group of;

term, timeframe, thing, feature, link, status, originator, event, party, participant, person, owner, address, location, organization, reviewer, rule, object, relationship info-item description, type identity, law, citation, claim, belief, strategy, concern, position, document characterization, communication, communication meta-data property, law, fact, statement, opinion, issue, theory, semantic token, name, statement, precedent, attribute, identity, evidentiary item description, concept, context, classification category, meta-data value, and other description;

each said topical element to be used as a base for deriving commonalty and similarity scores for said source object, wherein a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, wherein all instances of said coding key cnxpt of a type are assigned a single fxxt based upon said source object provenance authority fxxt and the type of coding key;

ix. determining relevance of said source object to a search objective stated as a search query specification step wherein said source object is a result set item in a search result set;

x. determining pertinence of said source object for a domain of wisdom extraction objective stated as a fxxt specification step wherein said source object is an info-item of any type applicable to said fxxt specification step;

xi. determining pertinence of said source obj ect for a prioritization rule of a methodology workflow specification step wherein said source object is an info-item of any type applicable to said methodology workflow specification step;

xii. determining pertinence of said source object for an alert generation rule of an alert specification wherein said source object is an info-item of any type applicable to said alert specification generation rule;

xiii. initiating requests for action, with attached description of action, to a user according to methodology workflow specification step;

xiv. initiating alerts, with attached description, to a user according to an alert specification generation rule;

xv. initiating methodologies according to said methodology templates;

xvi. initiating workflows according to said workflow templates;

xvii. providing search query procedure templates for searching for source objects to determine relevance;

xviii. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

xix. providing methodology and workflow templates for project management of searching for and reviewing source obj ects to determine relevance to a stated meaning or issue;

xx. providing prediction analytics establishing commonalty and similarity scores for source objects;

xxi. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group of;

specialized metrics, needed bias adjustment, needed outlier elimination, translation quality, degree of data repairing needed, cost of scripting to encode needed translations, cost of scripting to provide needed business rules, cost of resources necessary to enable needed additional discovery, cost of scripting to enforce by automatic business and quality detection rules, proportion of duplicates, width of diversity of data argument opinions, proportion of business rule violations, proportion of missing values, evaluation results of quality analytic, proportion of misaligned attributes, proportion of un-normalized values, and needed verification by domain experts;

xxii. computing a predicted weighted ranking of the likely relevance of said source object to a coding key cnxpt as specified;

and

xxiii. computing a predicted weighted rejection ranking of said source object according to rules for rejection for security rules;

and

f. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effecting change;

iii. to collect information into a data set to be compared against or added to said commonplace;

iv. to categorize by manual culling of said source object according to concepts and contexts as represented by existing cnxpt;

v. to categorize by manual culling to re-prioritize said source object for further review according to pre-specified workflow rules or to remove said source object from further review or from a collection of source objects in said commonplace of information;

vi. to argue constructively about the meaning of a concept represented by a cnxpt by registering zero or more votes stating a suggested textual definition of said concept'"'"'s meaning in descriptive information or an identity indicator of a cnxpt;

vii. to argue constructively about the meaning of a concept represented by a cnxpt by registering a vote regarding the proper contextual placement of said cnxpt'"'"'s meaning within a categorization of such meanings;

viii. to argue constructively about the meaning of a concept represented by a cnxpt by registering a vote regarding values of characteristics of said cnxpt;

ix. to argue constructively about the meaning of a concept represented by a cnxpt by registering against said cnxpt a ranking stating an opinion regarding the relevance of an information resource or internal resource serving as an information resource to said cnxpt;

x. to argue constructively about the relatedness of a first concept represented by a first cnxpt to a second concept represented by a second cnxpt by registering a vote that said relatedness should be noted in said commonplace by a predetermined type of relationship info-item from said first cnxpt to said second cnxpt;

xi. to register a vote that a concept should or should not exist in said commonplace;

xii. to navigate around a map of said commonplace;

xiii. to request a search for wisdom;

xiv. to enter a fxxt specification involving extraction by meta-data and search queries to meet criteria for project;

xv. to accept a workflow task;

xvi. to specify search query specifications, workflow task assignment and document passing specifics to meet criteria for project;

xvii. to initiate operation of data extraction, document management, and prediction analytics;

xviii. to initiate continuing retrieval of source objects based on the criteria according to search query specifications;

xix. to establish a commonplace of information for purpose of a specific dispute or matter;

xx. to categorize source objects into workflow contexts;

xxi. to register an opinion with quantification regarding quality metrics;

xxii. to register an assessment of whether a source object meets the constraints for a quality metric;

xxiii. to allocate resources according to specified workflow rules for assignment or workflow rules for task acceptance;

xxiv. to refine search query specifications, categorizations, and priorities for review;

xxv. to highlight to others a data argument issue due to the conceptual meaning of two or more similar concepts represented by cnxpts;

xxvi. to specify pertinence prediction weightings;

xxvii. to notify a supervisory level regarding a data issue importance;

xxviii. to specify details for workflow structure and categorizations by establishing contexts for work tasks represented by cnxpts and workflow transitions represented by relationships to meet criteria for project;

xxix. to alter a workflow based upon quality checks produced by workflow and methodology;

xxx. to alter a workflow based upon review of metrics produced by workflow and methodology;

xxxi. to generate a logical view, data set, or data analytics cube utilizing the categorization provided by a generated map and the results of a search query collectively termed a viewpoint, wherein data arguing is resolved to a consensus, wherein said categorization is appropriate to a domain of wisdom for a use case, wherein use of different maps provides correlated categorization structuring of the same raw data, wherein raw data is converted to consensus structured clean data and useful decision structures, wherein various viewpoints form of correlative analysis base;

and

xxxii. to generate a report or data set of the data set catalog, provenance, access cost, consensus regarding data quality, and consensus regarding veracity of data making up said viewpoint.

220. The method of claim 1 to also provide for accepting improvements of the knowledge models of said commonplace, further including:

a. accepting at least one improvement to said commonplace, the improvement selected from the group of;

i. adding an info-item instance to broaden the scope of said commonplace by adding objects;

ii. changing an existing info-item instance;

iii. merging a first existing info-item instance and a second existing info-item instance;

iv. deleting an existing info-item instance;

v. adding a relationship info-item instance between a first info-item instance and a second info-item instance;

vi. changing an existing relationship info-item instance;

vii. adding an association between a first cnxpt instance and a second cnxpt instance;

viii. changing an existing association between a first cnxpt instance and a second cnxpt instance;

ix. deleting an existing association between a first cnxpt instance and a second cnxpt instance;

x. adding a fxxt specification instance having zero or more ordered fxxt specification step instances to establish a repeatable procedure for extracting relevant sets of associations between cnxpts for a set purpose according to said fxxt specification;

xi. changing an existing fxxt specification instance;

xii. changing an existing fxxt specification procedure step instance;

xiii. deleting an existing fxxt specification instance;

xiv. deleting an existing fxxt specification procedure step instance;

xv. adding a fxxt marking to an association class;

xvi. changing an existing fxxt marking of an association class;

xvii. adding a fxxt marking to an association instance between a first cnxpt instance and a second cnxpt instance;

xviii. changing an existing fxxt marking of an association between a first cnxpt instance and a second cnxpt instance;

xix. adding a fxxt marking to an existing cnxpt class;

xx. changing an existing fxxt marking of a cnxpt class;

xxi. adding a fxxt marking to an existing cnxpt instance;

xxii. changing an existing fxxt marking of a cnxpt instance;

xxiii. deleting an existing fxxt marking of an association instance;

xxiv. deleting an existing fxxt marking of a cnxpt instance;

xxv. adding a fxxt marking to an existing info-item instance;

xxvi. changing an existing fxxt marking of an info-item instance;

xxvii. deleting an existing fxxt marking of an info-item instance;

xxviii. adding a fxxt reference for a map definition to establish a repeatable procedure for generating said map from, at least, info-item instances marked by said fxxt;

xxix. changing an existing fxxt reference for a map definition to alter a repeatable procedure for generating said map from info-item instances marked by said fxxt;

xxx. deleting an existing fxxt reference for a map definition to alter generation of said map;

xxxi. invoking a map build to generate a map instance according to a map definition;

xxxii. deleting a map instance;

xxxiii. adding a visualization specification for a map definition to establish a repeatable procedure for generating an instance of said visualization from an instance of said map;

xxxiv. changing an existing visualization specification for a map definition to establish a repeatable procedure for generating an instance of said visualization from an instance of said map;

xxxv. invoking a visualization build to generate a visualization instance according to a map instance;

xxxvi. deleting an existing visualization instance;

xxxvii. adding a vote instance regarding an existing info-item instance;

xxxviii. adding a new relationship info-item instance and a vote instance regarding existence of an associative relationship of a type represented by said relationship info-item instance by moving an object representing a first info-item instance into a second info-item instance wherein said first info-item instance and said second info-item instance become holders of roles in said relationship info-item instance;

xxxix. adding a vote instance regarding an existing relationship info-item instance by moving an object in a visualization representing an info-item instance holding a role in said relationship info-item instance in said commonplace, said vote stating a belief regarding a property of said relationship info-item selected from the group of;

existence of said relationship, strength of said relationship, direction of said relationship, type of said relationship, an attribute of said relationship, a feature of said relationship, a trait of said relationship, a display characteristic of said relationship, and a property of said relationship;

xl. adding a new association info-item instance and a vote instance regarding the existence of an associative relationship represented by said association info-item instance by moving a displayed object representing said first cnxpt info-item instance into a second cnxpt info-item instance wherein said first cnxpt info-item instance and said second cnxpt info-item instance become holders of roles in said association info-item instance;

xli. adding a vote instance regarding an existing association info-item instance by moving a displayed object representing a cnxpt info-item instance holding a role in said association info-item instance;

xlii. changing, by a first user, a vote instance added by said first user regarding an info-item instance;

xliii. deleting, by a first user, a vote instance added by said first user regarding an info-item instance;

xliv. adding a modeling property to an info-item instance;

xlv. adding a modeling property to become a class property on all cnxpt instances of a defined cnxpt class;

xlvi. changing an existing modeling property;

xlvii. deleting an existing modeling property;

xlviii. adding a modeling equation to an info-item instance;

xlix. adding a modeling equation to be applied as a class method to all cnxpt instances of a defined cnxpt class;

l. changing an existing modeling equation instance;

li. deleting an existing modeling equation instance;

lii. invoking a modeling run to generate modeling results according to a model held in a map instance;

liii. adding a methodology specification info-item instance having zero or more ordered methodology specification step info-item instances to establish guidelines for a procedure offered to users for adoption to accomplish at least one objective;

liv. changing an existing methodology specification info-item instance;

lv. deleting an existing methodology specification info-item instance;

lvi. changing an existing methodology specification procedure step info-item instance;

lvii. deleting an existing methodology specification procedure step info-item instance;

lviii. adding a workflow specification info-item instance having zero or more ordered workflow specification step info-item instances to establish a procedure to carry out, with optional adaptation;

lix. changing an existing workflow specification info-item instance;

lx. changing an existing workflow specification procedure step info-item instance;

lxi. invoking an existing workflow specification info-item instance to build a workflow instance;

lxii. updating an existing workflow instance to bring it current with the live workflow it represents;

lxiii. adding a flow definition info-item instance;

lxiv. changing an existing flow definition info-item instance;

lxv. invoking an existing flow definition info-item instance to instantiate a flow;

lxvi. updating an existing flow instance to bring it into sync with the live flow it represents;

lxvii. adding a definition info-item of a displayable map object;

lxviii. changing an existing map definition info-item instance;

lxix. deleting an existing map definition info-item instance;

lxx. adding an instance of a displayable map object to a visualization of said map;

lxxi. changing a displayable map object instance of visualization of said map;

lxxii. deleting a displayable map object instance;

lxxiii. adding an info-item type definition instance to broaden said scope of said commonplace by adding object types;

lxxiv. changing an existing info-item type definition instance;

lxxv. deleting an existing info-item type definition instance;

lxxvi. adding a commonality relationship definition info-item instance optionally with an enrolling of a heuristic software plug-in to generate relationship instances of such commonality relationships;

lxxvii. changing an existing commonality relationship definition info-item instance;

lxxviii. deleting an existing commonality relationship definition info-item instance;

lxxix. adding a commonality relationship instance;

lxxx. changing an existing commonality relationship instance;

lxxxi. deleting an existing commonality relationship instance;

lxxxii. invoking an existing heuristic software plug-in;

lxxxiii. adding an imputation definition info-item instance optionally with an enrolling of a heuristic software plug-in to perform such imputations;

lxxxiv. changing an existing imputation definition info-item instance;

lxxxv. adding an imputation instance;

lxxxvi. changing an existing imputation instance;

lxxxvii. deleting an existing imputation instance;

lxxxviii. invoking an existing imputation instance;

lxxxix. adding a query definition info-item instance;

xc. changing an existing query definition info-item instance;

xci. deleting an existing query definition info-item instance;

xcii. invoking an existing query definition to obtain a result set;

xciii. performing a culling of a result set produced from invoking an existing query definition;

xciv. refreshing an existing query definition to obtain a refreshed result set;

xcv. refreshing a culling of a result set produced from refreshing an existing query definition;

xcvi. deleting a result set;

xcvii. adding a communication definition instance regarding an info-item instance;

xcviii. changing an existing communication definition instance;

xcix. invoking a transmitting of an existing communication definition instance;

c. receiving a communication definition instance;

ci. deleting a communication definition instance;

cii. adding a consortium specification info-item instance having zero or more role definition instances to establish an organizational design to carry out tasks, with optional adaptation, and having zero or more documentation classes to establish an agreement for participation and set negotiation patterns for obtaining agreement, with optional adaptation;

ciii. changing an existing consortium specification info-item instance;

civ. changing an existing consortium specification role info-item instance;

cv. reporting a change in status for an existing consortium specification info-item instance, the status type selected from the group of;

task completion, objective completion, negotiation step completion, negotiation failure, negotiation success, documentation added, valuation change, ownership change, intellectual property status change, announcement, progress made, termination announcement, personnel change, funding status change, disagreement or dispute regarding reported information, agreement reached, advertisement, involvement in dispute, involvement in legal action, acceptance of investment, offer to enter investment pool, request or offer to graduate from investment pool, acceptance of request to graduate from investment pool, and public notice;

cvi. going live with an existing consortium specification info-item instance to initiate build-up of the consortium;

cvii. adding a communication info-item instance having zero or more document instances to establish a negotiation for a role and task plan to carry out work needed as participation, with optional adaptation;

cviii. updating an existing consortium instance to bring it current with the live organization it represents;

cix. adding an investment pool specification info-item instance having zero or more role definition instances to establish an organizational design to carry out tasks, with optional adaptation, and having zero or more documentation classes to establish an agreement for participation and set negotiation patterns for obtaining agreement, with optional adaptation;

cx. changing an existing investment pool specification info-item instance;

cxi. changing an existing investment pool specification role info-item instance;

cxii. reporting a change in status for an existing investment pool specification info-item instance, the status type selected from the group of;

funding announcement, negotiation step completion, negotiation failure, negotiation success, documentation added, valuation change, ownership change, intellectual property status change, announcement, progress made, termination announcement, personnel change, funding status change, disagreement or dispute regarding reported information, agreement reached, advertisement, involvement in dispute, involvement in legal action, acceptance of investment, offer made to enter investment pool, request made to graduate from investment pool, portfolio change, acceptance of request to graduate from investment pool, and public notice;

cxiii. going live with an existing investment pool specification info-item instance;

cxiv. adding a communication info-item instance having zero or more document instances to establish a negotiation milestone, with optional adaptation;

cxv. updating an existing investment pool instance to bring it current with the live organization it represents;

cxvi. adding an ingesting definition info-item instance optionally with an enrolling of a heuristic software plug-in to perform such ingesting;

cxvii. changing an existing ingesting definition info-item instance with an enrolling of a heuristic software plug-in to perform such ingesting;

cxviii. invoking an ingesting of information into said commonplace;

cxix. changing a description of an info-item;

cxx. changing a property of an info-item;

and

cxxi. changing an identifier of an info-item.

221. The method of claim 1 to also provide ability to add or change wisdom, wherein:

a. accepting and processing a request to add or change information by at least one interaction selected from the group of;

i. a non-contextually dependent request to add or change information by a command selected from the group of;

01. marking of information by a fxxt;

02. marking of information to be ingested and marked by a fxxt;

03. alteration of a fxxt;

04. adding or altering a map definition;

05. altering a map definition by adding or removing a fxxt reference;

06. altering a map definition by altering the weighting for a fxxt reference;

07. relating an information resource represented by an irxt instance to a ttx;

08. requesting, by a user, changes to information already in said commonplace of information;

09. requesting to ingest a source of data in record form and a sufficient query;

10. requesting to ingest a source of commonality data;

11. requesting to ingest a classification scheme for concepts;

12. requesting to ingest a source of categorizations of concepts;

13. requesting to ingest, from a source of the nature of machine learning, results of sets of similarities involving one or more types selected from the group of;

a set of similar documents, a set of similar media objects, a set of similar concept statements, a set of classified documents, a set of classified media objects, a set of classified concept statements, a set of relationships between documents, a set of relationships between media objects, a set of relationships between concept statements;

14. requesting to ingest a query against a source of objects and the objects found wherein the query states by its contents a concept;

15. requesting to ingest that a source of data to be crawled and a sufficient scoping of the crawl, the results to be ingested;

16. executing a query able to produce or refresh a result set of irxts, the irxts to be constructed to represent information resources located at an indicated source external to said commonplace of information;

17. ingesting a data batch of citation rich documentation;

18. requesting removal of an info-item authoritatively by an approved user anticipating that such a request will be considered immediately after appropriate transaction handling;

19. adding a cnxpt instance from a ttx instance where the ttx instance is believed by a user to represent a concept;

20. entering culling commands in manual review to change by elimination, addition, or reordering the items of a result set not related to a cnxpt;

and

21. accepting imputations of commonalities as associations, without contextual review of the associations;

and

ii. accepting a request by the user to position to a location in a map of said commonplace of information to set a context for adding or changing information and accepting a contextually dependent request to add or change information by a command selected from the group of;

01. adding or altering information conceived of by said user;

02. adding or altering relationships between ttxs added by said user;

03. adding or altering associations between cnxpt instances added or voted on by said user;

04. voting by said user regarding information in said commonplace of information stating a belief of a type selected from the group of;

correctness of information, importance of information, similarity between cnxpts within a perspective, and appropriateness of a description;

05. marking of information by a fxxt;

06. relating an information resource represented by an irxt instance to a ttx;

07. relating an information resource represented by an irxt instance to a cnxpt by creating an occurrence;

08. requesting, by a user, changes to information already in said commonplace of information;

09. requesting to ingest a query against a source of objects and the objects found wherein the query states by its contents a concept, the concept considered by the user to be related to a context represented by a cntexxt itself represented by a cnxpt, the concept to be made a cnxpt related to said cntexxt by a new hierarchical association;

10. executing a query able to produce or refresh a result set of irxts, the irxts to be constructed to represent information resources located at an indicated source external to said commonplace of information, the query related to a cnxpt;

11. voting to remove redundant knowledge of the form of a cnxpt, and anticipating that such a vote will be considered subsequently toward removing the knowledge;

12. voting to remove redundant knowledge of the form of an association, and anticipating that such a vote will be considered subsequently toward removing the knowledge;

13. adding a cnxpt instance from a ttx instance where the ttx instance is believed by a user to represent a concept, the concept considered by the user to be related to a context represented by a cntexxt itself represented by a cnxpt, the concept to be made a cnxpt related to said cntexxt by a new hierarchical association;

14. entering culling commands in manual review to change by elimination, addition, or reordering the items of a result set related to a cnxpt;

15. entering culling commands in manual review to change by elimination, addition, or reordering the items of an area of consideration or area of interest;

16. categorizing cnxpts within a perspective by moving cnxpts on a visualization wherein a vote for a new association between two cnxpts occurs when one is dropped onto or put into another, and a vote for changing an association between two cnxpts occurs when one cnxpt is dragged or taken out of a cnxpt serving as a cntexxt wherein the dragged cnxpt was representing a child or set member of the cntexxt;

and

17. accepting imputations of commonality as an association in the destination context of said association;

b. processing the addition or change request by said user;

and

c. processing any newly added or altered data to update maps, visualizations, result sets, or other artifacts derived from the newly added or altered data.

222. The method of claim 1, to make available investment opportunities for organizations developing technologies related to concepts within a commonplace of information, further comprising:

a. displaying to said user a portion of said organization of knowledge of at least one domain of wisdom according to display and delivery means;

b. forming a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt in one or more phases selected from the group of;

i. connection opportunity offered;

ii. connection requested;

iii. selecting an object of wisdom to act upon;

iv. requesting display of a result set for culling;

v. requesting making contact with a listed person, project consortia, or organization;

vi. requesting purchase of a listed item;

vii. scheduling participation;

viii. requesting investment in a listed project consortia, pool, or organization;

ix. stating an opinion;

x. stating status of a task;

xi. stating interest;

xii. offering an incentive;

xiii. offering a funding incentive;

xiv. requesting vetting information or access to vetting information;

xv. requesting consideration for funding;

xvi. stating an evaluation;

xvii. requesting consideration for pool graduation;

xviii. stating consortia formation;

xix. publicizing for consortia participation;

xx. negotiating for consortia participation;

xxi. negotiating for deliverable acceptance;

xxii. requesting display of a structural view of cntexxts based upon wisdom found;

and

xxiii. requesting the navigating to a cntexxt based upon wisdom found;

and

c. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect change;

iii. to navigate around a map of said commonplace;

and

iv. to request a search for wisdom.

223. The method of claim 1 to provide for searching in a knowledge tool, further comprising:

a. providing method for substantially loading information into the knowledge tool;

b. providing a method for substantially curating information in the knowledge tool, the method selected from the group of;

i. providing method for progressively curating data in continuous quality improvement process;

ii. empowering a diverse user set to curate according to their own expertise, interest, and knowledge;

iii. empowering a diverse user set to curate according to a plurality of their own perspectives;

iv. empowering a diverse user set to curate based upon data combined in multiple ways to expose issues not otherwise visible;

v. empowering a diverse user set to curate based upon data combined to overcome sparsity from overly small set of sources;

and

vi. empowering a diverse user set to curate based upon data combined to overcome sparsity a source;

c. providing a user a method to search for a concept in a circumstance selected from the group of;

i. providing a competitive analyst a method to search for competing technologies and determine their relative attributes;

ii. providing a portfolio tool for utilizing crowdsourced valuation information indexed by a custom categorization by a user of ownership information categorized within said commonplace of information, the categorization index optionally based upon work by another user;

iii. providing a product company a method to search for new product acquisitions;

iv. providing a subsumption learning apparatus to users;

v. providing a user a decision tree to lead through a roughly similar situation another user dealt with and tracked;

vi. providing a user a knowledge tool for rapidly understanding an area of knowledge substantially in the manner of learning;

vii. providing a user a knowledge tool for their learning;

viii. providing a user a method to determine a negotiating position in a phased exchange;

ix. providing a user a method to learn from what another person recently realized about a topic;

x. providing a user a method to obtain details regarding a concept;

xi. providing a user a method to obtain details regarding a technology;

xii. providing a user a method to obtain results of analyses by others regarding a concept;

xiii. providing a user a method to obtain results of analyses by others regarding a specific question and a method of assembly of the analysis toward a more complex issue;

xiv. providing a user a method to obtain results of analyses by others regarding a technology;

xv. providing a user a method to obtain results of analyses by others regarding a valuation of a property;

xvi. providing a user a method to obtain results of analyses by others with a collective assessment of the accuracy of the analysis;

xvii. providing a user a method to obtain the quality improvements made by others in the contents of the knowledge tool;

xviii. providing a user a method to participate in a negotiation to obtain a share of ownership in a property;

xix. providing a user a method to participate in a negotiations toward collaborative work;

xx. providing a user a source of ideas deep enough in detail to ensure comparability with an idea a user has in their mind;

xxi. providing a user a source of ideas organized enough to ensure efficiency in a search for a detailed concept a user has in their mind;

xxii. providing a user a source of ideas to improve innovation depth;

xxiii. providing a user a source of ideas to spur innovation in unconsidered directions;

xxiv. providing a user a source of ideas with enough different paths and detail to ensure comparability by each of a set of attributes of an idea that is multi-faceted or has any complexity;

xxv. providing a user a tool for entering a minimum amount of information to attract a following without exposing enough information to explain the topic by use of categorization;

xxvi. providing a user a workflow template to respond to a other party in a collaboration;

xxvii. providing a user a workflow to adopt roughly appropriate for responding to a situation where another user built one;

xxviii. providing a user with automatically harmonized categorizations;

xxix. providing an analyst a method to search for something exciting to discuss;

xxx. providing an automatic expository organization tool for direct use by learners;

xxxi. providing an individual a method to search for a new venture to participate in;

xxxii. providing an inventor a method to place a technology into an auction where bids could be solicited from interested others in a still un-described invention;

xxxiii. providing an inventor a method to search for a technology patently similar to an idea before the idea is exposed;

xxxiv. providing an inventor a method to search for a technology without substantially describing an invention;

xxxv. providing an inventor a method to search for a technology;

xxxvi. providing an investor a method to learn the history of the organization possibly being formed around an invention;

xxxvii. providing an inventor a method for building a track record online for presentation to investors;

xxxviii. providing an investor a method to search for new opportunities;

xxxix. providing an investor or interested purchaser to participate in an intellectual property auction;

xl. providing crowdsourced valuation information indexed by a custom categorization by a user of other information categorized within said commonplace of information, the categorization index optionally based upon work by another user;

xli. providing indexed information categorized within said commonplace of information;

xlii. providing information indexed by a custom categorization by a user of other information categorized within said commonplace of information, the categorization index based upon work by another user;

xliii. providing information indexed by a custom categorization by a user of other information categorized within said commonplace of information;

xliv. providing valuation information indexed by a custom categorization by a user of ownership information categorized within said commonplace of information;

xlv. providing crowdsourced linkage information at great levels of detail between a technology and a technological application context where the technology would satisfy a requirement of the application, each within said commonplace of information;

xlvi. providing crowdsourced competitive information at great levels of detail between a technology and another technology both able to satisfy the requirements of a technological application, each within said commonplace of information;

xlvii. providing crowdsourced timeframe based competitive valuation information at great levels of detail between a plurality of technologies able to satisfy the requirements of a one or more technological applications;

xlviii. comforting a user hitting roadblocks in use;

xlix. triggering a user to shift to slow thinking for concentrating on an area where interest, by user or others, is high in new analysis of detailed material;

l. inspiring a user during use, buy a method selected from the group of;

01. spurious information display for triggering concept associating;

02. wake-up triggers to reduce over-concentration;

and

03. breaking the continuity field of a user;

li. providing a user a knowledge tool for marking a detailed context about being an idea that may be of interest without describing the idea further to obtain an understanding of interest in the idea;

lii. providing a user a knowledge tool for marking a detailed context without describing the idea further as being an idea of interest to attract solutions matching the categorization surrounding the context;

liii. providing a user a knowledge tool for marking a detailed context without describing the idea further as being an idea that would probably be a solution for a technological application of interest to attract solutions matching the categorization surrounding the context and fulfilling requirements of the application;

liv. providing a user a knowledge tool for marking a detailed context in a plurality of categorizations, all said markings referring to the same idea without describing the idea further as being an idea that would probably be a solution for a technological application of interest to attract solutions matching the categorizations surrounding all of the said markings and fulfilling requirements of the application;

lv. providing a user a knowledge tool for marking a detailed context in one or more of a plurality of technical functional categorizations, all said markings referring to the same idea without describing the idea further as being an idea that would probably be a solution for a technological application to state an innovation;

lvi. providing a user a knowledge tool for marking a detailed context in one or more of a plurality of technical functional categorizations, all said markings referring to the same idea without describing the idea further as being an idea that would probably be a solution for a technological application to state an innovation and to form into an application substantially of the nature of a non-provisional patent application the contexts wherein the markings are made plus one sentence stating an innovation not stated as a description in the knowledge tool;

lvii. providing a user a knowledge tool for marking a detailed context in one or more of a plurality of technical functional categorizations, all said markings referring to the same idea without describing the idea further as being an idea that would probably be a solution for a technological application to state an innovation and to identify its prior art without regard to how distant into the future the applicability of the prior art would be before it became pertinent to the idea;

and

lviii. triggering a user to shift to fast thinking for increased readiness for creativity;

d. providing a user a method to collaborate in a circumstance selected from the group of;

i. obtaining and categorizing information;

ii. curation of entered information;

iii. indexing of information;

iv. building a model for determining the expectation of profitability timeframe;

v. running causality networks to project where technology was going and how an idea would match requirements of the applications of the future;

vi. predicting whether a business of an inventor could serve as a sufficiently strong development group based upon its collected business progress record;

vii. plan how an invention would be made competitive;

viii. plan how an invention would be integrated into a product line;

ix. forming estimates of cost of functionality;

x. forming estimates of product timing and rollout;

xi. curation of categorizations;

xii. improvement of searches of external sources and subsequent indexing;

xiii. harmonization of categorizations;

xiv. determining if an invention would be a good earner in the portfolio of an investor;

xv. securely and anonymously messaging by linking by a concept to show interest or seek information;

xvi. securely and anonymously negotiating with potential contributors to conduct information exchanges and signing agreements;

xvii. determining if an invention would be a good earner in a product portfolio;

xviii. ingesting patent and research paper files;

and

xix. crowdsourced machine learning supervision;

e. providing crowdsourced data of a type selected from the group of;

i. providing crowdsourced valuation information at great levels of detail indexed by a custom categorization of technological application contexts based upon information selected from the group of;

01. interest in the applications of the technology shown in the past;

02. interest shown in the applications of the technology on a projective basis over a large number of years into the future;

03. interest shown by investors;

04. the stages of development of products satisfying the applications;

05. the competitive postures of products satisfying the applications;

06. interest shown by foreign engineers;

07. estimates on precursor applications;

and

08. estimates on precursor technologies;

ii. with categorizations harmonized automatically and dynamically when accessed;

iii. results of machine learning;

iv. results of performing statistical analysis;

v. results of performing econometric analysis;

vi. requests for technology;

vii. collaborative strategic analysis;

viii. requests for intellectual property;

ix. found disclosures of intellectual property;

and

x. comments regarding technology on social websites;

and

f. providing a method for obtaining data of a type selected from the group of;

i. monitoring offers for sale or assignment of intellectual property;

ii. monitoring product companies offering their technologies for sale;

iii. monitoring open strategic analysis;

iv. monitoring tracking efforts regarding intellectual property by owners;

v. performing econometric analysis;

vi. automated search updates;

vii. crawling the web;

viii. ingesting patent and research documents;

ix. from associations wishing to sell their data for analysis;

x. performing machine learning;

xi. performing statistical analysis;

and

xii. monitoring failed searches.

224. The method of claim 1 to allow a user to act upon the information in the commonplace by using a map, further including:

a. accepting and processing zero or more user commands according to low level procedure models for use cases means, said command selected from the group of;

i. to add a category by adding a new context that is more accurate for the focus sought by subdividing the context;

ii. to remove a category;

iii. to create or delete a cnxpt;

iv. to create or delete a community txo occurrence relationship;

v. to create or delete a comxo info-item;

vi. to create or delete a custom affinitive association;

vii. to create or delete a custom hierarchical association;

viii. to create or delete a data set;

ix. to create or delete a direct information resource citation relationship;

x. to create or delete a fxxt;

xi. to create or delete a goal;

xii. to create or delete a map;

xiii. to create or delete a product info-item;

xiv. to create or delete a query info-item;

xv. to create or delete a query step specification;

xvi. to create or delete a register information request;

xvii. to create or delete a result set;

xviii. to create or delete a source;

xix. to create or delete a subject identifier occurrence relationship;

xx. to create or delete a trait relationship info-item occurrence relationship;

xxi. to create or delete a ttx citation association;

xxii. to create or delete a txo from a result set;

xxiii. to create or delete a user interest vote;

xxiv. to create or delete a user satisfaction vote;

xxv. to create or delete a user interest txo occurrence relationship;

xxvi. to create or delete an info-item;

xxvii. to create or delete an information resource citation relationship;

xxviii. to create or delete an irxt;

xxix. to create or delete an occurrence;

xxx. to create or delete an offer;

xxxi. to create or delete and position a cnxpt;

xxxii. to create or delete a visualization;

xxxiii. to create or delete an information item and occurrence;

xxxiv. to add wisdom;

xxxv. to add or change a description to a cnxpt;

xxxvi. to add a result set member to a cnxpt;

xxxvii. to add a result set member to a goal;

xxxviii. to add an information item and occurrence to a cnxpt;

xxxix. to assign an identity indicator to a cnxpt;

xl. to attach or detach a query info-item to a cnxpt;

xli. to attach or detach a query info-item to a goal;

xlii. to attach or detach a query to a cnxpt as children;

xliii. to attach or detach a query to a cnxpt as parents;

xliv. to attach or detach a query to a cnxpt as siblings;

xlv. to attach or detach a query to a goal;

xlvi. to attach or detach a result set info-item to a cnxpt;

xlvii. to attach or detach a result set info-item to a goal;

xlviii. to attach or detach a result set to a cnxpt as children;

xlix. to attach or detach a result set to a cnxpt as parents;

l. to attach or detach a result set to a cnxpt as siblings;

li. to attach or detach a result set to a goal as children;

lii. to attach or detach a result set to a goal as parents;

liii. to attach or detach a result set to a goal as siblings;

liv. to detach two info-items;

lv. to finalize a goal into a cnxpt;

lvi. to finalize a query for a cnxpt;

lvii. to name or rename an info-item;

lviii. to name or rename a visualization;

lix. to connect by a relationship info-item a first and a second cnxpt;

lx. to convert a data set to a result set;

lxi. to convert a result set to an area;

lxii. to convert a search or findall to a query;

lxiii. to convert a selection set to a result set;

lxiv. to convert an area to a result set;

lxv. to position a cnxpt;

lxvi. to alter a category;

lxvii. to categorizing a concept by causing a first cnxpt to become a member of the cntexxt of a second cnxpt;

lxviii. to categorizing a concept by fuzzy categorization by expressing personal indecision while causing a first cnxpt to become a member of the cntexxt of a second cnxpt with a fuzziness;

lxix. to remove a first cnxpt from membership in a cntexxt;

lxx. to specify information regarding an info item;

lxxi. to navigate between cnxpts;

lxxii. to search for wisdom;

lxxiii. to search for a concept represented by a cnxpt shown or not shown in the map;

lxxiv. to focus on a specific concept;

lxxv. to focus on an unspecified different concept;

lxxvi. to search associatively by navigating between cnxpts;

lxxvii. to focus on a specific dxo;

and

lxxviii. to request a different organization of knowledge;

wherein any addition, change, or deletion may affect stigmergy and is an addition of wisdom affecting said consensus.

225. The method of claim 1 to empower a user to act upon information in the commonplace by using a map interface to locate a context representing said information, further comprising:

a. accepting a command selected from the group of;

i. command to initiate display of a map visualization for a predetermined depiction;

ii. command to initiate display of different subject matter for generating a predetermined depiction;

iii. command to locate a cntexxt;

iv. command to locate a cnxpt;

v. command to locate an association;

vi. command to select a cntexxt to ready it for an action;

vii. command to select a cnxpt to ready it for an action;

viii. command to display information regarding a cntexxt;

ix. command to display information regarding a cnxpt;

x. command to change information regarding the cnxpt;

xi. command to highlight on the display those cnxpts similar to a selected cnxpt in a predetermined measure of similarity;

xii. command to display a list of information resources relevant to a cnxpt;

xiii. command to vote that a first cnxpt instance should be a child of a second cnxpt instance in a specific map by voting that an association should exist;

xiv. command to vote that a first cnxpt instance should not be a child of a second cnxpt instance in a specific map by voting that an association should exist;

xv. command to vote that a first cnxpt instance should be considered more similar to a second cnxpt instance in a specific map by voting that an association should exist but have a higher strength weighting;

xvi. command to vote that a first cnxpt instance should be considered less similar to a second cnxpt instance in a specific map by voting that an association should exist but have a lower strength weighting;

xvii. command to display information regarding the association between a first cnxpt and a second cnxpt;

and

xviii. command to change information regarding the association between a first cnxpt and a second cnxpt;

b. processing the entered command to focus on the context represented by a located cnxpt;

c. processing the entered command to act on said information of the cntexxt represented by the located cnxpt;

and

d. returning control to the user.

whereby a command causes a refocusing of a map instance to a context and then operate on information of the context.

226. The method of claim 1, by executing stored instructions that perform mapping operations to cause the computer system to locate wisdom sought, further including:

a. providing at least one invocation procedure to obtain wisdom, of a sequencing selected from the group of;

i. procedure for obtaining wisdom yielding a list of at least one cnxpt into a derived ontology, the procedure then initiating formation of a map from a map definition referencing a set of zero or more fxxts, wherein the procedure is of a type selected from the group of;

01. a search procedure for obtaining content for at least one domain of wisdom by one or more searches yielding a list of at least one cnxpt, the procedure then initiating a map formation procedure for a pre-determined map definition and passing the search results to the map formation procedure, wherein the searches are defined prior to invocation of said procedure for obtaining content, the assignment of formed map definition to search determined prior to invocation of said procedure for obtaining content;

and

02. a search procedure for obtaining content for at least two domains of wisdom by two or more searches yielding at least two lists of at least one cnxpt, the procedure then initiating a map formation procedure for each of at least two pre-determined map definitions and passing at least one of said at least two lists of at least one cnxpt as search results to each of the map formation procedures for each of at least two pre-determined map definitions for building said pre-determined map definitions, wherein the searches are defined prior to invocation of said procedure for obtaining content, the assignment of map definition to search determined prior to invocation of said procedure for obtaining content;

ii. auxiliary procedure for obtaining content for zero or more domains of wisdom by performing one or more searches each yielding a list of zero or more cnxpts and zero or more associations, the auxiliary procedure invokable by a map formation procedure, the auxiliary procedure referencing a set of zero or more fxxts, the result of the auxiliary procedure added into a derived ontology;

iii. follow procedure obtaining content for a domain of wisdom having a list of zero or more cnxpts and zero or more associations by invoking a connection to a map already formed to follow activity of that formed map, wherein the activity is of a type selected from the group of;

01. one or more changes are made in a map controlled by one or more other users;

02. one or more opinions are given in a predefined map having accessible comments;

03. a tour is given in a predefined map;

04. an explanation is given in a predefined map having accessible comments, the comments providing descriptions;

05. an accessible dialog is present for viewing in a map created previously;

06. an accessible dialog is present for viewing in a map currently controlled by one or more other users;

07. a story is given in a predefined map having dynamic content, the content augmented by predefined description;

and

08. a story is given in a predefined map having a tour, the tour augmented by predefined description;

iv. interconnect procedure obtaining content for a domain of wisdom having a list of zero or more cnxpts and zero or more associations by performing a connection to a map already formed to interact with that map;

v. research procedure for obtaining related information resources by an interactive request for collection under a topic represented by a parent ttx, the interactive request made to a search tool, the results of a type selected from the group of;

01. a result set attached to the parent ttx, the result set items attached to the ttx as occurrences;

02. a set of child ttxs fitted into the parent ttx, each child ttx representing a cluster for a subtopic of the topic represented by the parent ttx, the clusters determined from a clustering partitioning of a set of information resources automatically generated for grouping the information resources into topical clusters, each information resource in the set clustered associated with only one topical cluster, each information resource member found to be in a first cluster for a first topic represented by a first ttx listed in a result set attached to the first ttx representing the first topic of the first cluster, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition;

03. a set of child ttxs fitted into the parent ttx, each child ttx representing a partition for a subclass of the class represented by the parent ttx, the partitions determined from a partitioning of a set of information resources automatically generated for grouping the information resources into class-based partitions, each partition representing a subclass of the class of the parent ttx, each information resource in the set partitioned associated with only one class-based partition, each information resource member found to be in a first partition for a first topic represented by a first ttx listed in a first result set attached to the first ttx representing the first topic of the first partition, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition;

04. a set of child ttxs fitted into the parent ttx, each child ttx representing a setoid for a subset of the set represented by the parent ttx, the setoids determined from a partitioning of a set of information resources automatically generated for grouping the information resources into setoids, each setoid representing a subset of the set of the parent ttx, each information resource in the set partitioned associated with at least one setoid, each information resource member found to be in a first setoid for a first class represented by a first ttx listed in a first result set attached to the first ttx representing the first class of the first setoid, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first class of the first partition, the degree to which the information resource is associated with the first setoid retained with the occurrence;

05. a set of child ttxs fitted into the parent ttx, each child ttx representing a fuzzy cluster for a subtopic of the topic represented by the parent ttx, the fuzzy clusters determined from a fuzzy clustering of a set of information resources automatically generated for grouping the information resources into topical fuzzy clusters, each fuzzy cluster representing a subtopic of the topic of the parent ttx, each information resource in the set fuzzy clustered associated with at least one topical fuzzy cluster, each information resource member found to be in a first fuzzy cluster for a first topic represented by a first ttx listed in a result set attached to the first ttx representing the first topic of the first fuzzy cluster, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition, the degree to which the information resource is associated with the first fuzzy cluster retained with the occurrence;

06. a set of child ttxs representing information resource clusters fitted into the parent ttx, the clusters determined from a hierarchical clustering partitioning of a set of information resources automatically generated for grouping the information resources into topical clusters, each deeper hierarchical cluster representing a subtopic of its parent cluster, each information resource in the set clustered associated with only one topical cluster, each root of the hierarchical clustering forest represented by a child ttx fitting directly into the parent ttx and representing the topic of the root and the collection of deeper subtopic clusters included in the tree of the forest under the root, each deeper hierarchical cluster represented by a subtopic ttx fit into the ttx representing the parent topic of the subtopic, each information resource member found to be in a first cluster for a first topic represented by a first ttx listed in a result set attached to the first ttx representing the first topic of the first cluster, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition;

07. a set of child ttxs representing information resource partitions fitted into the parent ttx, the partitions determined from a hierarchical partitioning of a set of information resources automatically generated for grouping the information resources into topical partitions, each deeper hierarchical partition representing a subtopic of its parent partition, each information resource in the set partitioned associated with only one topical partition, each root of the hierarchical partitioning forest represented by a child ttx fitting directly into the parent ttx and representing the topic of the root and the collection of deeper subtopic partitions included in the tree of the forest under the root, each deeper hierarchical partition represented by a subtopic ttx fit into the ttx representing the parent topic of the subtopic, each information resource member found to be in a first partition for a first topic represented by a first ttx listed in a first result set attached to the first ttx representing the first topic of the first partition, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition;

08. a set of child ttxs representing information resource setoids fitted into the parent ttx, the setoids determined from a hierarchical partitioning of a set of information resources automatically generated for grouping the information resources into class-based setoids, each deeper hierarchical setoid representing a subclass of its parent setoid, each information resource in the set partitioned associated with at least one class-based setoid, each root of the hierarchical partitioning forest represented by a child ttx fitting directly into the parent ttx and representing the class of the root and the collection of deeper subclass setoids included in the tree of the forest under the root, each deeper hierarchical setoid represented by a subclass ttx fit into the ttx representing the parent class of the subclass, each information resource member found to be in a first setoid for a first class represented by a first ttx listed in a first result set attached to the first ttx representing the first class of the first setoid, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first class of the first partition, the degree to which the information resource is associated with the first setoid retained with the occurrence;

and

09. a set of child ttxs representing information resource fuzzy clusters fitted into the parent ttx, the fuzzy clusters determined from a hierarchical fuzzy clustering of a set of information resources automatically generated for grouping the information resources into class-based fuzzy clusters, each deeper hierarchical fuzzy cluster representing a subclass of its parent fuzzy cluster, each information resource in the set fuzzy clustered associated with at least one class-based fuzzy cluster, each root of the hierarchical fuzzy clustering forest represented by a child ttx fitting directly into the parent ttx and representing the class of the root and the collection of deeper subclass fuzzy clusters included in the tree of the forest under the root, each deeper hierarchical fuzzy cluster represented by a subclass ttx fit into the ttx representing the parent class of the subclass, each information resource member found to be in a first fuzzy cluster for a first topic represented by a first ttx listed in a result set attached to the first ttx representing the first topic of the first fuzzy cluster, each information resource listed as a result set item in the first result set attached to the first ttx attached as an occurrence to the first ttx representing the first topic of the first partition, the degree to which the information resource is associated with the first fuzzy cluster retained with the occurrence;

and

vi. fxxt resolution procedure for obtaining content for one domain of wisdom by performing a resolution for one fxxt specification stated in the map definition, the fxxt-resolution procedure yielding derived ontology containing a list of zero or more cnxpts and zero or more associations;

whereby variations of the invocation of maps allow for spawning other maps, expanded collection methods for wisdom, and ability to generate multi-forest and multi-purpose maps.

227. The method of claim 1 to also provide searching after map instantiation to locate wisdom sought, further including:

a. providing at least one procedure to locate wisdom yielding a list of at least one cnxpt into a derived ontology, wherein the procedure may then supply the basis wisdom for the formation of a map from a map definition referencing a set of zero or more fxxts, wherein the formation of the map is initiated after the basis wisdom is collected, wherein the procedure is of a type selected from the group of;

i. using result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant to a degree greater than a pre-defined number;

ii. using result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a list of at least one cnxpt to which the documents are relevant to a degree greater than a pre-defined number based upon the combined relevance of the set of documents to each cnxpt;

iii. using the set of cnxpts defined to be in a story where story is established from an ordered list of at least one cntexxt represented by one cnxpt, the search for content of the map specified by the story;

iv. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing tasks in a task plan, the search for content of the map specified by the plan;

v. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing nodes in a flow, the search for content of the map specified by the flow;

vi. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing nodes and association relating the cnxpts stating a precedence;

vii. using the result of a search yielding at least one cnxpt, the result passed into the map formation procedure;

viii. using fxxt specification stated in map definition to determine wisdom to be used to form content of a domain of wisdom;

and

b. providing zero or more procedures to accept search criteria to locate wisdom;

c. activating zero or more procedures to accept zero or more search criteria to locate wisdom;

d. accepting zero or more search criteria to locate wisdom;

e. specifying at least one procedure to locate wisdom based upon search criteria received;

f. presenting zero or more result sets for culling by the user, wherein the result set as finalized by user and accepted is placed into a derived ontology;

g. activating the at least one procedure to locate wisdom parameterized by the zero or more search criteria to locate wisdom to obtain a first domain of wisdom into a derived ontology;

h. determining zero or more second domains of wisdom by activating a second of the at least one procedure to locate wisdom parameterized by the zero or more search criteria to locate wisdom into a derived ontology;

i. accepting zero or more commands to select a map definition and zero or more stated parameters to further specify a map based upon said map definition, said zero or more commands to select said map definition and zero or more stated parameters for said map termed a map instantiation specification;

and

j. forming a map instance from the derived ontology and said map instantiation specification;

whereby one or more domains of knowledge are structured to become useful for a new map;

whereby a map definition stating fxxt utilizations serves as a receiving vehicle for one or more domains of knowledge passed to it;

whereby a unified search structure is provided so that a user may obtain wisdom into a first map ready for further use, the map depicting a perspective of the wisdom sought.

228. The method of claim 227 to also provide for tuning a map to a subjective perspective of of a user, further including:

a. determining identity of subsets of votes in wisdom located in said first domain of wisdom and said zero or more second domains of wisdom for which subjectivity is to be weighted by forming subsetting definitions formed from division intersection specifications whose elements are selected from the group of;

voting user identity, voting user organization identity, aggregation identity assigned to voting user, source identity, fxxt identity, info-item type, info-item attribute, info-item trait, info-item purpose, info-item relevance, time period of data collection from source, info-item creation time period, purlieu, location, info-item time period for a trait, info-item modification time period, membership in aggregate, membership in defined subset of aggregate, membership in organization, membership in defined subset of organization, degree of veracity, degree of presence of trait, descriptive attribute categorical division, and descriptive attribute value range, and zero or one group holding votes not in a defined disjoint sub set;

b. accepting a subjectivity factor coefficient for weighting the votes of the identified disjoint subsets for which subjectivity is to be weighted;

c. accepting a subjectivity factor coefficient for weighting the votes of said zero or one group holding votes not in a defined disjoint subset;

d. forming, prior to map generation, a grouping of all votes found to be considered during map generation, each group identified by the identity of the disjoint subset of votes the group is composed from, or a default identity for said zero or one group holding votes not in a defined disjoint subset;

e. determining, prior to map generation, for each group identity, the pre-determined default factor coefficient vote strengths that would be utilized in the generating of a map instance from said map definition if all votes were being weighted without regard to differentiated subjectivity as given by a value selected from the group of;

the value one, said subjectivity factor coefficient for weighting the votes of said zero or one group holding votes not in a defined disjoint subset, and a pre-defined value serving as a default;

f. determining, prior to map generation, for each group identity, according to the pre-determined algorithm for combining the default factor coefficient and the accepted subjectivity factor coefficient, a per group weighting factor coefficient for application to vote strengths for the votes in each group;

g. determining, for all votes in a group, the final per vote strength by multiplying the raw vote strength by the per group weighting factor coefficient for application to vote strengths for the votes in the group for utilization in the generating of a map instance from said map definition;

h. forming a map instance from said map definition;

whereby a map may be personalized to show a subjective perspective of the data in the domain of wisdom;

whereby the effect of subjectivity, expertise, or differentiated sources may be set for a map toward examination of a known perspective regarding the domains of wisdom of the map;

whereby belief strengths may be increased, decreased, aggregated, or disaggregated voting strengths may be set to allow generation of perspective specific maps by equal consideration, expert aggregation, aggregation by each of a set of disagreeing camps, personal prerogative, departmental consensus, party-line, trusted source specific, un-trusted source specific, time-varying opinion, subjective, and as a default the egalitarian objective perspective maps may be generated for use and inter-comparison.

229. The method of claim 1 to also provide for searching during fxxt extraction to locate wisdom sought, further including:

a. providing at least one auxiliary procedure to locate wisdom wherein the procedure may be invoked by a map formation procedure, the auxiliary procedure specified in the map definition, the map definition referencing a set of zero or more fxxts, the result of the auxiliary procedure placed into a derived ontology, wherein the procedure is of a type selected from the group of;

i. using result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant greater than a pre-defined degree;

ii. using result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a list of at least one cnxpt to which the documents are relevant to a degree greater than a pre-defined number based upon the combined relevance of the set of documents to each cnxpt;

iii. using the set of cnxpts defined to be in a story where story is established from an ordered list of at least one cntexxt represented by one cnxpt, the story specified in the context search specification of map definition, the search for content of the map specified by the story;

iv. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing tasks in a task plan, the plan specified in the context search specification of map definition, the search for content of the map specified by the plan, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

v. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing tasks in a task plan, the plan specified in the context search specification of map definition, the search for content of the map specified by the plan, the search performed internal to map formation procedure;

vi. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing nodes in a flow, the plan specified in the context search specification of map definition, the search for content of the map specified by the flow, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

vii. using the set of cnxpts defined to be in a directed graph where the directed graph is established from cnxpts representing nodes in a flow, the flow specified in the context search specification of map definition, the search for content of the map specified by the flow, the search performed internal to map formation procedure;

viii. using result of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result passed into the map formation procedure;

ix. using result of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

and

x. using fxxt specification stated in map definition to determine wisdom to be used to form content of a domain of wisdom;

b. accepting zero or more commands to select said map definition and zero or more stated parameters to further specify a map based upon said map definition, said zero or more commands to select said map definition and zero or more stated parameters for said map termed a map instantiation specification;

c. forming a map instance from said map instantiation specification;

d. providing zero or more procedures to process search criteria of map instantiation specification to locate wisdom;

e. specifying at least one procedure to locate wisdom;

f. activating zero or more procedures to accept zero or more search criteria to locate wisdom;

g. accepting zero or more search criteria to locate wisdom;

h. activating the at least one procedure to locate wisdom parameterized by the zero or more search criteria to locate wisdom to obtain a first domain of wisdom;

i. determining zero or more second domains of wisdom by activating a second of the at least one procedure to locate wisdom parameterized by the zero or more search criteria to locate wisdom;

j. accepting zero or more commands to select a first domains of wisdom and zero or more second domains of wisdom to form a map definition;

and

whereby one or more domains of knowledge are structured to become useful as wisdom available;

whereby a map definition stating fxxt utilizations serves as a specification vehicle for defining one or more domains of knowledge;

whereby a map definition serves as a holder of a user'"'"'s search request for generation of a map showing one or more domains of knowledge;

whereby the search for information to satisfy the purpose of a map is detailed in a map definition by stating search criteria for a first and possibly subsequent domains of knowledge;

whereby a unified search structure is provided so that a user may obtain wisdom into a first map ready for further use, the map depicting a perspective of the wisdom sought.

230. The method of claim 1 to also provide context searching by search specification to locate a context to center presentation on within a map, further including:

a. forming a map instance from a map definition;

b. determining a default first context containing a set of at least one cntexxt of said map instance;

c. providing at least one procedure to utilize context search specification for locating a context in a map instance, of a type selected from the group of;

i. using result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant greater than a pre-defined number, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

ii. using result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a list of at least one cnxpt to which the documents are relevant to a degree greater than a pre-defined number based upon the combined relevance of the set of documents to each cnxpt, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

iii. using result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant greater than a pre-defined number, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

iv. using result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a list of at least one cnxpt to which the documents are relevant to a degree greater than a pre-defined number based upon the combined relevance of the set of documents to each cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

v. using first cntexxt in a story where the story is established from an ordered list of at least one cntexxt, the story specified in the context search specification of map definition, the search for content of the map specified by the story, the search performed internal to map formation procedure, the story initiated at first cntexxt upon map initiation;

vi. using result of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result passed into the map formation procedure, but where result is empty use default context represented by at least one cntexxt;

vii. using result of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure, but where result is empty use default context represented by at least one cntexxt;

and

viii. using default context represented by at least one cntexxt where context search specification calls for direct use of default context;

d. activating the at least one procedure to utilize context search specification for locating a context in said map instance;

and

e. determining a first context represented by a cntexxt of said map instance for display according to the at least one procedure to utilize context search specification;

whereby a first focusing of a map to a context represented by an area or a cntexxt of a map instance is determined.

231. The method of claim 230 to also provide for changing a context to a requested alternative domain of knowledge, further including:

a. accessing the map specifying an organization of knowledge;

b. accepting a map definition specification request for one or more second organizations of knowledge;

c. generating a map instance containing said one or more second organizations of knowledge;

d. determining, for each of said one or more second organizations of knowledge, a default second cnxpt as the cntexxt to focus on in said map instance containing said one or more second organizations of knowledge;

and

e. presenting for use said map instance containing said one or more second organizations of knowledge;

whereby one or more subsequent maps containing revised perspectives on wisdom sought are made ready for further use.

232. The method of claim 230 to also provide flexible selection of a subsequent context in a map instance, further including:

a. providing at least one procedure to locate a subsequent context in said map instance, of a type selected from the group of;

i. accepting zero or more navigation commands stating a different cnxpt representing an alternative context selection, of a type selected from the group of;

01. using highest ranked result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant wherein the list of cnxpts is ranked by the degree of relevance, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

02. using highest ranked result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a ranked list of at least one cnxpt based upon the combined relevance of the set of documents to each cnxpt, the search performed external to map formation procedure, the result used to initiate the map formation procedure;

03. using highest ranked result, where result is not empty, of a search where the criteria is provided by a document'"'"'s contents for concept mapping and the search by document yields a list of at least one cnxpt to which the document is relevant wherein the list of cnxpts is ranked by the degree of relevance, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

04. using highest ranked result, where result is not empty, of a search where the criteria is provided by the contents of a set of documents for concept mapping and the search by documents yields a ranked list of at least one cnxpt based upon the combined relevance of the set of documents to each cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

05. using next cntexxt in story, where a next cntexxt is given, where story is established from an ordered list of at least one cntexxt, the story specified in the context search specification of map definition, the story progression determined by navigation controls;

and

06. using first cntexxt in story where story is established from an ordered list of at least one cntexxt, the story specified in the context search specification of map definition, the story initiated at first cntexxt upon map visualization initiation;

and

ii. accepting search criteria from one or more commands to specify an alternative search strategy for context selection, termed a secondary context search specification, for locating a context in said map instance, of a type selected from the group of;

01. using result, where result is not empty, of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result returned into the map formation procedure;

02. using result, where result is not empty, of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result returned into the map formation procedure;

03. using result, where result is not empty, of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

04. using result, where result is not empty, of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

and

05. using default context represented by at least one cnxpt where context search specification calls for direct use of default context;

b. activating the at least one procedure to locate a subsequent context in said map instance;

and

c. determining, from the result given by the at least one procedure to locate a subsequent context in said map instance, a next context represented by a cntexxt for the proper focusing in said map, the scope of specification of the context selected from the group of;

i. an identity of at least one cnxpt of said map instance;

ii. an identity of an area of consideration comprised of at least one cnxpt of said map instance;

iii. an identity of an area of interest comprised of at least one cnxpt of said map instance;

iv. a position from which the objects of the context are to be observed when the visualization is next presented to a user to view the context;

v. zero or more comments to be viewable by a user near the context when the visualization is next presented to a user to view the context;

vi. zero or more sounds to be available to the user for playing when the visualization is next presented to a user to view the context;

vii. zero or more vocalizations to be available for playing to the user when the visualization is next presented to a user to view the context;

viii. zero or more explanations to be viewable by a user near the context when the visualization is next presented to a user to view the context;

ix. zero or more parameters for zero or more viewports to be used to hold the one or more portions of the visualization next presented to a user to view the context or to present additional text, sounds, or other related information;

x. zero or more parameters for zero or more areas of the zero or more viewports to be used to hold the one or more portions of the visualization, the parameters stating the coloration of the one or more portions of the viewports next presented to a user to view the context;

and

xi. zero or more parameters for zero or more areas of the zero or more viewports to be used to hold the one or more portions of the visualization, the parameters stating the additional text, sounds, or other related information to be displayed in the one or more portions of the viewports next presented to a user to view the context;

whereby a change of context to show a subsequent frame of reference may be specified by a user.

233. The method of claim 230 to also present a different conceptual context within a map, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge;

and

c. generating, using said map definition, a map instance, the map instance having cnxpts in cntexxts representing contexts;

d. accepting from a user an instigation to change the context the map instance is focused on selected from the group of;

i. accepting a navigation by a user from one context represented by a cntexxt in the map to a different cntexxt;

and

ii. accepting a search query by a user causing a movement from one context represented by a cntexxt in the map to a different cntexxt;

whereby the map shows a context around a concept.

234. The method of claim 1 to also provide a visualization of a map holding wisdom sought, further including:

a. forming a map instance from said map instantiation specification;

b. determining a visualization of said map instance;

c. determining a context of said map instance for centering display;

and

d. presenting said visualization of said map instance to said user;

whereby a map instance is made into a visible user interface for a user.

235. The method of claim 1 to also provide for changing a context to an alternative context in a map instance, further including:

a. accepting a cnxpt locating command to select a second cnxpt presented as a subsequent cntexxt of wisdom;

b. repositioning, according to said locating command, said organization of knowledge to a second concept represented by said second cnxpt as a result of locating command;

whereby a subsequent focusing of a map to a context represented by an area or a cntexxt of a map instance is determined.

236. The method of claim 1 to also provide flexible selection of a subsequent context in a map instance to present, further including:

a. accepting zero or more cnxpt locating commands to determine the subsequent cntexxt to present, with any stated additional specification, to select a subsequent first cnxpt presented as a subsequent cntexxt of wisdom by operation of a process selected from the group of;

according to ideation means, according to finding and searching and query and retrieval means, according to goal based searching means, according to selection set management means, according to focus on information means, and according to alter information through visualization means;

said zero or more cnxpt locating commands selected from the group of;

i. selecting by default said default first cnxpt;

ii. stating in a search query specification step specification a first cnxpt;

iii. choosing from a list of cnxpts an alternative first cnxpt;

iv. choosing from a list of cnxpts an alternative first cnxpt by initiating a finding query;

v. choosing from a list of cnxpts an alternative first cnxpt, said list determined by accepting a text string wherein said string is matched against the descriptive information stored for each cnxpt;

vi. choosing from a list of cnxpts an alternative first cnxpt, said list determined by listing all root cnxpts in said domain of wisdom;

vii. navigating to a cntexxt chosen from all said cntexxts in said domain of wisdom according to visualization navigation means to choose a new first cnxpt;

viii. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a navigation by relationship info-item request resulting in a list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt;

ix. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a search query according to finding, searching, query and retrieval means resulting in a list of cnxpts;

x. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to finding, searching, query and retrieval means resulting in a list of cnxpts;

xi. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a goal search query according to goal based searching means resulting in a list of cnxpts;

xii. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to finding, searching, query and retrieval means a search query intended to result in a list containing a plurality of cnxpts having a property meeting criteria given by said additional specification and resulting in a list of cnxpts;

and

xiii. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to finding, searching, query and retrieval means a search query intended to result in a list containing a plurality of cnxpts having a property meeting criteria given by said additional specification and resulting in a list of cnxpts;

and

b. repositioning the focus on said organization of knowledge to a single cnxpt representing a cntexxt.

237. The method of claim 1 to also provide steering by result set matching for selection of a subsequent context in a map instance, further including:

a. providing at least one procedure to locate a subsequent context in said map instance, of a type selected from the group of;

i. accepting zero or more navigation commands stating a different cnxpt representing an alternative context selection, of type;

and

ii. accepting search criteria from one or more commands to specify an alternative search strategy for context selection, termed a secondary context search specification, for locating a context in said map instance, of a type selected from the group of;

01. use result, where result is not empty, of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result returned into the map formation procedure;

02. use result, where result is not empty, of a search yielding at least one cnxpt, the search performed external to map formation procedure, the result returned into the map formation procedure;

03. use result, where result is not empty, of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

04. use result, where result is not empty, of a search yielding at least one cnxpt, the search specified in the context search specification of map definition, the search performed internal to map formation procedure;

and

05. use default context represented by at least one cntexxt where context search specification calls for direct use of default context;

b. activating the at least one procedure to locate a subsequent context in said map instance;

and

c. determining, from the result given by the at least one procedure to locate a subsequent context in said map instance, a next context represented by a cntexxt of said map instance, the proper focusing for said map;

whereby the map is prepared to accept zero or more second wisdom request commands on the basis of the resulting found context as a subsequent frame of reference.

238. The method of claim 1 to also provide additional parts of a search command beyond a type of wisdom sought, further including:

a. accepting zero or one additional parts of a first or next wisdom request command providing an indication of a type of wisdom sought selected from the group of;

i. a null result;

ii. a result defined by a search analytic;

iii. information from a query, the type of information selected from the group of;

01. alert information;

02. analytic information;

03. associative position information navigation;

04. conceptual interrelationship info-item information;

05. entity similarity information;

06. business decision information;

07. business growth progress information;

08. business transaction information;

09. categorization information;

10. characteristic information;

11. commonality information;

12. competitive product information;

13. concept similarity information;

14. consortium artifact information;

15. consortium information;

16. contract transaction information;

17. crawl result information;

18. data availability;

19. goal information;

20. how-to information about invention;

21. how-to information about invention protection;

22. how-to information about innovative business growth;

23. info-item information;

24. information resource information;

25. interest shown by users;

26. satisfaction shown by users;

27. information about experts;

28. information about participants;

29. investment information;

30. investment opportunity information;

31. investment pool information;

32. investment diligence vetting information;

33. legal case information;

34. legal case strategy information;

35. legal discovery status information;

36. legal discovery relevance information;

37. legal information;

38. legal precedent information;

39. methodology information;

40. communal mind mapping consensus information;

41. model information;

42. negotiation process tracking information;

43. occurrence information;

44. opinion information;

45. outline construction information;

46. patent clearance process information;

47. patent clearance exposure information;

48. plug-in information;

49. portfolio entry information;

50. portfolio information;

51. portfolio transaction information;

52. prediction information;

53. process analysis information;

54. process control information;

55. product design information;

56. product control information;

57. product longevity information;

58. project control information;

59. property information;

60. purlieu information;

61. registration information;

62. relationship info-item information;

63. research study information;

64. result set information;

65. statistical analysis information;

66. subscription and usage information;

67. survey information;

68. template information;

69. trait information;

70. transaction information;

and

71. workflow information;

iv. a single item of a type, the type selected from the group of;

01. a cnxpt info-item;

02. a conceptual meaning;

03. a consortium info-item;

04. a crawl result;

05. a deal made in a consortium transaction;

06. a deal made in a portfolio transaction;

07. a deal made in an investment pool transaction;

08. a decision made in a consortium business decision;

09. a decision made in a portfolio business decision;

10. a decision made in an investment pool business decision;

11. a differentiator;

12. a discovery objective;

13. a fact to rule applicability ordered pair of cnxpt info-items;

14. a law info-item;

15. a legal charge theory of the case info-item;

16. a legal doctrine principle info-item;

17. a legal fact info-item;

18. a legal general rule info-item;

19. a legal jurisdiction info-item;

20. a legal precedent info-item;

21. a legal rule element info-item;

22. a legal rule info-item;

23. a legal theory of the case info-item;

24. a link cited in an attached occurrence;

25. a methodology info-item;

26. a model info-item;

27. a modeling result;

28. a participant info-item in a consortium;

29. a precedent successor dependency ordered pair of cnxpt info-items;

30. a prediction outcome info-item;

31. a prediction outcome value;

32. a prediction;

33. a property of a type of interest shown;

34. a property of a type of interest shown;

35. a property of an info-item;

36. a purlieu;

37. a query;

38. a registration;

39. a relationship info-item meaning;

40. a role of a consortium;

41. a set of matching pairings;

42. a set of applicability pairings;

43. a set of dependency pairings;

44. a specific rule;

45. a step in a fxxt specification info-item;

46. a step of a specification of an info-item having a specification for processing;

47. a study info-item;

48. a study objective;

49. a study result;

50. a subscription;

51. a survey result;

52. a task info-item in a timeline of a workflow;

53. a task info-item of a methodology;

54. a task info-item of a workflow;

55. a competitive constraint info-item;

56. a purlieu constraint info-item;

57. a tracked info-item of a consortium;

58. a trait of an info-item;

59. a transaction result;

60. a type of connected relationship;

61. a type of interest shown;

62. a type of relationship info-item;

63. a vote result;

64. a workflow info-item;

65. an information resource reference info-item;

66. an investment pool info-item;

67. an item of a blog;

68. an item of a commonality;

69. an item of a crawl result;

70. an item of a pool info-item;

71. an item of a portfolio info-item;

72. an item of a subscription;

73. an item of a transaction;

74. an occurrence info-item;

75. an opinion info-item;

76. an event info-item;

77. an evidence info-item;

78. an identifiable product of a task of a methodology;

79. an item of a portfolio;

80. a child in said organization of knowledge;

81. a commonality;

82. a consortium info-item;

83. a crawl result;

84. a crawl specification info-item;

85. a descendant in said organization of knowledge;

86. a descendant leaf in said organization of knowledge;

87. a fxxt info-item;

88. a goal info-item;

89. a methodology info-item;

90. a model info-item;

91. a parent in said organization of knowledge;

92. a participant info-item in a consortium info-item;

93. a plug-in;

94. a pool info-item;

95. a portfolio info-item;

96. a prediction info-item;

97. a query specification info-item;

98. a registration;

99. a result set;

100. a role info-item of a consortium info-item;

101. a sibling in said organization of knowledge;

102. a step in a fxxt specification;

103. a step of a methodology info-item;

104. a step of a model specification info-item;

105. a step of a prediction specification info-item;

106. a step of a query specification info-item;

107. a step of a workflow info-item;

108. a subscription specification;

109. a task info-item in a timeline of a workflow info-item;

110. a task info-item of a methodology info-item;

111. a task info-item of a workflow info-item;

112. a tracked item of a consortium info-item;

113. a transaction info-item;

114. a type of interest shown;

115. a workflow info-item;

116. an alert info-item;

117. an analytic;

118. an ancestor in said organization of knowledge;

119. an ancestor root in said organization of knowledge;

120. an attached occurrence in said organization of knowledge;

121. an avatar info-item;

122. an event info-item in a timeline of a workflow info-item;

123. an info-item connected by relationship info-item in said organization of knowledge;

124. an information resource referenced in an attached occurrence info-item in said organization of knowledge;

125. an item of a blog;

126. an item of a commonality specification;

127. an item of a crawl result;

128. an item of a pool;

129. an item of a result set;

130. an item of a subscription;

131. an item of a transaction;

and

132. an identity indicator value;

v. a list of a type of selected from the group of;

01. a list of alerts;

02. a list of analytics;

03. a list of avatars;

04. a list of property information regarding an info-item;

05. a list of characteristics;

06. a list of cnxpt info-items;

07. a list of commonalities;

08. a list of conceptual meanings;

09. a list of consortium info-items;

10. a list of crawl info-items;

11. a list of crawl results;

12. a list of decisions made;

13. a list of decisions needed;

14. a list of differentiators;

15. a list of fxxt info-items;

16. a list of goal info-items;

17. a list of identity indicators;

18. a list of info-items;

19. a list of information resource reference info-items;

20. a list of information resources;

21. a list of items of a result set;

22. a list of items of a set of crawl results;

23. a list of items of a set of pools;

24. a list of items of a set of portfolios;

25. a list of items of a subscription;

26. a list of items of a transaction;

27. a list of items of blogs;

28. a list of items of commonalities;

29. a list of links;

30. a list of methodology info-items;

31. a list of model info-items;

32. a list of occurrence info-items;

33. a list of outcome info-items;

34. a list of outcomes possible;

35. a list of pairs of cnxpt dependencies;

36. a list of pairs of cnxpts matching by applicability;

37. a list of pairs of cnxpts matching by interest;

38. a list of pairs of cnxpts matching by suitability;

39. a list of pairs of cnxpts matching by a constraint;

40. a list of pairs of cnxpts matching by trait;

41. a list of pairs of cnxpts matching semantically;

42. a list of participant info-items in a list of consortium info-items;

43. a list of plug-ins;

44. a list of pool info-items;

45. a list of portfolio info-items;

46. a list of precedent successor dependency pairs of cnxpts;

47. a list of prediction info-items;

48. a list of properties of types of interest shown;

49. a list of properties;

50. a list of purlieu;

51. a list of queries;

52. a list of registrations;

53. a list of relationships;

54. a list of result sets;

55. a list of roles of consortiums;

56. a list of steps in fxxts;

57. a list of steps of a specification of an info-item having a specification

58. a list of steps of a specification of an info-item having a specification stating actions to be carried out;

59. a list of steps of methodologies;

60. a list of steps of models;

61. a list of steps of predictions;

62. a list of task info-items of a specification of an info-item having a specification stating actions to be taken by a user;

63. a list of tasks in timelines of workflows;

64. a list of tasks of a set of methodologies;

65. a list of tasks of a set of workflows;

66. a list of tracked items of consortiums;

67. a list of traits;

68. a list of transactions;

69. a list of types of interest shown;

70. a list of types of relationships;

and

71. a list of workflows;

vi. a pairing of a type selected from the group of;

01. a pair of cnxpts matching by interest;

02. a pair of cnxpts matching by suitability;

03. a pair of cnxpts matching by a constraint;

04. a pair of cnxpts matching by trait;

05. a pair of cnxpts matching semantically;

06. a metric ordered area of consideration of cnxpts;

07. a metric ordered area of interest of cnxpts;

08. a metric ordered result set;

09. an ordered pair of cnxpts matching by suitability of evidence to discovery objective;

10. an ordered pair of cnxpts matching by suitability of evidence to fact;

11. an ordered pair of cnxpts matching by suitability of fact to rule element;

12. an ordered pair of cnxpts matching by suitability of function to audience;

13. an ordered pair of cnxpts matching by suitability of function to need;

14. an ordered pair of cnxpts matching by suitability rule to jurisdiction;

and

15. an ordered pair of cnxpts matching semantically;

vii. a result set of a type selected from the group of;

01. a result of a fxxt specification;

02. a result of a model specification;

03. a result of a workflow specification;

04. a result set of pairs of cnxpts matching by interest;

05. a result set of pairs of cnxpts matching by suitability;

06. a result set of pairs of cnxpts matching by a constraint;

07. a result set of pairs of cnxpts matching by trait;

08. a result set of pairs of cnxpts matching semantically;

and

09. a result set of precedence dependency pairs of cnxpts;

viii. an event of a type selected from the group of;

01. an action triggered by said search;

02. an action defined by a search analytic triggered by said search;

03. an event triggered by said search;

and

04. an event defined by a search analytic triggered by said search;

ix. a list of cnxpts, the list of a type selected from the group of;

01. a list selected from the group of;

immediate children, cntexxt children, and members of the cntexxt of said identified cnxpt in said identified forest;

02. a list of the set of all member cnxpts in a cntexxt identified by one or more cnxpts containing direct descendant cnxpts at all levels of descendancy of said specifically identified one or more cnxpts, said list termed the list of descendants;

03. a list selected from the group of;

the set of all member cnxpts in a cntexxt containing a specifically identified cnxpt, said list termed the list of siblings of said specifically identified cnxpt;

and

04. a list selected from the set of all member cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent forest, said list comprising the set of second cnxpts wherein the second cnxpt is a descendant of said specifically identified cnxpt if the cntexxt represented by said second cnxpt itself is empty having no descendants in said specifically identified descendent forest, said list termed the leaf list of said specifically identified cntexxt in said specifically identified descendent forest, said leaf cnxpt termed a leaf of said specifically identified cntexxt in said specifically identified descendent forest, said leaf cnxpt termed a leaf of said specifically identified descendent forest;

x. a compound list of cnxpts, the list of a type selected from the group of;

01. a forest selected from the set of all member cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent forest, said list the set of second cnxpts wherein the second cnxpt is a descendant of said specifically identified cnxpt and said specifically identified cnxpt, and all interconnecting hierarchical relationships from said specifically identified descendent forest, said forest termed the sub-tree of said specifically identified cntexxt in said specifically identified descendent forest;

02. a list selected from the set of all second cnxpts in the leaf list of said specifically identified first cnxpt;

03. a list selected from the set of all second cnxpts in a parent list of the cnxpt representing the cntexxt in said specifically identified descendent forest;

04. a list selected from the group of;

the set of all second cnxpts in a specifically identified descendent forest wherein each second cnxpt is a sibling cnxpt of the cnxpt representing the cntexxt of which a specifically identified cnxpt is a member but excluding said cnxpt representing the cntexxt of which said specifically identified cnxpt is a member, said list termed the list of uncles of said specifically identified cnxpt in said specifically identified descendent forest, said list termed the list of uncles of said cntexxt;

05. a list selected from the group of;

the set of all second cnxpts of a specifically identified descendent forest wherein said second cnxpt has no parent in said specifically identified descendent forest regardless of whether said second cnxpt has no children in said specifically identified descendent forest, each said second cnxpt termed a root of said specifically identified descendent forest, said list termed the root list of said specifically identified descendent forest;

06. a list selected from the set of all second cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent forest, said list containing said specifically identified cnxpt regardless of whether said cntexxt itself is empty wherein said specifically identified cnxpt is a leaf and also containing the parent in said specifically identified descendent forest of any said second cnxpt in said list, said list termed the ascendant list of said specifically identified cntexxt in said specifically identified descendent forest, each said second cnxpt termed an ascendant cnxpt of said specifically identified cntexxt in said specifically identified descendent forest, said list together with the hierarchical relationships connecting said ascendant cnxpts to form said specifically identified descendent forest termed the ascendant path of said specifically identified cntexxt in said specifically identified descendent forest;

07. a list selected from the group of;

the set of all second cnxpts in a specifically identified descendent forest wherein each second cnxpt is a sibling cnxpt of the cnxpt representing the cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent forest plus any root in said specifically identified descendent forest if said cnxpt representing the cntexxt of which a specifically identified cnxpt is a member is also a root, but excluding said cnxpt representing the cntexxt of which said specifically identified cnxpt is a member, said list termed the list of uncles of said specifically identified cnxpt in said specifically identified descendent forest, said list termed the list of forest uncles of said cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent forest, each item in said list of uncles termed an uncle of each member of said cntexxt of which said specifically identified cnxpt is a member in said specifically identified descendent forest;

08. a list, formed in response to a specification requesting the root list of said specifically identified descendent forest, of the set of all second cnxpts of a specifically identified descendent forest wherein said second cnxpt has no parent in said specifically identified descendent forest regardless of whether said second cnxpt has no children in said specifically identified descendent forest and regardless of whether said specifically identified descendent forest has more than one said second cnxpt, each said second cnxpt termed a root of said specifically identified descendent forest, said list termed the root list of said specifically identified descendent forest, said list alternatively termed the forest root list of said specifically identified descendent forest, said specifically identified descendent forest alternatively termed a forest where only a single said second cnxpt exists in specifically identified descendent forest;

09. a list, formed in response to a specification requesting the list of siblings of said specifically identified root cnxpt in said specifically identified descendent forest, of the set of all second root cnxpts in a specifically identified descendent forest containing a specifically identified root cnxpt, said set of second root cnxpts reduced to eliminate as a set member said specifically identified root cnxpt, wherein said specification also states that said list is to contain the sibling cnxpts of said specifically identified cnxpt in a specifically identified descendent forest, said list termed the list of siblings of said specifically identified root cnxpt in said specifically identified descendent forest;

10. a list, formed in response to a specification requesting the ascendant sub-tree of said specifically identified cntexxt in said specifically identified ascendant forest, of the set of all second cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified ascendant forest, said list containing said specifically identified cnxpt regardless of whether said cntexxt itself is empty wherein said specifically identified cnxpt is a leaf and also containing the parent in said specifically identified ascendant forest of any said second cnxpt in said list, said list termed the ascendant list of said specifically identified cntexxt in said specifically identified ascendant forest, each said second cnxpt termed an ascendant cnxpt of said specifically identified cntexxt in said specifically identified ascendant forest, said list together with the set of hierarchical relationships connecting said ascendant cnxpts taken from the list of hierarchical relationships connecting said specifically identified ascendant forest termed the ascendant sub-tree of said specifically identified cntexxt in said specifically identified ascendant forest;

11. a list, formed in response to a specification requesting the primary flow list in said specifically identified forest, of the set of all ordered pairs of cnxpts of the set of a first cnxpt in a first position and a second cnxpt in the second position wherein each said first cnxpt and each said second cnxpt are both in a specifically identified forest selected from the group of;

ascendant forest and descendent forest, wherein said first cnxpt is a predecessor in a flow-type directed association to said second cnxpt as successor, said ordered pair termed a primary flow pair in said specifically identified forest, said first cnxpt termed a primary predecessor flow cnxpt of said primary flow pair, said second cnxpt termed a primary successor flow cnxpt of said primary flow pair, said list of ordered pairs termed a primary flow list in said specifically identified forest;

12. a list, formed in response to a specification requesting the same level primary flow list in said specifically identified forest, of the set of all primary flow pairs in a specifically identified forest;

13. a list, formed in response to a specification requesting the different level primary flow list in said specifically identified forest, of the set of all primary flow pairs in a specifically identified forest;

14. a list, formed in response to a specification requesting the same level secondary flow list in said specifically identified forest, of the set of all ordered pairs of cnxpts of the set of a first cnxpt in a first position and a second cnxpt in the second position wherein each said first cnxpt and each said second cnxpt are both in a specifically identified forest;

15. a list, formed in response to a specification requesting the root level flow tensor list in said specifically identified forest;

and

16. a list, formed in response to a specification requesting the same level flow tensor list in said specifically identified forest, of the set of all ordered tuples each of a first cnxpt, a second cnxpt, and a weight from a set of flow pairs in a specifically identified forest;

xi. a listing of the contents of a map performed by a search, the map of a type selected from the group of;

01. a map, formed in response to a specification requesting a co-location map of concepts, of the set of cnxpts within a specifically identified forest selected from the group of;

ascendant forest, enhanced ascendant forest, descendant forest, and enhanced descendent forest;

with placement on the root level and placement within any parent cnxpt determined by co-location positioning, according to map generation means, said map termed a co-location map of said specifically identified forest;

02. a list comprised of zero or more info-items contained within a precedence map;

and

03. a list comprised of zero or more info-items contained within a flow map;

and

xii. an action taken upon completion of a search, the action of a type selected from the group of;

01. a repositioning to a cnxpt within the cntexxt defined by said cnxpt to indicate the likely location of the concept having a meaning best matching said requested search, wherein said organization of knowledge is immediately repositioned to said point in said cntexxt.

239. The method of claim 1 to also provide additional parts of a search command to identify a search base parameter, further including:

a. accepting zero or more additional parts of a first or next wisdom request command each providing a reference to an identified search base to be used as a parameter in said first or next wisdom request.

240. The method of claim 1 to also provide for additional parts of a search command to identify further search parameters, further including:

a. accepting zero or more additional parts of a first or next wisdom request command each providing an additional specification to be used as the criterion in said first or next wisdom request in a priority order;

i. a reference to a search query specification;

ii. an indicator stating whether a weighting is to be applied when combining consensus and said user'"'"'s opinion;

iii. a weighting specification for combining consensus and said user'"'"'s opinion;

iv. a relevance coefficient specification for combining consensus and said user'"'"'s opinion;

v. a pertinence coefficient specification for combining consensus and said user'"'"'s opinion;

vi. an indicator stating whether a degree of fuzziness is to be applied when combining consensus and said user'"'"'s opinion;

vii. a value of a degree of fuzziness for combining consensus and said user'"'"'s opinion;

viii. a value of a per-level inheritance effect dampening coefficient for combining consensus and said user'"'"'s opinion based upon common ancestry in an organization of knowledge;

ix. an indicator stating whether an ordering is to be applied to said first form of result after completion;

x. a type of ordering to apply to said first form of result after completion;

xi. a type;

xii. an citation type;

xiii. a causality type;

xiv. a probability distribution;

xv. an identity indicator type;

xvi. an identity indicating a result set;

xvii. an identity indicating a result set item;

xviii. an identity indicator indicating an organization of knowledge;

xix. a list combination specification;

xx. a number of characters;

xxi. a position in a string;

xxii. a number of entries;

xxiii. a value of the form of an identity indicator;

xxiv. a value of the form of an info-item property;

xxv. a value of the form of an info-item characteristic;

xxvi. a value of the form of a trait;

xxvii. a value of the form of a purlieu;

xxviii. a value of the form of a keyword;

xxix. a value of the form of an info-item characteristic identifier;

xxx. a value of the form of an info-item property identifier;

xxxi. a value of the form of a data set attribute identifier;

xxxii. a value of the form of a data set attribute;

xxxiii. a value of the form of a data set table identifier;

xxxiv. a position in a list;

xxxv. a number of items;

xxxvi. a position in a result set list;

xxxvii. a collating sequence;

xxxviii. a language;

xxxix. a text string;

xl. a regular expression string;

xli. a string;

xlii. a value of a parameter;

and

xliii. a value of a pre-established preference.

241. The method of claim 1 to also provide for additional parts of a search command to identify further search parameters to state a frame of reference, further including:

a. accepting zero or one additional part of a first or next wisdom request command providing a specification for search to obtain contents for said first form of result to serve as a subsequent frame of reference by selection of said type of wisdom sought, said specification for search selected from the group of;

i. requesting an empty set;

ii. requesting a default set;

iii. requesting a search by analytic;

iv. requesting a set containing a specified Boolean combination of the items in a first said identified search base and the items in a second said identified search base;

v. requesting a set containing a specified subset of the items in a first said identified search base;

vi. requesting a set containing a specified subset of the candidate items in a first said identified search base which to a specified degree of fuzziness each candidate item has a trait that matches a string of text given by a combination of one or more specified matching criteria according to finding, searching, query and retrieval means and attach result set to goal according to goal based searching means;

vii. requesting a set containing a specified subset of the candidate items in a first said identified search base which to a specified degree of fuzziness meets criteria given in said additional specification selected from the group of;

01. has said one or more types of wisdom sought having a non-null value;

02. has said one or more types of wisdom sought having a value matching a value given in a second said identified search base;

03. has said one or more types of wisdom sought having a type value matching a value given in a second said identified search base;

04. has said one or more types of wisdom sought having a fxxt matching a value for a fxxt identity indicator matching a value given in a second said identified search base;

05. is attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

06. is relevant to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

07. is related to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

08. is cited by an information resource given by one or more occurrences attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

09. cites an information resource given by one occurrence attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

10. cites an information resource given by one or more occurrences attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

11. has an identity indicator meeting criteria given by said additional specification;

12. has an identity indicator given in a second said identified search base of cnxpts;

13. has an identity indicator meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

14. has a characteristic value meeting criteria given by said additional specification;

15. has a characteristic value given in a second said identified search base of cnxpts;

16. has a characteristic value meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

17. has a trait meeting criteria given by said additional specification;

18. has a trait given in a second said identified search base of cnxpts;

19. has a trait meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

20. has a property meeting criteria given by said additional specification;

21. has a property given in a second said identified search base of cnxpts;

22. has a property meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

23. has a purlieu meeting criteria given by said additional specification;

24. has a purlieu given in a second said identified search base of cnxpts;

25. has a purlieu meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

26. has an attribute meeting criteria given by said additional specification;

27. has an attribute given in a second said identified search base of cnxpts;

28. has an attribute meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

29. has a keyword meeting criteria given by said additional specification;

30. has a keyword given in a second said identified search base of cnxpts;

31. has a keyword meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

and

32. has a field, specified by said additional specification, said field selected from the group of;

identity indicator, property value, characteristic value, trait, purlieu, attribute, and keyword, meeting criteria given by said additional specification, matching against a specified value given in a second said identified search base;

viii. requesting said one or more types of wisdom sought for a concept represented by an item in the list created from the set of all items in a first said identified search base cnxpt;

ix. requesting information for a concept represented by a set of cnxpts ostensibly belonging in a cntexxt wherein said information is a part of the wisdom available for the cnxpt representing said cntexxt, said cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

x. requesting a list of properties defined for a cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

xi. requesting a value for a characteristic of a cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

xii. requesting a value for a characteristic of an info-item in the list created from the set of all items in a first said identified search base;

xiii. requesting a list of values of characteristics of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xiv. requesting a list of values of characteristics of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xv. requesting a result set list for culling list items of info-items connected to a cnxpt to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set list created from the set of all info-items connected to a cnxpt in a first said identified search base, said info-items of a type specified in said additional specification, said result set items ordered by a characteristic or property value wherein said characteristic or property is specified in said additional specification;

xvi. requesting a result set list for culling list items of info-items connected to a cnxpt to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set list created from the set of all info-items connected to a cnxpt in a first said identified search base, said info-items of a type specified in a second said identified search base, said result set items ordered by a characteristic or property value wherein said characteristic or property is specified in said additional specification;

xvii. requesting a list of values of properties of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xviii. requesting characteristic or property information regarding an info-item in the list created from the set of all items in a first said identified search base;

xix. requesting a list of values of properties of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xx. requesting a fact or an estimation of a fact represented by a value for a characteristic of an info-item in the list created from the set of all items in a first said identified search base;

xxi. requesting a fact or an estimation of a fact represented by a value for a characteristic of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xxii. requesting a fact or an estimation of a fact represented by a value for a characteristic of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xxiii. a fact or an estimation of a fact represented by a value for a characteristic of a specific type for a concept represented by a set of cnxpts ostensibly belonging in a cntexxt wherein said information is a part of the wisdom available for the cnxpt representing said cntexxt, said cnxpt in the list created from the set of all items in a first said identified search base;

xxiv. requesting said one or more types of wisdom sought for an info-item wherein said information is a part of the wisdom available for said info-item, said info-item in the list created from the set of all items in a first said identified search base;

xxv. requesting a list of identity indicators of a set of info-items in the list created from the set of all items in a first said identified search base;

xxvi. requesting a list of identity indicators of info-items connected to a cnxpt in the list created from the set of all items in a first said identified search base;

xxvii. requesting a list of identity indicators of info-items connected to a cnxpt in the list created from the set of all items in a first said identified search base of a type of info-item listed in a second said identified search base listing info-item type identifiers;

xxviii. requesting information for a concept represented by a cnxpt wherein said information is external to said commonplace, but is likely related to said cnxpt in the list created from the set of all items in a first said identified search base;

xxix. requesting characteristic or property information regarding an occurrence in the list created from the set of all items in a first said identified search base where said item is an occurrence info-item;

xxx. requesting a relevance ranking of an information resource relevant to a cnxpt, said information resource likely to contain said wisdom, said cnxpt in the list created from the set of all items in a first said identified search base where said item is a cnxpt;

xxxi. requesting an information resource relevant to a cnxpt, said information resource likely to contain said wisdom, said cnxpt in the list created from the set of all items in a first said identified search base where said item is a cnxpt;

xxxii. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item of a type listed in a second said identified search base listing info-item type identifiers;

xxxiii. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item having a characteristic of a type specified in said additional specification and a value listed in a second said identified search base;

xxxiv. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item having a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxv. requesting a list of identity indicators of traits attached to cnxpts in the list created from the set of all items in a first said identified search base where said trait has a property with a value specified in said additional specification;

xxxvi. requesting a list of identity indicators of traits attached to cnxpts in the list created from the set of all items in a first said identified search base where said trait has a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxvii. requesting a list of identity indicators of purlieu attached to cnxpts in the list created from the set of all items in a first said identified search base where said purlieu has a property with a value specified in said additional specification;

xxxviii. requesting a list of identity indicators of purlieu attached to cnxpts in the list created from the set of all items in a first said identified search base where said purlieu has a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxix. requesting a result set list for culling list items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria;

xl. requesting a result set list for culling list items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base;

xli. requesting a result set list for culling list items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlii. requesting a result set list for culling information resource items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria;

xliii. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base;

xliv. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlv. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all information resource returned from a search request, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlvi. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all information resources returned from a search request to determine information resources relevant to a cnxpt in the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlvii. requesting a result set to build a goal by query from a search query, said result set implying a concept sought by said user by searching for said goal;

xlviii. requesting a result set of information resources to build a goal, said result set implying a concept sought by said user by searching for said goal;

xlix. requesting a repositioning for navigation to a best cntexxt of a set of better cntexxts each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said best cntexxt represented by a cnxpt having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

l. requesting a list for picking a selection of what appears to said user as a best cntexxt of a set of better cntexxts listed, each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said cnxpts optionally having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

li. requesting a repositioning for navigation into an area of consideration of better cntexxts each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said cntexxts each represented by a cnxpt having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

lii. requesting a list of cnxpts representing concepts for inclusion in an area of consideration or area of interest for navigating, according to said user'"'"'s own criteria;

liii. requesting a result from an operation, said result indicating one or more cntexxts represented by one or more second cnxpts, the operation selected from the group of;

01. movement of user focus to a context represented by a second cnxpt, said second cnxpt appearing first in a list of results in an order specified in said additional specification, said second cnxpt representing a second cntexxt;

02. list of identity indicators of a type specified by said additional specification listing, in an order specified in said additional specification, said list for selecting cnxpt items based upon what appears to the user as a good choice according to said user'"'"'s own criteria, said identity indicator of each second cnxpt representing a second cntexxt;

03. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for culling cnxpt items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, altering an item value, entering an opinion, item addition, and item removal, said identity indicator of each second cnxpt representing a second cntexxt;

04. a timeline listing identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

05. a list of conceptual meanings listing, in an order specified in said additional specification, said conceptual meaning in a language specified by said additional specification, said conceptual meaning of a second cnxpt representing a second cntexxt;

06. a timeline listing conceptual meanings of a type and language specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

07. a co-location map for associative searching, navigation, or a predetermined purpose, said map created from the set of all second cnxpts representing second cntexxts;

08. a flow map for associative searching of a process, navigation, or a predetermined purpose, showing each identity indicator of a type specified by said additional specification listing, in an ordering for flow based upon a specified flow relationship info-item type specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt, said map created from the set of all said second cnxpts representing second cntexxts;

09. a co-location map with flow for associative searching, searching of a process, navigation, or a predetermined purpose, showing each identity indicator of a type specified by said additional specification listing, in an ordering for flow based upon a specified flow relationship info-item type specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt, said map created from the set of all said second cnxpts representing second cntexxts;

10. a list of values of a characteristic, in an order specified in said additional specification, in a language specified by said additional specification, said value of a characteristic of a second cnxpt representing a second cntexxt;

11. a list of differentiations in conceptual meaning listing, in an order specified in said additional specification, each such differentiation in a language specified by said additional specification, said differentiation of a second cnxpt representing a second cntexxt;

12. a list of differentiations of a characteristic of a specified type specified by said additional specification listing, in an order specified in said additional specification, said characteristic value of each second cnxpt representing a second cntexxt;

13. a timeline listing differentiations of conceptual meanings of a type and language specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

14. an area of consideration for culling cnxpt items to improve said area of consideration'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said area of consideration created from the set of all second cnxpts representing second cntexxts;

15. an area of interest for culling cnxpt items to improve said area of interest'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said area of interest created from the set of all second cnxpts representing second cntexxts;

16. a portfolio information table listing values of info-items of types specified by said additional specification, listing one or more values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, for reviewing info-items of said types specified to improve said portfolio'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said portfolio created from information related to items in the set of all second cnxpts representing second cntexxts;

17. modeling results of types specified by said additional specification listing one or more result values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said results for each second cnxpt representing a second cntexxt;

18. an estimation of a fact represented by a modeling result of a type specified by said additional specification and a degree of fuzziness specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said estimation for each second cnxpt representing a second cntexxt;

19. an estimation of the probability of the existence of a fact represented by a modeling result of a type specified by said additional specification, a degree of fuzziness specified by said additional specification, and a time frame specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said estimation for each second cnxpt representing a second cntexxt;

20. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing modeling results for cnxpt items based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said second cnxpt meeting criteria based upon a modeling result of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

21. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing outcomes based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, item information research, item information collection, initiating contact, prediction acceptance, prediction rejection, ranking, altering an item value, entering an opinion, item addition, and item removal, said outcome meeting criteria based upon a modeling result of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, based upon one or more second cnxpts each representing a second cntexxt;

22. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing subject matter selected from the group of;

principle, standard, practice, field, jurisdiction, purlieu, trait, law, author, subject, fact, opinion, doctrine, study, study result, lab test report, evidence item, evidence type, element, documentary evidence, theory, topic, category, entry meaning, entry impact, precedent, entry relevance, rule, a user defined content type, an analytic content type;

for cnxpt items based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said second cnxpt meeting criteria of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

23. a report of information regarding audience strength based upon interest shown, based upon one or more second cnxpts each representing a second cntexxt;

24. a report of information regarding general audience strength, based upon one or more second cnxpts each representing a second cntexxt;

25. a report of information regarding dependent audience strength based upon a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

26. a report of information regarding interest shown, based upon one or more second cnxpts each representing a second cntexxt;

27. a report of information regarding interest shown for a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

28. a report of information regarding dependent audience strength based upon a relationship info-item traversal based upon one or more second cnxpts as origins, said second cnxpts each representing a second cntexxt;

29. a report of information regarding normalized interest shown metrics for one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

30. a report of information regarding normalized interest shown metrics for a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

31. a list of tuples of cnxpt identity indicators being pairs of;

two cnxpts wherein a first cnxpt matches a second cnxpt according to relationships entered by users or by matching criteria of a type specified in said wisdom request command parts, in an order specified in said additional specification, each second cnxpt representing a second cntexxt;

and

32. prediction results of types specified by said additional specification listing one or more prediction values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said prediction results based upon each second cnxpt representing a second cntexxt.

242. The method of claim 1 to also provide for additional parts of a search command to identify further search parameters to state a specification form required, further including:

a. accepting zero or more first or next wisdom request commands, each of one or more parts, with any stated additional specification, initial zero or more parts each providing zero or one indication of the type of a first form of result to serve as a subsequent frame of reference for decision and action when generated, to be generated according to the finding, searching, query and retrieval process means, said initial zero or more parts of said first or next wisdom request command in a specification form selected from the group consisting of;

i. user entered search command;

ii. user entered search query;

iii. user entered request to follow a methodology query;

iv. user entered request to follow a path specified by a user;

v. user entered search recorded macro step;

vi. user request to repeat or refresh a search command or query;

and

vii. search query specification step specification;

b. specifying the type of results to be produced, where the search results in no hits, said first form of result selected from the group consisting of;

i. a result set with no result set items;

ii. an indication that the search query resulted in no found items;

iii. an empty set;

and

iv. a default set;

c. specifying the type of results to be produced, where the search results in one hit, said first form of result selected from the group consisting of;

i. an avatar;

ii. a commonality;

iii. a conceptual meaning by a repositioning;

iv. a deal made;

v. a decision made;

vi. a directory listing;

vii. a fxxt extraction invocation;

viii. a goal;

ix. a link;

x. a methodology action;

xi. a plug-in;

xii. a portfolio entry;

xiii. a registration made;

xiv. a relationship info-item;

xv. a resolved link;

xvi. a result of a model invocation;

xvii. a result of a prediction;

xviii. a result of a workflow invocation;

xix. a scalar;

xx. a single item result;

xxi. a specification;

xxii. a step in a specification;

xxiii. a taxonomy;

xxiv. a template;

xxv. a transaction;

xxvi. a value of a characteristic of an info-item;

xxvii. a value of a property of an info-item;

xxviii. a vote made;

xxix. a vote;

xxx. an alert;

xxxi. an event;

xxxii. an identity indicator of an info-item;

xxxiii. an info-item;

xxxiv. an information resource;

xxxv. an intermediate or final result of processing a specification of an info-item having a specification for processing;

xxxvi. an invocation of a step of a specification of an info-item having a specification for processing;

xxxvii. an item of a result set;

xxxviii. an outcome defined by the search;

and

xxxix. a multi-media information block;

d. specifying the type of results to be produced, where the search results in multiple hits, said first form of result selected from the group consisting of;

i. a collaboration blog list;

ii. a crawl;

iii. a data set;

iv. a list data set, said list optionally visualized;

v. a map data set, said map optionally visualized;

vi. a directed graph;

vii. a directory;

viii. a forest of trees;

ix. a graph;

x. a list for picking a selection of a what appears to the user as a good choice according to said user'"'"'s own criteria;

xi. a list;

xii. a pair tuple or pairing;

xiii. an ordered pair tuple or pairing;

xiv. a product catalog;

xv. a result set map;

xvi. a portfolio map;

xvii. a portfolio;

xviii. a result of an analytic invocation;

xix. a result set list;

xx. a result set;

xxi. a timeline;

xxii. a timeline ordered area of consideration of cnxpt info-items;

xxiii. a timeline ordered area of interest of cnxpt info-items;

xxiv. a timeline ordered result set;

xxv. a timeline ordered list;

xxvi. a timeline ordered graphical composite of durations;

xxvii. a transaction list;

xxviii. an area of consideration of cnxpt info-items;

xxix. an area of interest of cnxpt info-items;

xxx. a selection set;

xxxi. a set;

xxxii. a sub-tree;

xxxiii. a tracking history of an item of a consortium;

xxxiv. a tree;

xxxv. an ordered list;

and

xxxvi. an ordered result set list;

e. specifying the type of results to be produced, where the search results in a building of a structure, said first form of result selected from the group consisting of;

i. a data set comprising a list, said list not a visualization;

ii. a list data set, said list optionally visualized;

iii. a data set comprising a map, said map not a visualization;

iv. a map data set, said map optionally visualized;

v. a descendent tree formed according to fxxt descendent tree extraction process means;

vi. a descendent forest formed according to fxxt descendent tree extraction process means;

vii. an ascendant tree formed according to calculate ascendant trees process means;

viii. an ascendant tree forest formed according to calculate ascendant trees process means;

ix. a result of a fxxt extraction according to fxxt calculation script interpretation process means;

x. a methodology consisting of;

at least one part selected from the group consisting of;

01. a theoretical discussion;

02. a discussion of a general process to follow;

and

03. a list of methodology steps defined by a methodology according to second level for process, innovation, study or share and commune in innovation, product planning, competitive analysis and environmental scanning, innovation investment planning portfolio analysis data mining, intellectual property valuation and metrics, information services and access sales, patent invention or socialize process means;

xi. a workflow defined according to workflow and alerts process means and processing of workflow task lists by a defined set of task steps managed by the system by a workflow system plugin means;

xii. a list of events, each represented by a cnxpt info-item, each stated with zero or more time points referenced according to either a specified horizon or the current real world frame, each having zero or more statuses based upon its type, each status susceptible to consensus voting, each event having a type selected from the group consisting of;

01. a suggested methodology step task, with status values roughly equivalent to suggested, prioritized, planned, scheduled, assigned, completed;

02. a planned task, with status values roughly equivalent to prioritized, scheduled, assigned, completed;

03. a task not completed, with status value set to a default value equivalent to incomplete;

04. a to-do item, with status values roughly equivalent to scheduled, assigned, completed;

05. a workflow task, with status values roughly equivalent to suggested, prioritized, planned, scheduled, specification completed, implemented, tested, queued, executed once, executing in repetition, assigned, completed;

06. an issue, with status values roughly equivalent to reported, planned, raised, prioritized, rejected, scheduled, assigned, completed, solved, implemented;

07. a trouble report, with status values roughly equivalent to reported, auto response sent, blog started, response sent, response planned, raised internally, prioritized, rejected, scheduled, assigned, completed, solved, implemented;

08. a request, with status values roughly equivalent to planned, raised, prioritized, rejected, scheduled, assigned, completed, solved, implemented;

09. an approval, with status values roughly equivalent to incomplete, approved, rejected, disapproved, funded, assigned, completed;

10. an outcome, with status values roughly equivalent to possible, accepted;

11. a chosen cnxpt representing a chosen path followed based upon a decision, with status values roughly equivalent to recommended, taken;

12. a deal made referencing a deal between parties, with status values roughly equivalent to suggested, prioritized, planned, scheduled, negotiating, specification completed, offer made, accepted, executed;

13. a transaction result event, with status values roughly equivalent to suggested, prioritized, planned, scheduled, negotiating, specification completed, transfer ready, paid;

14. a feature request, with status values roughly equivalent to reported, planned, raised, prioritized, rejected, scheduled, assigned, completed, solved, implemented, tested, alpha, beta, available;

15. a processing function required of a workflow, with status values roughly equivalent to incomplete, scheduled, in process, completed;

16. an acceptance required of a workflow, with status values roughly equivalent to incomplete, approved, rejected, disapproved, funded, assigned, completed;

17. a check-off required in a workflow, with status values roughly equivalent to incomplete, satisfactory, or improper;

18. result sets to cull, with status values roughly equivalent to scheduled, assigned, completed;

19. result set items to review, with status values roughly equivalent to scheduled, assigned, completed;

20. a general event, with status values roughly equivalent to scheduled, completed;

21. a historic event, with status values roughly equivalent to rejected and locked as historic, completed and locked as historic;

and

22. a close out event indication;

xiii. a visualized map based upon positioning of cnxpts within an area formed according to set or area map generation process means;

xiv. a visualized map based upon positioning of cnxpts within an area formed according to fxxt specific ttx map generation process means;

xv. a predictive map formed according to fxxt specific ttx map generation and predictive intelligence process means;

xvi. a workflow task map formed according to fxxt specific ttx map generation process means;

xvii. a process flow map formed according to fxxt specific ttx map generation process means;

xviii. a methodology step map formed according to fxxt specific ttx map generation process means;

xix. a portfolio expected monetary value map formed according to fxxt specific ttx map generation and primary predictions process means;

xx. a timeline event formed according to fxxt specific ttx map generation process means;

xxi. a methodology step map formed according to fxxt specific ttx map generation process means;

and

xxii. a visualized map formed according to fxxt specific ttx map generation process means on the basis of information generated by second level for process, predictive intelligence, primary predictions, or innovation investment planning, portfolio analysis, data mining, and metrics process means;

f. specifying the type of results to be produced, where the search results in the repositioning of at least one info-item in a map, said first form of result selected from the group consisting of;

i. a set of one or more repositionings, termed a general repositioning, each repositioning selected from the group consisting of;

01. a moving of a logical pointer, or data cursor, in a non-displayed logical view of said organization of knowledge, termed a scripted repositioning;

02. a moving of a visible viewing point in a displayed view of said organization of knowledge, termed a visual repositioning;

and

03. a moving of a mechanical point on a physically structured organization of knowledge, termed a physical repositioning;

ii. a general repositioning to a single cnxpt wherein said organization of knowledge is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt;

iii. a general repositioning to a single cnxpt wherein said organization of knowledge within an area of consideration of cnxpts is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt within said area of consideration;

iv. a general repositioning to a single cnxpt wherein said organization of knowledge within an area of interest of cnxpts is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt within said area of interest;

v. a general repositioning to a single cnxpt wherein said organization of knowledge within a timeline of cnxpts is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt within said timeline;

vi. a general repositioning to a single cnxpt wherein said organization of knowledge within a timeline ordered area of consideration of cnxpts is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt within said area of consideration;

vii. a general repositioning to a single cnxpt wherein said organization of knowledge within a timeline ordered area of interest of cnxpts is immediately repositioned to a single concept presented as the cntexxt defined by said single cnxpt within said area of interest;

viii. a default form of repositioning based upon the type of requested search;

ix. a null repositioning result wherein no change of positions results;

and

x. an output or action, the result defined by a search analytic;

and

g. specifying the type of results to be produced, where the search invokes an analytic, the pre-designated form of result of the analytic.

243. The method of claim 1 to also provide for locating an information resource or internal resource serving as an information resource by crawling, further including:

a. using zero or more cnxpts as binding points for crawl results, the bound parts selected from the group of;

i. the crawl identity;

ii. a description;

iii. the plan for information gathering including what to crawl, how to crawl, when to crawl, what to create from the crawl, the result set structures to result, determination of relevance, and other parameters for controlling the process;

iv. zero or more reusable queries, a completed query run modifying a result set;

v. the identity of the crawling instance;

vi. the crawling instance status;

vii. the recorded process of gathering, stating the effect on the resulting organization caused by queries, digesting, or culling, referencing the content, action, and the source;

viii. a list of the locators of information resources found as a result set with rsxitems related to irxt info-items representing information resources found, the information from one or more sources, the sources selected from the group;

the internet, a heterogeneous repository, and a document management system;

ix. the dynamic history of work done in gathering and analyzing;

and

x. the overall basis of a crawl to collect and organize a dynamic organization of information relevant to the meaning of the cnxpt;

whereby a crawling engine obtains data from online repositories or mounted repository export data set.

244. The method of claim 1 to also provide for an ordering metric of returned results of a query, further including:

a. accepting zero or more additional parts of a first or next wisdom request command providing zero or more ordering specifications stating an ordering metric to apply to said first form of result after completion of said search if either said form of result, said type of wisdom sought, or said additional specifications indicate that an ordering is to be performed, according to the finding, searching, query and retrieval process means, said ordering by ordering metric to be applied in the order of specification of said additional part, said ordering by said form of result selected from the group consisting of;

b. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing subject matter selected from the group consisting of;

principle, standard, practice, field, jurisdiction, purlieu, trait, law, author, subject, fact, opinion, doctrine, study, study result, lab test report, evidence item, evidence type, element, documentary evidence, theory, topic, category, entry meaning, entry impact, precedent, entry relevance, rule, a user defined content type, an analytic content type;

for cnxpt items based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said second cnxpt meeting criteria of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

c. obtaining a result set from a search to ready for an action on the result set items of the result set, the type of action and type of result set items in the result set selected from the group of;

i. request display of a particular type of structural view of info-items based upon an entered type, to show the result set items of result set;

ii. request termination of interaction with said first form of result;

iii. narrow area of consideration to area of interest by eliminating dxos, ttxs, txos, or cnxpts from inclusion in area, or adding ttxs, txos, or cnxpts into area, according to narrow area of consideration to area of interest means;

iv. categorize or re-categorize cnxpts according to said organization of knowledge;

v. adjust characteristics or properties of search result info-items such as dxos, ttxs, txos, or cnxpts;

vi. prioritize cnxpts for further review according to specified workflow rules or to remove them from further review or from organization of knowledge, domain of wisdom, or commonplace of information;

vii. make contact with a person, project consortia, or organization associated with a result info-item;

viii. requesting purchase of a product associated with a result info-item;

ix. requesting investment in a project consortia, pool, or organization associated with a result info-item;

x. requesting the navigating to a cntexxt based upon wisdom found;

xi. categorizing source objects listed in a result set into an alternative contexts as represented by a cnxpt, said source object of a type selected from the group of;

data sets, meta-data, files, information resources, statements, communications, templates, info-items, legal decisions, docket, story, transcripts, and documents after a query of a prior step has been repeated;

xii. accepting culling commands in manual review to categorize source objects listed in a result set into an alternative contexts as represented by a cnxpt, said source object of a type selected from the group of;

data sets, meta-data, files, information resources, statements, communications, templates, info-items, legal decisions, docket, story, transcripts, and documents;

xiii. accepting culling commands in manual review to re-prioritize source objects listed in a result set for further review according to specified workflow rules or to remove them from further review or from collection of source objects in commonplace of information, said source object of a type selected from the group of;

data sets, meta-data, files, information resources, statements, communications, templates, info-items, legal decisions, docket, story, transcripts, and documents;

xiv. categorizing rows of a data set listed in a result set into an alternative contexts as represented by a cnxpt after a query of a prior step has been repeated;

xv. accepting culling commands in manual review to categorize rows of a data set listed in a result set into an alternative contexts as represented by a cnxpt;

and

xvi. accepting culling commands in manual review to re-prioritize rows of a data set listed in a result set for further review according to specified workflow rules or to remove them from further review;

and

d. accepting zero or one indications that said user has completed use of said first or next wisdom request command and indicating a resolution status for said command, said status selected from the group of;

i. search result satisfied need of user and resulted in locating the wisdom sought, optionally stating a retention paradigm, optionally stating a retention period;

ii. search result satisfied need of user at this time and search command is to be retained, optionally stating a retention paradigm, optionally stating a retention period;

iii. search result failed to satisfy need of user and should be abandoned as inadequate;

iv. a default indication that user has abandoned said search command for an unknown reason, wherein said search command is to be either retained for a predetermined period or retained for a stated period if said search command was previously marked for retention;

v. search result satisfied need of user but resulted in failing to locate the wisdom sought of a concept being conjured by said user while locating a first cntexxt wherein said user signifies that said wisdom should have been, wherein a new cnxpt should be created within said first cntexxt to objectify the concretized conjuring of said concept being conjured by said user, optionally requesting a differentiation from said user, optionally stating a retention paradigm, optionally stating a retention period;

vi. search result satisfied need of user but resulted in failing to locate the wisdom sought of a concept being conjured by said user and represented by a goal cnxpt while locating a first cntexxt wherein said user signifies that said wisdom should have been, wherein said goal is to be converted into a third cnxpt and located within said first cntexxt to objectify the concretized conjuring of said concept being conjured by said user, optionally stating a retention paradigm, optionally stating a retention period, wherein indications regarding the goal of how said concretized conjuring represented by said goal is differentiable from said first concept represented by said first cntexxt represented internally by said first cnxpt are applied to said third cnxpt, optionally requesting a differentiation from said user;

vii. search result satisfied need of user but resulted in failing to locate the wisdom sought while locating a cntexxt wherein said user signifies that said wisdom should have been, and said search command should be codified as a concept represented by a cnxpt;

and

viii. search result satisfied need of user but resulted in failing to locate the wisdom sought while locating a cntexxt wherein said user signifies that said wisdom should have been, and said search command should be codified as a concept represented by a cnxpt.

245. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate a type of result required, further including:

a. accepting zero or one additional parts of a first or next wisdom request command providing an indication of a type of wisdom sought selected from the group consisting of;

i. accepting zero or one additional parts of a first or next wisdom request command providing an indication of general information types of wisdom sought selected from the group consisting of;

01. alert information;

02. analytic information;

03. associative position information navigation;

04. conceptual interrelationship info-item information;

05. entity similarity information;

06. business decision information;

07. business growth progress information;

08. business transaction information;

09. categorization information;

10. characteristic information;

11. commonality information;

12. competitive product information;

13. concept similarity information;

14. consortium artifact information;

15. consortium information;

16. contract transaction information;

17. crawl result information;

18. data availability and sales information;

19. goal information;

20. how-to information about invention;

21. how-to information about invention protection;

22. how-to information about innovative business growth;

23. info-item information;

24. information resource information;

25. interest shown by users;

26. satisfaction shown by users;

27. information about experts;

28. information about participants;

29. investment information;

30. investment opportunity information;

31. investment pool information;

32. investment diligence and vetting information;

33. legal case information;

34. legal case strategy information;

35. legal discovery status information;

36. legal discovery relevance information;

37. legal information;

38. legal precedent information;

39. methodology information;

40. communal mind mapping consensus information;

41. model information;

42. negotiation process tracking information;

43. occurrence information;

44. opinion information;

45. outline construction information;

46. patent clearance process information;

47. patent clearance exposure information;

48. plug-in information;

49. portfolio entry information;

50. portfolio information;

51. portfolio transaction information;

52. prediction information;

53. process analysis information;

54. process control information;

55. product design information;

56. product control information;

57. product longevity information;

58. project control information;

59. property information;

60. purlieu information;

61. registration information;

62. relationship info-item information;

63. research study information;

64. result set information;

65. statistical analysis information;

66. subscription and usage information;

67. survey information;

68. template information;

69. trait information;

70. transaction information;

and

71. workflow information;

ii. accepting zero or one additional parts of a first or next wisdom request command providing an indication of single item types of wisdom sought selected from the group consisting of;

01. a cnxpt info-item satisfying criteria;

02. a conceptual meaning;

03. a consortium info-item;

04. a crawl result;

05. a deal made in a consortium transaction;

06. a deal made in a portfolio transaction;

07. a deal made in an investment pool transaction;

08. a decision made in a consortium business decision;

09. a decision made in a portfolio business decision;

10. a decision made in an investment pool business decision;

11. a differentiator;

12. a discovery objective;

13. a fact to rule applicability ordered pair of cnxpt info-items;

14. a law info-item;

15. a legal charge theory of the case info-item;

16. a legal doctrine or principle info-item;

17. a legal fact info-item;

18. a legal general rule info-item;

19. a legal jurisdiction info-item;

20. a legal precedent info-item;

21. a legal rule element info-item;

22. a legal rule info-item;

23. a legal theory of the case info-item;

24. a link cited in an attached occurrence in said organization of knowledge;

25. a methodology info-item;

26. a model info-item;

27. a modeling result;

28. a participant info-item in a consortium;

29. a precedent successor dependency ordered pair of cnxpt info-items;

30. a prediction outcome info-item;

31. a prediction outcome value;

32. a prediction;

33. a property of a type of interest shown;

34. a property of a type of interest shown;

35. a property of an info-item;

36. a purlieu;

37. a query;

38. a registration;

39. a relationship info-item meaning;

40. a role of a consortium;

41. a set of matching pairings;

42. a set of applicability pairings;

43. a set of dependency pairings;

44. a specific rule;

45. a step in a fxxt specification info-item;

46. a step of a specification of an info-item having a specification for processing;

47. a study info-item;

48. a study objective;

49. a study result;

50. a subscription;

51. a survey result;

52. a task info-item in a timeline of a workflow;

53. a task info-item of a methodology;

54. a task info-item of a workflow;

55. a competitive constraint info-item;

56. a purlieu constraint info-item;

57. a tracked info-item of a consortium;

58. a trait of an info-item;

59. a transaction result;

60. a type of connected relationship;

61. a type of interest shown;

62. a type of relationship info-item;

63. a vote result;

64. a workflow info-item;

65. an information resource reference info-item;

66. an investment pool info-item;

67. an item of a blog;

68. an item of a commonality;

69. an item of a crawl result;

70. an item of a pool info-item;

71. an item of a portfolio info-item;

72. an item of a subscription;

73. an item of a transaction;

74. an occurrence info-item;

and

75. an opinion info-item;

iii. accepting zero or one additional parts of a first or next wisdom request command providing an indication of item identifier types of wisdom sought selected from the group consisting of;

01. an event info-item in a timeline of a workflow;

02. an evidence info-item;

03. an identifiable product of a task of a methodology;

04. an identity indicator an item of a portfolio;

05. an identity indicator of a child in said organization of knowledge;

06. an identity indicator of a commonality;

07. an identity indicator of a consortium info-item;

08. an identity indicator of a crawl result;

09. an identity indicator of a crawl specification info-item;

10. an identity indicator of a descendant in said organization of knowledge;

11. an identity indicator of a descendant leaf in said organization of knowledge;

12. an identity indicator of a fxxt info-item;

13. an identity indicator of a goal info-item;

14. an identity indicator of a methodology info-item;

15. an identity indicator of a model info-item;

16. an identity indicator of a parent in said organization of knowledge;

17. an identity indicator of a participant info-item in a consortium info-item;

18. an identity indicator of a plug-in;

19. an identity indicator of a pool info-item;

20. an identity indicator of a portfolio info-item;

21. an identity indicator of a prediction info-item;

22. an identity indicator of a query specification info-item;

23. an identity indicator of a registration;

24. an identity indicator of a result set;

25. an identity indicator of a role info-item of a consortium info-item;

26. an identity indicator of a sibling in said organization of knowledge;

27. an identity indicator of a step in a fxxt specification;

28. an identity indicator of a step of a methodology info-item;

29. an identity indicator of a step of a model specification info-item;

30. an identity indicator of a step of a prediction specification info-item;

31. an identity indicator of a step of a query specification info-item;

32. an identity indicator of a step of a workflow info-item;

33. an identity indicator of a subscription specification;

34. an identity indicator of a task info-item in a timeline of a workflow info-item;

35. an identity indicator of a task info-item of a methodology info-item;

36. an identity indicator of a task info-item of a workflow info-item;

37. an identity indicator of a tracked item of a consortium info-item;

38. an identity indicator of a transaction info-item;

39. an identity indicator of a type of interest shown;

40. an identity indicator of a workflow info-item;

41. an identity indicator of an alert info-item;

42. an identity indicator of an analytic;

43. an identity indicator of an ancestor in said organization of knowledge;

44. an identity indicator of an ancestor root in said organization of knowledge;

45. an identity indicator of an attached occurrence in said organization of knowledge;

46. an identity indicator of an avatar info-item;

47. an identity indicator of an event info-item in a timeline of a workflow info-item;

48. an identity indicator of an info-item connected by relationship info-item in said organization of knowledge;

49. an identity indicator of an information resource referenced in an attached occurrence info-item in said organization of knowledge;

50. an identity indicator of an item of a blog;

51. an identity indicator of an item of a commonality specification;

52. an identity indicator of an item of a crawl result;

53. an identity indicator of an item of a pool;

54. an identity indicator of an item of a result set;

55. an identity indicator of an item of a subscription;

56. an identity indicator of an item of a transaction;

and

57. an identity indicator value;

iv. accepting zero or one additional parts of a first or next wisdom request command providing an indication of list types of wisdom sought selected from the group consisting of;

01. a list of alerts;

02. a list of analytics;

03. a list of avatars;

04. a list of characteristic or property information regarding an info-item;

05. a list of characteristics;

06. a list of cnxpt info-items;

07. a list of commonalities;

08. a list of conceptual meanings;

09. a list of consortium info-items;

10. a list of crawl info-items;

11. a list of crawl results;

12. a list of decisions made;

13. a list of decisions needed;

14. a list of differentiators;

15. a list of fxxt info-items;

16. a list of goal info-items;

17. a list of identity indicators;

18. a list of info-items;

19. a list of information resource reference info-items;

20. a list of information resources;

21. a list of items of a result set;

22. a list of items of a set of crawl results;

23. a list of items of a set of pools;

24. a list of items of a set of portfolios;

25. a list of items of a subscription;

26. a list of items of a transaction;

27. a list of items of blogs;

28. a list of items of commonalities;

29. a list of links;

30. a list of methodology info-items;

31. a list of model info-items;

32. a list of occurrence info-items;

33. a list of outcome info-items;

34. a list of outcomes possible;

35. a list of pairs of cnxpt dependencies;

36. a list of pairs of cnxpts matching by applicability;

37. a list of pairs of cnxpts matching by interest;

38. a list of pairs of cnxpts matching by suitability;

39. a list of pairs of cnxpts matching by a constraint;

40. a list of pairs of cnxpts matching by trait;

41. a list of pairs of cnxpts matching semantically;

42. a list of participant info-items in a list of consortium info-items;

43. a list of plug-ins;

44. a list of pool info-items;

45. a list of portfolio info-items;

46. a list of precedent successor dependency pairs of cnxpts;

47. a list of prediction info-items;

48. a list of properties of types of interest shown;

49. a list of properties;

50. a list of purlieu;

51. a list of queries;

52. a list of registrations;

53. a list of relationships;

54. a list of result sets;

55. a list of roles of consortiums;

56. a list of steps in fxxts;

57. a list of steps of a specification of an info-item having a specification for processing;

58. a list of steps of a specification of an info-item having a specification stating actions to be taken by a user or to be carried out by a processor;

59. a list of steps of methodologies;

60. a list of steps of models;

61. a list of steps of predictions;

62. a list of task info-items of a specification of an info-item having a specification stating actions to be taken by a user;

63. a list of tasks in timelines of workflows;

64. a list of tasks of a set of methodologies;

65. a list of tasks of a set of workflows;

66. a list of tracked items of consortiums;

67. a list of traits;

68. a list of transactions;

69. a list of types of interest shown;

70. a list of types of relationships;

and

71. a list of workflows;

v. accepting zero or one additional parts of a first or next wisdom request command providing an indication of pair types of wisdom sought selected from the group consisting of;

01. a pair of cnxpts matching by interest;

02. a pair of cnxpts matching by suitability;

03. a pair of cnxpts matching by a constraint;

04. a pair of cnxpts matching by trait;

05. a pair of cnxpts matching semantically;

06. a metric ordered area of consideration of cnxpts;

07. a metric ordered area of interest of cnxpts;

08. a metric ordered result set;

09. an ordered pair of cnxpts matching by suitability of evidence to discovery objective;

10. an ordered pair of cnxpts matching by suitability of evidence to fact;

11. an ordered pair of cnxpts matching by suitability of fact to rule element;

12. an ordered pair of cnxpts matching by suitability of function to audience;

13. an ordered pair of cnxpts matching by suitability of function to need;

14. an ordered pair of cnxpts matching by suitability rule to jurisdiction;

and

15. an ordered pair of cnxpts matching semantically;

vi. accepting zero or one additional parts of a first or next wisdom request command providing an indication of result set types of wisdom sought selected from the group consisting of;

01. a result of a fxxt specification;

02. a result of a model specification;

03. a result of a workflow specification;

04. a result set of pairs of cnxpts matching by interest;

05. a result set of pairs of cnxpts matching by suitability;

06. a result set of pairs of cnxpts matching by a constraint;

07. a result set of pairs of cnxpts matching by trait;

08. a result set of pairs of cnxpts matching semantically;

and

09. a result set of precedence dependency pairs of cnxpts;

vii. accepting zero or one additional parts of a first or next wisdom request command providing an indication of action types of wisdom sought selected from the group consisting of;

01. an action triggered by said search;

02. an action defined by a search analytic triggered by said search;

03. an event triggered by said search;

and

04. an event defined by a search analytic triggered by said search;

viii. accepting zero or one additional parts of a first or next wisdom request command providing an indication of other types of wisdom sought selected from the group consisting of;

01. a general repositioning to a single cnxpt apparently having a meaning best matching, according to a requested search intended by user to indicate the meaning sought as a goal of said user, a point within the cntexxt defined by said single cnxpt to indicate to said user the likely location of the concept defined by said goal, wherein said organization of knowledge is immediately repositioned to said point in said cntexxt;

02. a list, formed in response to a specification requesting the list of immediate children or the cntexxt children or the list of members of said cntexxt of said specifically identified cnxpt in said specifically identified descendent tree, consisting of;

the set of all second cnxpts in a cntexxt represented by a specifically identified cnxpt such that each second cnxpt is the child in a parent-child relationship info-item with said specifically identified cnxpt, wherein said specification also states that said list is to contain only the immediate child cnxpts of said specifically identified cnxpt in said specifically identified descendent tree, said list termed the list of immediate children of said cntexxt represented by said specifically identified cnxpt in said specifically identified descendent tree, said list termed the list of members of said cntexxt represented by said specifically identified cnxpt in said specifically identified descendent tree, said list termed the list of children of said cntexxt represented by said specifically identified cnxpt in said specifically identified descendent tree, each item in said list of members termed a member of said cntexxt represented by said specifically identified cnxpt in said specifically identified descendent tree, each item in said list of members termed a child of said specifically identified cnxpt in said specifically identified descendent tree;

03. a list, formed in response to a specification requesting the list of descendants of said specifically identified cnxpt in said specifically identified descendent tree, consisting of;

the set of all member cnxpts in a cntexxt represented by a specifically identified cnxpt plus each second cnxpt that is the child in a parent-child relationship info-item with any of said member cnxpts or, iteratively, with any other such second cnxpts, but excluding said specifically identified cnxpt, wherein said specification also states that said list is to contain direct descendant cnxpts at all levels of descendancy of said specifically identified cnxpt in said specifically identified descendent tree, said list termed the list of descendants of said specifically identified cnxpt in said specifically identified descendent tree;

04. a list, formed in response to a specification requesting the list of siblings of said specifically identified cnxpt in said specifically identified descendent tree, consisting of;

the set of all member cnxpts in a cntexxt containing a specifically identified cnxpt, said set of member cnxpts reduced to eliminate as a set member said specifically identified cnxpt and the cnxpt representing said cntexxt containing a specifically identified cnxpt, wherein said specification also states that said list is to contain the sibling cnxpts of said specifically identified cnxpt in a specifically identified descendent tree, said list termed the list of siblings of said specifically identified cnxpt in said specifically identified descendent tree;

05. a list, formed in response to a specification requesting the leaf list of said specifically identified cnxpt in said specifically identified descendent tree, consisting of;

the set of all member cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent tree, said list comprising the set of second cnxpts such that the second cnxpt is a descendant of said specifically identified cnxpt if the cntexxt represented by said second cnxpt itself is empty such that said second cnxpt has no descendants in said specifically identified descendent tree, or said specifically identified cnxpt if said specifically identified cntexxt itself is empty such that said specifically identified cnxpt has no descendants in said specifically identified descendent tree, said list termed the leaf list of said specifically identified cntexxt in said specifically identified descendent tree, said leaf cnxpt termed a leaf of said specifically identified cntexxt in said specifically identified descendent tree, said leaf cnxpt termed a leaf of said specifically identified descendent tree;

06. a tree, formed in response to a specification requesting the sub-tree of said cntexxt of said specifically identified cnxpt in said specifically identified descendent tree, consisting of;

the set of all member cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent tree, said list comprising the set of second cnxpts such that the second cnxpt is a descendant of said specifically identified cnxpt and said specifically identified cnxpt, and all interconnecting hierarchical relationships from said specifically identified descendent tree, said hierarchical relationships being either between said member cnxpts or between said member cnxpts and said specifically identified cnxpt, said tree termed the sub-tree of said specifically identified cntexxt in said specifically identified descendent tree, said tree termed the sub-tree of said specifically identified cnxpt in said specifically identified descendent tree, said tree termed a sub-tree of said specifically identified descendent tree;

07. a list, formed in response to a specification requesting the leaf list of a specifically identified sub-tree of a specifically identified descendent tree, consisting of;

the set of all second cnxpts of a specifically identified sub-tree of a specifically identified descendent tree said sub-tree represented by a specifically identified first cnxpt, said list consisting of;

all second cnxpts representing a sub-tree with but one member such that said second cnxpt has no descendants in said specifically identified descendent tree, said list termed the leaf list of said specifically identified first cnxpt in said specifically identified descendent tree, each of said second cnxpts in said leaf list termed a leaf of said specifically identified sub-tree in said specifically identified descendent tree, each of said second cnxpts in said leaf list termed a leaf of said specifically identified descendent tree;

08. a list, formed in response to a specification requesting the parent list of said specifically identified descendent tree, consisting of;

the set of all second cnxpts in a specifically identified descendent tree such that each second cnxpt represents a cntexxt in a specifically identified descendent tree, said cntexxt having at least one member other than said second cnxpt representing said cntexxt, said list termed the parent list of said specifically identified descendent tree, each said second cnxpt in said parent list termed a parent cnxpt in said specifically identified descendent tree, each said parent cnxpt termed the parent of the cntexxt represented by said parent cnxpt in said specifically identified descendent tree;

09. a list, formed in response to a specification requesting the list of uncles of said specifically identified cnxpt in said specifically identified descendent tree or the list of uncles of said cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent tree or an uncle of a member of said cntexxt of which said specifically identified cnxpt is a member in said specifically identified descendent tree, consisting of;

the set of all second cnxpts in a specifically identified descendent tree such that each second cnxpt is a sibling cnxpt of the cnxpt representing the cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent tree but excluding said cnxpt representing the cntexxt of which said specifically identified cnxpt is a member, said list termed the list of uncles of said specifically identified cnxpt in said specifically identified descendent tree, said list termed the list of uncles of said cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent tree, each item in said list of uncles termed an uncle of each member of said cntexxt of which said specifically identified cnxpt is a member in said specifically identified descendent tree;

10. a list, formed in response to a specification requesting the root list of said specifically identified descendent tree, consisting of;

the set of all second cnxpts of a specifically identified descendent tree such that said second cnxpt has no parent in said specifically identified descendent tree regardless of whether said second cnxpt has no children in said specifically identified descendent tree, each said second cnxpt termed a root of said specifically identified descendent tree, said list termed the root list of said specifically identified descendent tree;

11. a list, formed in response to a specification requesting the root list of said specifically identified descendent tree, consisting of;

the set of all second cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified descendent tree, said list containing said specifically identified cnxpt regardless of whether said cntexxt itself is empty such that said specifically identified cnxpt is a leaf and also containing the parent in said specifically identified descendent tree of any said second cnxpt in said list, said list termed the ascendant list of said specifically identified cntexxt in said specifically identified descendent tree, each said second cnxpt termed an ascendant cnxpt of said specifically identified cntexxt in said specifically identified descendent tree, said list together with the hierarchical relationships connecting said ascendant cnxpts to form said specifically identified descendent tree termed the ascendant path of said specifically identified cntexxt in said specifically identified descendent tree;

12. a list, formed in response to a specification requesting the list of uncles of said specifically identified cnxpt in said specifically identified descendent forest or the list of forest uncles of said cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent forest, consisting of;

the set of all second cnxpts in a specifically identified descendent forest such that each second cnxpt is a sibling cnxpt of the cnxpt representing the cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent forest plus any root in said specifically identified descendent forest if said cnxpt representing the cntexxt of which a specifically identified cnxpt is a member is also a root, but excluding said cnxpt representing the cntexxt of which said specifically identified cnxpt is a member, said list termed the list of uncles of said specifically identified cnxpt in said specifically identified descendent forest, said list termed the list of forest uncles of said cntexxt of which a specifically identified cnxpt is a member in said specifically identified descendent forest, each item in said list of uncles termed an uncle of each member of said cntexxt of which said specifically identified cnxpt is a member in said specifically identified descendent forest;

13. a list, formed in response to a specification requesting the root list of said specifically identified descendent forest, consisting of;

the set of all second cnxpts of a specifically identified descendent forest such that said second cnxpt has no parent in said specifically identified descendent forest regardless of whether said second cnxpt has no children in said specifically identified descendent forest and regardless of whether said specifically identified descendent forest has more than one said second cnxpt, each said second cnxpt termed a root of said specifically identified descendent forest, said list termed the root list of said specifically identified descendent forest, said list alternatively termed the forest root list of said specifically identified descendent forest, said specifically identified descendent forest alternatively termed a tree where only a single said second cnxpt exists in specifically identified descendent forest;

14. a list, formed in response to a specification requesting the list of siblings of said specifically identified root cnxpt in said specifically identified descendent tree, consisting of;

the set of all second root cnxpts in a specifically identified descendent forest containing a specifically identified root cnxpt, said set of second root cnxpts reduced to eliminate as a set member said specifically identified root cnxpt, wherein said specification also states that said list is to contain the sibling cnxpts of said specifically identified cnxpt in a specifically identified descendent tree, said list termed the list of siblings of said specifically identified root cnxpt in said specifically identified descendent tree;

15. a list, formed in response to a specification requesting the ascendant sub-tree of said specifically identified cntexxt in said specifically identified ascendant tree, consisting of;

the set of all second cnxpts of a specifically identified cntexxt represented by a specifically identified cnxpt and a specifically identified ascendant tree, said list containing said specifically identified cnxpt regardless of whether said cntexxt itself is empty such that said specifically identified cnxpt is a leaf and also containing the parent in said specifically identified ascendant tree of any said second cnxpt in said list, said list termed the ascendant list of said specifically identified cntexxt in said specifically identified ascendant tree, each said second cnxpt termed an ascendant cnxpt of said specifically identified cntexxt in said specifically identified ascendant tree, said list together with the set of hierarchical relationships connecting said ascendant cnxpts taken from the list of hierarchical relationships connecting said specifically identified ascendant tree termed the ascendant sub-tree of said specifically identified cntexxt in said specifically identified ascendant tree;

16. a visualized map, formed in response to a specification requesting the display of a co-location map of concepts, consisting of;

the visualization of the set of cnxpts within a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, with placement on the root level and placement within any parent cnxpt determined by co-location positioning, according to map generation function means, said map termed a co-location map of said specifically identified forest;

17. a list, formed in response to a specification requesting the primary flow list in said specifically identified forest, consisting of;

the set of all ordered pairs of cnxpts consisting of;

the set of a first cnxpt in a first position and a second cnxpt in the second position such that each said first cnxpt and each said second cnxpt are both in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, such that said first cnxpt is a predecessor in a flow-type directed association to said second cnxpt as successor, said ordered pair termed a primary flow pair in said specifically identified forest, said first cnxpt termed a primary predecessor flow cnxpt of said primary flow pair, said second cnxpt termed a primary successor flow cnxpt of said primary flow pair, said list of ordered pairs termed a primary flow list in said specifically identified forest;

18. a list, formed in response to a specification requesting the same level primary flow list in said specifically identified forest, consisting of;

the set of all primary flow pairs in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, such that the predecessor cnxpt and the successor cnxpt in said primary flow pair are both in the same level as specified from the distance from a root of the forest, said primary flow pair termed a same level primary flow pair, said list of same level primary flow pairs termed a same level primary flow list in said specifically identified forest;

19. a list, formed in response to a specification requesting the different level primary flow list in said specifically identified forest, consisting of;

the set of all primary flow pairs in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, such that the predecessor cnxpt and the successor cnxpt in said primary flow pair are not in the same level as specified from the distance from a root in the forest, said primary flow pair termed a different level primary flow pair, said list of different level primary flow pairs termed a different level primary flow list in said specifically identified forest;

20. a list, formed in response to a specification requesting the same level secondary flow list in said specifically identified forest, consisting of;

the set of all ordered pairs of cnxpts consisting of;

the set of a first cnxpt in a first position and a second cnxpt in the second position such that each said first cnxpt and each said second cnxpt are both in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, such that said first cnxpt and said second cnxpt are both in the same level as specified from the distance from a root of the forest, such that either an ascendant of said first cnxpt is a predecessor in a primary flow pairs where said second cnxpt is successor or that said first cnxpt is a predecessor in a primary flow pairs where an ascendant of said second cnxpt is successor, said ordered pair termed a same level secondary flow pair in said specifically identified forest, said first cnxpt termed a secondary predecessor flow cnxpt of said same level secondary flow pair if said same level secondary flow pair was added because of an ascendant of said first cnxpt in first position, said second cnxpt termed a secondary successor flow cnxpt of said same level secondary flow pair if said same level secondary flow pair was added because of an ascendant of said second cnxpt in second position, said list of ordered pairs termed a same level secondary flow list in said specifically identified forest;

21. a list, formed in response to a specification requesting the same level flow tensor list in said specifically identified forest, consisting of;

the set of all ordered tuples each consisting of;

a first cnxpt, a second cnxpt, and a weight from a set of flow pairs in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, each flow pair selected from the group consisting of;

a same level secondary flow pair and a same level primary flow pair, such that one ordered tuple will exist in the list if any matching flow pair exists wherein said first cnxpt of said ordered tuple is the predecessor cnxpt in a flow pair where said second cnxpt is the successor cnxpt, said ordered tuple forming a weighted summarization of its matching flow pairs such that a weight is computed for said ordered tuple according to the generate flow tensors for enforcing map segment positioning process means, said ordered tuple termed a same level flow tensor, said list of same level flow tensor termed a same level flow tensor list in said specifically identified forest;

22. a list, formed in response to a specification requesting the root level flow tensor list in said specifically identified forest, consisting of;

the set of all ordered tuples each consisting of;

a first cnxpt, a second cnxpt, and a weight generated from the set of same level flow tensors in a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, such that one ordered tuple will exist in the list if any matching same level flow tensor exists wherein said first cnxpt of said ordered tuple is the cnxpt in the first position in a same level flow tensor where said second cnxpt is cnxpt in the second position in said same level flow tensor tuple or said first cnxpt of said ordered tuple is the root of the tree containing the cnxpt in the first position in a same level flow tensor where said second cnxpt is the root of the tree containing the cnxpt in the second position in said same level flow tensor tuple, such that said first and said second cnxpts are roots in said forest, said ordered tuple forming a weighted summarization of its basis same level flow tensor tuples such that a weight is computed for said ordered tuple according to the generate flow tensors for enforcing map segment positioning process means, said ordered tuple termed a root level flow tensor, said list of root level flow tensors termed a root level flow tensor list in said specifically identified forest;

and

23. a visualized map, formed in response to a specification requesting the display of a flow visualization optionally in conjunction with co-location map of concepts, consisting of;

the visualization of the set of cnxpts listed in the ordered tuples of all summarized flow tensors for a specifically identified forest selected from the group consisting of;

ascendant forest and descendent forest, with placement on any level primarily determined by said tensor directions and weights and secondarily influenced by co-location positioning, according to map generation function means and generate flow tensors for enforcing map segment positioning process means, said map termed a flow map of said specifically identified forest.

246. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought from a particular starting point, further including:

a. accepting zero or more additional parts of a first or next wisdom request command each providing a reference to an identified search base to be used as a parameter in said first or next wisdom request in an order given by the ordering of said additional part in said first or next wisdom request specification, said identified search base selected from the group consisting of;

i. a reference to a search cnxpt base the first defined and identifiable cnxpt selected from the group consisting of;

01. a specifically identified cnxpt as specified by an identity indicator;

02. the first cnxpt in a specifically identified list specified to be generated first;

03. an indicated cnxpt;

04. a cnxpt represented by a cntexxt presently selected in a visualization;

and

05. a cnxpt represented by the cntexxt presently being focused upon in a visualization;

ii. a reference to a search cnxpt list base the first defined and identifiable list of cnxpts selected from the group consisting of;

01. a specifically identified result set of cnxpts containing a plurality of identity indicators;

02. a specifically identified list of cnxpts containing a plurality of identity indicators;

03. a list of cnxpts in a specifically identified list being the first form of result of a prior wisdom request command termed herein as an identified list specified to be generated first;

04. an indicated result set of cnxpts containing a plurality of identity indicators;

05. an indicated list of cnxpts containing a plurality of identity indicators;

06. a list consisting of;

the set of cnxpts in a cntexxt presently indicated in a visualization and represented by a cnxpt;

07. a list created from the set of all cnxpts selected in a selected grouping;

08. a list consisting of;

the set of cnxpts in a cntexxt presently selected in a visualization and represented by a cnxpt;

and

09. a list consisting of;

the set of cnxpts in a cntexxt presently focused upon in a visualization and represented by a cnxpt;

iii. a reference to a search info-item base the first defined and identifiable info-item selected from the group consisting of;

01. a specifically identified info-item;

02. the first info-item in a specifically identified list specified to be generated first;

03. an indicated info-item;

and

04. a info-item presently selected in a visualization;

iv. a reference to a search info-item list base the first defined and identifiable list of info-items selected from the group consisting of;

01. a specifically identified result set of info-items containing a plurality of identity indicators;

02. a specifically identified list of info-items containing a plurality of identity indicators;

03. a list being the first form of result of a prior wisdom request command termed herein as an identified list specified to be generated first;

04. an indicated result set of info-items containing a plurality of identity indicators;

05. an indicated list of info-items containing a plurality of identity indicators;

06. a list consisting of;

the set of info-items selected in a visualization;

and

07. a list consisting of;

the set of info-items presently focused upon in a visualization;

v. a reference to a search relationship info-item base the first defined and identifiable relationship info-item selected from the group consisting of;

01. a specifically identified relationship info-item;

02. the first relationship info-item in a specifically identified list specified to be generated first;

03. an indicated relationship info-item;

and

04. a relationship info-item presently selected in a visualization;

vi. a reference to a first search relationship info-item list base the first defined and identifiable list of relationship info-items selected from the group consisting of;

01. a specifically identified result set of relationship info-items containing a plurality of identity indicators;

02. a specifically identified list of relationship info-items containing a plurality of identity indicators;

03. a list created from the set of all relationships connected to a cnxpt representing a cntexxt specifically identified;

04. a list created from the set of all relationships connected to the plurality of cnxpts in the set of cnxpts in a cntexxt specifically identified;

05. a list being the first form of result of a prior wisdom request command termed herein as an identified list specified to be generated first;

06. an indicated result set of relationship info-items containing a plurality of identity indicators;

07. an indicated list of relationship info-items containing a plurality of identity indicators;

08. a list created from the set of all relationships connected to a cnxpt representing a cntexxt presently selected in a visualization;

specifically identified in additional;

09. a list created from the set of all relationships connected to a cnxpt representing a cntexxt presently selected in a visualization;

10. a list created from the set of all relationships connected to a cnxpt representing a cntexxt presently selected in a visualization;

11. a list created from the set of all relationships connected to the plurality of cnxpts in the set of cnxpts in a cntexxt presently selected in a visualization and represented by a cnxpt;

12. a list consisting of;

the set of relationship info-items selected in a visualization;

13. a list created from the set of all relationships connected to a cnxpt representing a cntexxt presently indicated in a visualization;

14. a list created from the set of all relationships connected to the plurality of cnxpts in the set of cnxpts in a cntexxt presently indicated in a visualization and represented by a cnxpt;

15. a list consisting of;

the set of relationship info-items presently focused upon in a visualization;

16. a list created from the set of all relationships connected to a cnxpt representing a cntexxt presently focused upon in a visualization;

and

17. a list created from the set of all relationships connected to the plurality of cnxpts in the set of cnxpts in a cntexxt presently focused upon in a visualization;

vii. a reference to a search value base the first defined and identifiable value selected from the group consisting of;

01. a specifically identified value given in said additional specification;

and

02. the value of the first entry in a specifically identified list specified to be generated first;

viii. a reference to a identified search base the first defined and identifiable list of values selected from the group consisting of;

01. a result set of values, specifically identified in said additional specification, containing a plurality of values;

02. a list of values, specifically identified in said additional specification, containing a plurality of values;

03. a list being the first form of result of a prior wisdom request command termed herein as an identified list specified to be generated first;

04. an indicated result set of values containing a plurality of values;

and

05. an indicated list of values containing a plurality of values;

ix. a reference to a search type identifier base the first defined and identifiable type identifier selected from the group consisting of;

01. a specifically identified type identifier given in said additional specification;

and

02. the type identifier of the first entry in a specifically identified list specified to be generated first;

x. a reference to a identified search base the first defined and identifiable list of type identifiers selected from the group consisting of;

01. a result set of type identifiers, specifically identified in said additional specification, containing a plurality of type identifiers;

02. a list of type identifiers, specifically identified in said additional specification, containing a plurality of type identifiers;

03. a list being the first form of result of a prior wisdom request command termed herein as an identified list specified to be generated first;

04. an indicated result set of type identifiers containing a plurality of type identifiers;

and

05. an indicated list of type identifiers containing a plurality of type identifiers;

xi. a reference to a search data set row of the first defined and identifiable data set selected from the group consisting of;

01. a specifically identified data set and an ordering query equivalent to an SQL select with an order by clause;

02. an indicated data set row;

03. a data set row presently selected in a result set list of data set rows;

and

04. a data set row presently selected in a display list;

xii. a reference to a search data set table of the first defined and identifiable data set selected from the group consisting of;

01. a specifically identified data set and a table identity;

02. a specifically identified data set and a generating query equivalent to an SQL select;

03. an indicated data set table;

04. a data set table formed from the plurality of rows presently selected in a result set list of data set rows;

05. a data set table presently selected in a result set list of data set tables;

06. a data set table presently selected in a display list;

and

07. a data set and a temporary table being the first form of result of a prior wisdom request command termed herein as an identified data set temporary table specified to be generated first;

xiii. a reference to a search goal base the first defined and identifiable goal selected from the group consisting of;

01. a specifically identified goal as specified by an identity indicator;

02. an indicated goal;

03. a goal presently selected in a visualization;

and

04. a goal presently being focused upon in a visualization;

xiv. a reference to a matching, dependency, applicability, or other list of pairings the first defined and identifiable item or list selected from the group consisting of;

01. a specifically identified pairing as specified by an identity indicator;

02. a specifically identified pairing list;

03. a relationship info-item stating a pairing presently indicated in a visualization;

04. a set of relationships stating pairings presently indicated in a visualization;

05. a relationship info-item stating a pairing presently selected in a visualization;

and

06. a set of relationships stating pairings presently selected in a visualization;

xv. a reference to a search result set;

xvi. a reference to a fxxt specification extraction set possibly unresolved;

xvii. a reference to a list of information resources identity indicator values;

xviii. a reference to a search query specification step possibly unresolved;

xix. a reference to a search query specification possibly unresolved;

and

xx. a reference to a database search query possibly unresolved.

247. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought based upon additional criteria, further including:

a. accepting zero or more additional parts of a first or next wisdom request command each providing an additional specification to be used as a value, weight, parameter, indicator, switch, ordering, type, structure, object, analytic, degree of fuzziness, or other criterion in said first or next wisdom request in a priority order given by the ordering of said additional part in said first or next wisdom request specification such that any subsequent additional specification part of the same type will be utilized, in order, only if its sequence ordinal is less than or equal to the number of such criterion of such type called for in said search request specification of said first or next wisdom request command, said additional specification selected from the group consisting of;

i. a reference to a search query specification based upon which said result set presently existing was last modified, such that a default value of a null list is established if no reference is otherwise specified;

ii. an indicator stating whether a weighting is to be applied when combining consensus and said user'"'"'s opinion, such that a default value equivalent to indicating that no weighting is to be applied is established if no indicator is otherwise specified;

iii. a weighting specification for combining consensus and said user'"'"'s opinion, such that a default value of all coefficients being equal to one is to be applied is established if no weighting specification is otherwise specified;

iv. a relevance coefficient specification for combining consensus and said user'"'"'s opinion, such that a default value of all relevance coefficients being equal to one is to be applied is established if no relevance specification is otherwise specified;

v. a pertinence coefficient specification for combining consensus and said user'"'"'s opinion, such that a default value of all pertinence coefficients being equal to one is to be applied is established if no pertinence specification is otherwise specified;

vi. an indicator stating whether a degree of fuzziness is to be applied when combining consensus and said user'"'"'s opinion, such that a default value equivalent to indicating that no fuzziness is to be applied is established if no indicator of use of fuzziness is otherwise specified;

vii. a value of a degree of fuzziness for combining consensus and said user'"'"'s opinion, such that a default value of no fuzziness is to be applied is established if no fuzziness specification is otherwise specified;

viii. a value of a per-level inheritance effect dampening coefficient for combining consensus and said user'"'"'s opinion based upon common ancestry in an organization of knowledge, such that a value of said per-level inheritance effect dampening coefficient is specified for a stated number of levels separating two cnxpts in an organization of knowledge, such that a default value of one is to be applied is established if no per-level inheritance effect dampening coefficient specification is otherwise specified;

ix. an indicator stating whether an ordering is to be applied to said first form of result after completion, such that a default value equivalent to indicating that no ordering is to be applied is established if no indicator is otherwise specified;

x. a type of ordering to apply to said first form of result after completion, such that a default for ordering is by said form of result selected from the group consisting of;

01. for modeling result, estimation, and prediction forms of result, a value of null ordering is to be applied if no metric is specified;

02. for timeline forms of result, ordering is by a time, process precedence, event precedence, or other metric, a default type of temporal ordering is to be applied if no type or metric is specified;

03. for co-location and area map forms of result, ordering for co-location is by descendent tree extraction process means based upon results of fxxt extraction process means;

04. for flow maps forms of result, ordering for flow is by a time, process precedence, event precedence, or other metric, a default type of temporal ordering is to be applied if no type or metric is specified;

05. for movement, ordering is by weighted averaging of algorithm scoring utilizing similarity criteria and a default type of least distance to move is to be applied if no ordering specification type is specified;

and

06. for list, portfolio table, report, and result set forms of result, ordering is by weighted averaging of algorithm scoring utilizing similarity criteria and a default type of null or random ordering is to be applied if no ordering specification type is specified;

xi. a type value, such that a default value equivalent to inclusion of all types are to be applied is established if no type specification is otherwise specified;

xii. an citation type value, such that a default value equivalent to a name citation type is established if no citation type specification is otherwise specified;

xiii. a causality type value, such that a default value equivalent to a simple, categorical, direct, precipitating causality type is established if no causality type specification is otherwise specified;

xiv. a probability distribution, such that a default value equivalent to perfect likelihood is established if no distribution specification is otherwise specified, said distribution optionally having a characteristic function or non-linear or non-continuous description;

xv. an identity indicator type value, such that a default value equivalent to a name identity indicator type in a default language is established if no identity indicator type specification is otherwise specified;

xvi. an identity indicator type value indicating a result set item descriptor, such that a default value equivalent to a name identity indicator type in a default language is established if no identity indicator type value indicating a result set item descriptor is otherwise specified;

xvii. an identity indicator type value indicating a result set item unique identity indicator, such that a default value equivalent to null is established if no identity indicator type value indicating a result set item unique identity indicator is otherwise specified;

xviii. an identity indicator indicating an organization of knowledge;

xix. a list combination specification;

xx. a number of characters;

xxi. a position in a string;

xxii. a number of entries;

xxiii. a value of the form of an identity indicator;

xxiv. a value of the form of an info-item property;

xxv. a value of the form of an info-item characteristic;

xxvi. a value of the form of a trait;

xxvii. a value of the form of a purlieu;

xxviii. a value of the form of a keyword;

xxix. a value of the form of an info-item characteristic identifier;

xxx. a value of the form of an info-item property identifier;

xxxi. a value of the form of a data set attribute identifier;

xxxii. a value of the form of a data set attribute;

xxxiii. a value of the form of a data set table identifier;

xxxiv. a position in a list;

xxxv. a number of items;

xxxvi. a position in a result set list;

xxxvii. a collating sequence, such that a default value from a system preference is established if no string specification is otherwise specified;

xxxviii. a language, such that a default value from a system preference is established if no string specification is otherwise specified;

xxxix. a text string, such that a default value of a null string is established if no string specification is otherwise specified;

xl. a regular expression string, such that a default value of a null string is to be applied is established if no string specification is otherwise specified;

xli. a string, such that a default value of a null string is established if no string specification is otherwise specified;

xlii. a value of a parameter;

and

xliii. a value of a pre-established preference;

and

b. accepting zero or one additional part of a first or next wisdom request command providing a specification for search to obtain contents for said first form of result to serve as a subsequent frame of reference by selection of said type of wisdom sought, considering criterion specified in other said parts of a first or next wisdom request command, said wisdom optionally based upon an optionally weighted combination of consensus and the user'"'"'s opinion according to said additional specification, said wisdom optionally based upon an optional fuzziness factor according to said additional specification, according to the ideation process means and finding searching query and retrieval process means and selection set management process means and focus on information process means and alter information through visualization process means, said specification for search selected from the group consisting of;

i. requesting an empty set;

ii. requesting a default set;

iii. requesting a search by analytic;

iv. requesting a set containing a specified Boolean combination of the items in a first said identified search base and the items in a second said identified search base;

v. requesting a set containing a specified subset of the items in a first said identified search base, said specified subset selected from the group consisting of;

01. the first item in a first said identified search base in the present ordering of said first identified search base;

02. the last item in a first said identified search base in the present ordering of said first identified search base;

03. the first n items in a first said identified search base with lowest specified identity indicator in a collating sequence specified such that the lowest identity indicator valued item is considered the front of said list, wherein n is zero or a positive whole number such that if n is greater then the number of items in said list then only the items in said list will be included in the specified subset;

04. the last n items in a first said identified search base with lowest specified identity indicator in a collating sequence specified such that the lowest identity indicator valued item is considered the front of said list, wherein n is zero or a positive whole number such that if n is greater then the number of items in said list then only the items in said list will be included in the specified subset;

05. the middle n items, starting at the item m in a first said identified search base with lowest specified identity indicator in a collating sequence specified such that the lowest identity indicator valued item is considered the front of said list, wherein n is zero or a positive whole number such that if n is greater then the number of items in said list then only the items in said list will be included in the specified subset, such that if m is greater than the count of items in the list the subset will have no entries, such that if the number of items in said list is t, then the number of items in the resulting subset will be the minimum oft minus m, or the value n;

06. the items in a first said identified search base having a specified value for a specified property;

07. the items in a first said identified search base having a specified value for a specified characteristic;

and

08. the items in a first said identified search base having a specified value for a specified identity indicator;

vi. requesting a set containing a specified subset of the candidate items in a first said identified search base, such that to a specified degree of fuzziness said one or more types of wisdom sought of said candidate item matches a string of text, optionally wild-carded, given in said additional specification, by a combination of one or more specified matching criteria according to find, findall, result set find, resultsetfindall, or findall search and attach result set to goal process means, said matching criteria selected from the group consisting of;

01. begins with;

02. does not begin with;

03. ends with;

04. does not ends with;

05. equals;

06. does not equal;

07. contains;

08. has meaning similar to;

09. does not have meaning similar to;

10. has matches to words specified;

11. matches according to a regular expression;

12. matches according to a Boolean word search;

and

13. has a plurality of words in pairwise proximity to one another by one or more distance factors;

vii. requesting a set containing a specified subset of the candidate items in a first said identified search base, such that to a specified degree of fuzziness said one or more types of wisdom sought meets criteria given in said additional specification selected from the group consisting of;

01. has said one or more types of wisdom sought having a non-null value;

02. has said one or more types of wisdom sought having a value matching a value given in a second said identified search base;

03. has said one or more types of wisdom sought having a type value matching a value given in a second said identified search base;

04. has said one or more types of wisdom sought having a fxxt matching a value for a fxxt identity indicator matching a value given in a second said identified search base;

05. is attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

06. is relevant to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

07. is related to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

08. is cited by an information resource given by one or more occurrences attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

09. cites an information resource given by one occurrence attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

10. cites an information resource given by one or more occurrences attached to a cnxpt having an identity indicator given in a second said identified search base of cnxpts;

11. has an identity indicator meeting criteria given by said additional specification;

12. has an identity indicator given in a second said identified search base of cnxpts;

13. has an identity indicator meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

14. has a characteristic value meeting criteria given by said additional specification;

15. has a characteristic value given in a second said identified search base of cnxpts;

16. has a characteristic value meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

17. has a trait meeting criteria given by said additional specification;

18. has a trait given in a second said identified search base of cnxpts;

19. has a trait meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

20. has a property meeting criteria given by said additional specification;

21. has a property given in a second said identified search base of cnxpts;

22. has a property meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

23. has a purlieu meeting criteria given by said additional specification;

24. has a purlieu given in a second said identified search base of cnxpts;

25. has a purlieu meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

26. has an attribute meeting criteria given by said additional specification;

27. has an attribute given in a second said identified search base of cnxpts;

28. has an attribute meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

29. has a keyword meeting criteria given by said additional specification;

30. has a keyword given in a second said identified search base of cnxpts;

31. has a keyword meeting criteria given by said additional specification to compare against a value given in a second said identified search base;

and

32. has a field, specified by said additional specification, said field selected from the group consisting of;

identity indicator, property value, characteristic value, trait, purlieu, attribute, and keyword, meeting criteria given by said additional specification, matching against a specified value given in a second said identified search base;

viii. requesting said one or more types of wisdom sought for a concept represented by an item in the list created from the set of all items in a first said identified search base cnxpt;

ix. requesting information for a concept represented by a set of cnxpts ostensibly belonging in a cntexxt wherein said information is a part of the wisdom available for the cnxpt representing said cntexxt, said cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

x. requesting a list of properties defined for a cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

xi. requesting a value for a characteristic of a cnxpt in the list created from the set of all items in a first said identified search base cnxpt;

xii. requesting a value for a characteristic of an info-item in the list created from the set of all items in a first said identified search base;

xiii. requesting a list of values of characteristics of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xiv. requesting a list of values of characteristics of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xv. requesting a result set list for culling list items of info-items connected to a cnxpt to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set list created from the set of all info-items connected to a cnxpt in a first said identified search base, said info-items of a type specified in said additional specification, said result set items ordered by a characteristic or property value wherein said characteristic or property is specified in said additional specification;

xvi. requesting a result set list for culling list items of info-items connected to a cnxpt to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set list created from the set of all info-items connected to a cnxpt in a first said identified search base, said info-items of a type specified in a second said identified search base, said result set items ordered by a characteristic or property value wherein said characteristic or property is specified in said additional specification;

xvii. requesting a list of values of properties of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xviii. requesting characteristic or property information regarding an info-item in the list created from the set of all items in a first said identified search base;

xix. requesting a list of values of properties of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xx. requesting a fact or an estimation of a fact represented by a value for a characteristic of an info-item in the list created from the set of all items in a first said identified search base;

xxi. requesting a fact or an estimation of a fact represented by a value for a characteristic of a specific set of info-items in the list created from the set of all items in a first said identified search base;

xxii. requesting a fact or an estimation of a fact represented by a value for a characteristic of specific types of info-item listed in the list created from the set of all items in a first said identified search base listing info-item type identifiers;

xxiii. a fact or an estimation of a fact represented by a value for a characteristic of a specific type for a concept represented by a set of cnxpts ostensibly belonging in a cntexxt wherein said information is a part of the wisdom available for the cnxpt representing said cntexxt, said cnxpt in the list created from the set of all items in a first said identified search base;

xxiv. requesting said one or more types of wisdom sought for an info-item wherein said information is a part of the wisdom available for said info-item, said info-item in the list created from the set of all items in a first said identified search base;

xxv. requesting a list of identity indicators of a set of info-items in the list created from the set of all items in a first said identified search base;

xxvi. requesting a list of identity indicators of info-items connected to a cnxpt in the list created from the set of all items in a first said identified search base;

xxvii. requesting a list of identity indicators of info-items connected to a cnxpt in the list created from the set of all items in a first said identified search base of a type of info-item listed in a second said identified search base listing info-item type identifiers;

xxviii. requesting information for a concept represented by a cnxpt wherein said information is external to said commonplace, but is likely related to said cnxpt in the list created from the set of all items in a first said identified search base;

xxix. requesting characteristic or property information regarding an occurrence in the list created from the set of all items in a first said identified search base where said item is an occurrence info-item;

xxx. requesting a relevance ranking of an information resource relevant to a cnxpt, said information resource likely to contain said wisdom, said cnxpt in the list created from the set of all items in a first said identified search base where said item is a cnxpt;

xxxi. requesting an information resource relevant to a cnxpt, said information resource likely to contain said wisdom, said cnxpt in the list created from the set of all items in a first said identified search base where said item is a cnxpt;

xxxii. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item of a type listed in a second said identified search base listing info-item type identifiers;

xxxiii. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item having a characteristic of a type specified in said additional specification and a value listed in a second said identified search base;

xxxiv. requesting a list of identity indicators of relationships in the list created from the set of all items in a first said identified search base where said item is a relationship info-item having a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxv. requesting a list of identity indicators of traits attached to cnxpts in the list created from the set of all items in a first said identified search base where said trait has a property with a value specified in said additional specification;

xxxvi. requesting a list of identity indicators of traits attached to cnxpts in the list created from the set of all items in a first said identified search base where said trait has a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxvii. requesting a list of identity indicators of purlieu attached to cnxpts in the list created from the set of all items in a first said identified search base where said purlieu has a property with a value specified in said additional specification;

xxxviii. requesting a list of identity indicators of purlieu attached to cnxpts in the list created from the set of all items in a first said identified search base where said purlieu has a property of a type specified in said additional specification and a value listed in a second said identified search base;

xxxix. requesting a result set list for culling list items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria;

xl. requesting a result set list for culling list items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base;

xli. requesting a result set list for culling list items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlii. requesting a result set list for culling information resource items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria;

xliii. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base;

xliv. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlv. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all information resource returned from a search request, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlvi. requesting a result set list for culling information resource items of a type to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said result set created from the set of all information resources returned from a search request to determine information resources relevant to a cnxpt in the set of all items in a first said identified search base, said result set items ordered by a characteristic value wherein said characteristic is specified in said additional specification;

xlvii. requesting a result set to build a goal by query from a search query, said result set implying a concept sought by said user by searching for said goal;

xlviii. requesting a result set of information resources to build a goal, said result set implying a concept sought by said user by searching for said goal;

xlix. requesting a repositioning for navigation to a best cntexxt of a set of better cntexxts each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said best cntexxt represented by a cnxpt having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

l. requesting a list for picking a selection of what appears to said user as a best cntexxt of a set of better cntexxts listed, each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said cnxpts optionally having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

li. requesting a repositioning for navigation into an area of consideration of better cntexxts each represented by a cnxpt from the set of all items in a first said identified search base where said items are cnxpts, said cntexxts each represented by a cnxpt having a value for a characteristic wherein said characteristic is specified in said additional specification, said characteristic indicating a quality score for the predetermined purpose of indicating similarity in regard to an indicated goal being sought;

lii. requesting a list of cnxpts representing concepts for inclusion in an area of consideration or area of interest for navigating, according to said user'"'"'s own criteria;

liii. requesting a result selected from the group consisting of;

01. movement of user focus to a context represented by a second cnxpt, said second cnxpt appearing first in a list of results in an order specified in said additional specification, said second cnxpt representing a second cntexxt;

02. list of identity indicators of a type specified by said additional specification listing, in an order specified in said additional specification, said list for selecting cnxpt items based upon what appears to the user as a good choice according to said user'"'"'s own criteria, said identity indicator of each second cnxpt representing a second cntexxt;

03. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for culling cnxpt items based upon what appears to the user as a good choice of culling action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, altering an item value, entering an opinion, item addition, and item removal, said identity indicator of each second cnxpt representing a second cntexxt;

04. a timeline listing identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

05. a list of conceptual meanings listing, in an order specified in said additional specification, said conceptual meaning in a language specified by said additional specification, said conceptual meaning of a second cnxpt representing a second cntexxt;

06. a timeline listing conceptual meanings of a type and language specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

07. a co-location map for associative searching, navigation, or a predetermined purpose, said map created from the set of all second cnxpts representing second cntexxts;

08. a flow map for associative searching of a process, navigation, or a predetermined purpose, showing each identity indicator of a type specified by said additional specification listing, in an ordering for flow based upon a specified flow relationship info-item type specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt, said map created from the set of all said second cnxpts representing second cntexxts;

09. a co-location map with flow for associative searching, searching of a process, navigation, or a predetermined purpose, showing each identity indicator of a type specified by said additional specification listing, in an ordering for flow based upon a specified flow relationship info-item type specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt, said map created from the set of all said second cnxpts representing second cntexxts;

10. a list of values of a characteristic, in an order specified in said additional specification, in a language specified by said additional specification, said value of a characteristic of a second cnxpt representing a second cntexxt;

11. a list of differentiations in conceptual meaning listing, in an order specified in said additional specification, each such differentiation in a language specified by said additional specification, said differentiation of a second cnxpt representing a second cntexxt;

12. a list of differentiations of a characteristic of a specified type specified by said additional specification listing, in an order specified in said additional specification, said characteristic value of each second cnxpt representing a second cntexxt;

13. a timeline listing differentiations of conceptual meanings of a type and language specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

14. an area of consideration for culling cnxpt items to improve said area of consideration'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said area of consideration created from the set of all second cnxpts representing second cntexxts;

15. an area of interest for culling cnxpt items to improve said area of interest'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said area of interest created from the set of all second cnxpts representing second cntexxts;

16. a portfolio information table listing values of info-items of types specified by said additional specification, listing one or more values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, for reviewing info-items of said types specified to improve said portfolio'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said portfolio created from information related to items in the set of all second cnxpts representing second cntexxts;

17. modeling results of types specified by said additional specification listing one or more result values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said results for each second cnxpt representing a second cntexxt;

18. an estimation of a fact represented by a modeling result of a type specified by said additional specification and a degree of fuzziness specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said estimation for each second cnxpt representing a second cntexxt;

19. an estimation of the probability of the existence of a fact represented by a modeling result of a type specified by said additional specification, a degree of fuzziness specified by said additional specification, and a time frame specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said estimation for each second cnxpt representing a second cntexxt;

20. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing modeling results for cnxpt items based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said second cnxpt meeting criteria based upon a modeling result of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

21. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing outcomes based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, item information research, item information collection, initiating contact, prediction acceptance, prediction rejection, ranking, altering an item value, entering an opinion, item addition, and item removal, said outcome meeting criteria based upon a modeling result of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, based upon one or more second cnxpts each representing a second cntexxt;

22. a result set of identity indicators of a type specified by said additional specification listing each identity indicator of a type specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value wherein said characteristic is specified in said additional specification, said result set list for reviewing subject matter selected from the group consisting of;

principle, standard, practice, field, jurisdiction, purlieu, trait, law, author, subject, fact, opinion, doctrine, study, study result, lab test report, evidence item, evidence type, element, documentary evidence, theory, topic, category, entry meaning, entry impact, precedent, entry relevance, rule, a user defined content type, an analytic content type;

for cnxpt items based upon what appears to the user as a good choice of adjustment action according to said user'"'"'s own criteria to improve said result set list'"'"'s quality for a predetermined purpose by an action selected from the group consisting of;

a user defined action for a purpose, ranking, scoring, re-prioritizing, rebuilding, altering an item value, entering an opinion, item information research, item information collection, initiating contact, item addition, and item removal, said second cnxpt meeting criteria of a type specified by said additional specification with zero or more satisfaction criterion values specified by said additional specification, said identity indicator of each second cnxpt representing a second cntexxt;

23. a report of information regarding audience strength based upon interest shown, based upon one or more second cnxpts each representing a second cntexxt;

24. a report of information regarding general audience strength, based upon one or more second cnxpts each representing a second cntexxt;

25. a report of information regarding dependent audience strength based upon a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

26. a report of information regarding interest shown, based upon one or more second cnxpts each representing a second cntexxt;

27. a report of information regarding interest shown for a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

28. a report of information regarding dependent audience strength based upon a relationship info-item traversal based upon one or more second cnxpts as origins, said second cnxpts each representing a second cntexxt;

29. a report of information regarding normalized interest shown metrics for one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

30. a report of information regarding normalized interest shown metrics for a relationship info-item traversal based upon one or more destination second cnxpts, said second cnxpts each representing a second cntexxt;

31. a list of tuples of cnxpt identity indicators being pairs consisting of;

two cnxpts such that a first cnxpt matches a second cnxpt according to relationships entered by users or by matching criteria of a type specified in said wisdom request command parts, in an order specified in said additional specification, each second cnxpt representing a second cntexxt;

and

32. prediction results of types specified by said additional specification listing one or more prediction values for each of said types as specified by said additional specification listing, in an order specified in said additional specification or ordered by a characteristic value or modeling result value wherein said characteristic or modeling result value is as specified in said additional specification, said prediction results based upon each second cnxpt representing a second cntexxt;

wherein the specification for the plurality of organizations of knowledge providing a base structure is selected from the group consisting of;

33. the organization of knowledge presently indicated;

34. the organization of knowledge presently selected;

35. the organization of knowledge specified in said additional specification;

36. the set of organizations of knowledge listed in said first identified search base;

37. the organization of knowledge in which the first item in said first identified search base resides;

38. the set of organizations of knowledge in which an item in said first identified search base resides;

39. the set of all organizations of knowledge;

40. a null organization of knowledge;

and

41. a default organization of knowledge;

wherein a set of constraints are applied, said set of constraints selected from the group consisting of;

42. wherein said second cnxpt is in the set of cnxpts in said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a cnxpt residing in said organizations of knowledge;

43. wherein said second cnxpt is in the set of cnxpts in said plurality of organizations of knowledge providing a base structure, said second cnxpt is an encompassing cntexxt of the first item in said first identified search base from as a starting point in the genealogy or a cntexxt encompassing such an encompassing cntexxt of the first item in said first identified search base up to the root of the tree in which said first item in said first identified search base resides, said second cnxpt termed an ancestor cnxpt;

44. wherein said second cnxpt is in the set of cnxpts in said plurality of organizations of knowledge providing a base structure, said second cnxpt is encompassed by the genealogy defined by a subtree of cntexxts wherein a first cnxpt of said first identified search base is the root of said subtree, to an optionally specified depth within the subtree up to including all leaves in the genealogy given, said second cnxpt termed a descendant cnxpt;

45. wherein said second cnxpt is in said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is a root in one or more of the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed an encompassing root cnxpt;

46. wherein said second cnxpt is in said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is a root in one or more of the genealogies in said plurality of organizations of knowledge providing a base structure in which an item in said first identified search base resides, said second cnxpt termed a root cnxpt encompassing a specified cnxpt;

47. wherein said second cnxpt is in said plurality of organizations of knowledge providing a base structure, wherein if said first item in said first identified search base is a cnxpt it is not included in the result set, said second cnxpt termed a domain relative;

48. wherein said second cnxpt is not in said plurality of organizations of knowledge providing a base structure;

49. wherein said second cnxpt is in said second identified search base such that said second cnxpt is not in said plurality of organizations of knowledge providing a base structure;

50. wherein said second cnxpt represents a concept similar in meaning to the meaning given by any item of said first identified search base based upon relationships created by users from their own belief or a score value determined by specified similarity criteria given by said additional specification, said second cnxpt termed a cnxpt similar according to a specific characteristic;

51. wherein said second cnxpt represents a concept similar in meaning to the meaning given by any item of said first identified search base based upon relationships created by users from their own belief or a score value determined by specified similarity criteria given by said additional specification involving a specified weighted averaging of specified similarity criteria given by said additional specification, said second cnxpt termed a cnxpt similar according to a weighted averaging of characteristic similarities;

52. wherein said second cnxpt represents a concept similar in meaning to the meaning given by any item of said first identified search base based upon relationships created by users from their own belief or a score value determined by specified similarity criteria given by said additional specification involving a specified weighted averaging of specified similarity criteria given by said additional specification including a commonality specified by said additional specification, said second cnxpt termed a cnxpt similar according to a stated commonality;

53. wherein said second cnxpt is related to items in said first identified search base by a specified relationship info-item type, said second cntexxt termed related by a specific relationship;

54. wherein said second cnxpt is related by a relationship info-item to one or more items in said first identified search base such that said one or more items in said first identified search base is within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a cnxpt related by a specific internal relationship;

55. wherein said second cnxpt is related by a relationship info-item to one or more items in said first identified search base such that said one or more items in said first identified search base is within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure such that said second cntexxt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a cnxpt related by a specific relationship info-item external to the genealogies, said second cnxpt termed a cnxpt related by a specific external relationship;

56. wherein a citation relationship info-item exists from said second cnxpt to one or more items in said first identified search base wherein said second cnxpt is the citing object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a citing cnxpt external to the organization of knowledge, said second cntexxt termed an external citing cnxpt;

57. wherein a citation relationship info-item exists from said second cnxpt to one or more items in said first identified search base wherein said second cnxpt is the citing object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a citing cnxpt internal to the organization of knowledge, said second cnxpt termed an internal citing cnxpt;

58. wherein a citation relationship info-item exists from said second cnxpt to one or more items in said first identified search base wherein said second cnxpt is the cited object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a cited cnxpt external to the organization of knowledge, said second cntexxt termed an external cited cnxpt;

59. wherein a citation relationship info-item exists from said second cnxpt to one or more items in said first identified search base wherein said second cnxpt is the cited object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a cited cnxpt internal to the organization of knowledge;

citing cnxpt external to the organization of knowledge, said second cnxpt termed an internal cited cnxpt;

60. wherein a citation relationship info-item exists from an occurrence attached to said second cnxpt to one or more occurrences in or attached to items in said first identified search base wherein said occurrence attached to said second cnxpt is the citing object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a citing cnxpt external to the organization of knowledge, said second cntexxt termed an external citing cnxpt candidate for an imputed occurrence citing relationship;

61. wherein a citation relationship info-item exists from an occurrence attached to said second cnxpt to one or more occurrences in or attached to items in said first identified search base wherein said occurrence attached to said second cnxpt is the citing object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a citing cnxpt internal to the organization of knowledge, said second cnxpt termed an internal citing cnxpt candidate for an imputed occurrence citing relationship;

62. wherein a citation relationship info-item exists from an occurrence attached to said second cnxpt to one or more occurrences in or attached to items in said first identified search base wherein said occurrence attached to said second cnxpt is the cited object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a cited cnxpt external to the organization of knowledge, said second cntexxt termed an external cited cnxpt candidate for an imputed occurrence cited relationship;

63. wherein a citation relationship info-item exists from an occurrence attached to said second cnxpt to one or more occurrences in or attached to items in said first identified search base wherein said occurrence attached to said second cnxpt is the cited object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a cited cnxpt internal to the organization of knowledge, said second cnxpt termed an internal cited cnxpt candidate for an imputed occurrence cited relationship;

64. wherein a citation relationship info-item exists from a second irxt representing a second information resource to a first irxt representing a first information resource, said second irxt related by a relationship info-item to a second occurrence attached to said second cnxpt, said first irxt in the set of entries selected from the group consisting of;

said first irxt in said first identified search base, said first irxt related by an attaching relationship info-item to one or more info-items in said first identified search base, said first irxt related by an attaching relationship info-item to one or more first occurrences attached to a first cnxpt in said first identified search base, and said first irxt related by one or more relevance relationship info-items to one or more first cnxpts in said first identified search base, wherein said second irxt is the citing object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a citing cnxpt external to the organization of knowledge, said second cntexxt termed an external citing cnxpt candidate for an imputed irxt citing relationship;

65. wherein a citation relationship info-item exists from a second irxt representing a second information resource to a first irxt representing a first information resource, said second irxt related by a relationship info-item to a second occurrence attached to said second cnxpt, said first irxt in the set of entries selected from the group consisting of;

said first irxt in said first identified search base, said first irxt related by an attaching relationship info-item to one or more info-items in said first identified search base, said first irxt related by an attaching relationship info-item to one or more first occurrences attached to a first cnxpt in said first identified search base, and said first irxt related by one or more relevance relationship info-items to one or more first cnxpts in said first identified search base;

wherein said second irxt is the citing object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a citing cnxpt internal to the organization of knowledge, said second cnxpt termed an internal citing cnxpt candidate for an imputed irxt citing relationship;

66. wherein a citation relationship info-item exists from a second irxt representing a second information resource to a first irxt representing a first information resource, said second irxt related by a relationship info-item to a second occurrence attached to said second cnxpt, said first irxt in the set of entries selected from the group consisting of;

said first irxt in said first identified search base, said first irxt related by an attaching relationship info-item to one or more info-items in said first identified search base, said first irxt related by an attaching relationship info-item to one or more first occurrences attached to a first cnxpt in said first identified search base, and said first irxt related by one or more relevance relationship info-items to one or more first cnxpts in said first identified search base;

wherein said second irxt is the cited object, such that said one or more items in said first identified search base are within the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, such that said second cnxpt is external to all said genealogies given by said trees in forests of said organization of knowledge, said second cnxpt termed a cited cnxpt external to the organization of knowledge, said second cntexxt termed an external cited cnxpt candidate for an imputed irxt cited relationship;

67. wherein a citation relationship info-item exists from a second irxt representing a second information resource to a first irxt representing a first information resource, said second irxt related by a relationship info-item to a second occurrence attached to said second cnxpt, said first irxt in the set of entries selected from the group consisting of;

said first irxt in said first identified search base, said first irxt related by an attaching relationship info-item to one or more info-items in said first identified search base, said first irxt related by an attaching relationship info-item to one or more first occurrences attached to a first cnxpt in said first identified search base, said first irxt related by one or more relevance relationship info-items to one or more first cnxpts in said first identified search base, wherein said second irxt is the cited object, such that said second cnxpt is internal to the genealogies given by trees in forests of said plurality of organizations of knowledge providing a base structure, said second cnxpt termed a cited cnxpt internal to the organization of knowledge, said second cnxpt termed an internal cited cnxpt candidate for an imputed irxt cited relationship;

68. wherein said second cnxpt represents a concept similar in meaning to the meaning given by any item of said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging of similarity criteria involving occurrences wherein an occurrence is present in both a first cnxpt in said first identified search base, and also in a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the average relevance of said occurrence in said first cnxpt and said second cnxpt to be added into the result and wherein an occurrence present in but one of a first cnxpt in said first identified search base or a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the relevance of said occurrence in the cnxpt where it is present to be subtracted from said result, said second cnxpt termed a cnxpt similar according to a weighted averaging of occurrence similarities;

69. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging algorithm utilizing similarity criteria involving cnxpt citations wherein an overall score is formed by determining a score for a factor from an algorithm and multiplying it by an algorithm result weighting coefficient, said score for a factor added to said overall score, said algorithm specified in said additional specification, said algorithm of a class selected from the group consisting of;

bibliographic coupling, co-citation analysis, co-citation proximity analysis, and link based page relevance ranking algorithms, said result weighting coefficient specified in said additional specification, said score normalized for proper comparability, wherein a citation of a citing information resource represented by a citing irxt to a cited information resource represented by a cited irxt is implied to be a citing relationship info-item between any first occurrence to which said citing irxt is relevant and related and any second occurrence to which said cited irxt is relevant and related, such that said first occurrence is termed a citing occurrence, such that said second occurrence is termed a cited occurrence, such that the weight given to the implied citing to cited occurrence relationship info-item is based upon the product of the relevance between said citing irxt and said citing occurrence and the relevance between said cited irxt and said cited occurrence and the weight of the citation relationship info-item between said citing and said cited irxt, wherein a citation of a citing occurrence to a cited occurrence is implied to be a citing relationship info-item between any third cnxpt to which said citing occurrence is attached and any fourth cnxpt to which said cited occurrence is attached, such that said third cnxpt is termed a citing cnxpt, such that said fourth cnxpt is termed a cited cnxpt, such that the weight given to the implied citing to cited cnxpt relationship info-item is based upon the product of the weight of the relationship info-item between said citing occurrence and said citing cnxpt and the weight of the relationship info-item between said cited occurrence and said cited cnxpt and the weight of the citation relationship info-item between said citing and said cited occurrence, said implied citations termed resolved citation relationships, said overall score providing a metric for the similarity of said first and said second cnxpts;

70. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging algorithm utilizing similarity criteria involving cnxpt citations wherein an overall score is formed by determining a score for a factor from an algorithm and multiplying it by an algorithm result weighting coefficient, said score for a factor added to said overall score, said algorithm specified in said additional specification, said algorithm of a class selected from the group consisting of;

bibliographic coupling, co-citation analysis, co-citation proximity analysis, and link based page relevance ranking algorithms, said result weighting coefficient specified in said additional specification, said score normalized for proper comparability, wherein a citation of a citing information resource represented by a citing irxt to a cited information resource represented by a cited irxt is implied to be a citing relationship info-item between any first occurrence to which said citing irxt is relevant and related and any second occurrence to which said cited irxt is relevant and related, such that said first occurrence is termed a citing occurrence, such that said second occurrence is termed a cited occurrence, such that the weight given to the implied citing to cited occurrence relationship info-item is based upon the product of the relevance between said citing irxt and said citing occurrence and the relevance between said cited irxt and said cited occurrence and the weight of the citation relationship info-item between said citing and said cited irxt, wherein a citation of a citing occurrence to a cited occurrence is implied to be a citing relationship info-item between any third cnxpt to which said citing occurrence is attached and any fourth cnxpt to which said cited occurrence is attached, such that said third cnxpt is termed a citing cnxpt, such that said fourth cnxpt is termed a cited cnxpt, such that the weight given to the implied citing to cited cnxpt relationship info-item is based upon the product of the weight of the relationship info-item between said citing occurrence and said citing cnxpt and the weight of the relationship info-item between said cited occurrence and said cited cnxpt and the weight of the citation relationship info-item between said citing and said cited occurrence, said implied citations termed resolved citation relationships, said first and said second cnxpts both being in said organization of knowledge, such that citation relationships where said first cnxpt or said second cnxpt cites the same cited object as an ancestor cnxpt in common to both said first cnxpt and said second cnxpt in said organization of knowledge are multiplied by a per-level inheritance effect dampening coefficient from consideration, said overall score providing a metric for the similarity of said first and said second cnxpts based upon commonality of ancestry and level in said organization of knowledge;

71. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging of similarity criteria involving traits wherein a trait is present in both a first cnxpt in said first identified search base, and also in a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the average relevance of said trait in said first cnxpt and said second cnxpt to be added into the result and wherein a trait present in but one of a first cnxpt in said first identified search base or a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the relevance of said trait in the cnxpt where it is present to be subtracted from said result;

72. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging of similarity criteria involving purlieu wherein a purlieu is present in both a first cnxpt in said first identified search base, and also in a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the average relevance of said purlieu in said first cnxpt and said second cnxpt to be added into the result and wherein a purlieu present in but one of a first cnxpt in said first identified search base or a second cnxpt representing said second cntexxt causes a weight based upon a specified coefficient times the relevance of said purlieu in the cnxpt where it is present to be subtracted from said result;

73. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging of similarity criteria involving purlieu, said first and said second cnxpts both being in said organization of knowledge such that gestation timings have been calculated for each possibly based in part on purlieu, purlieu probability distributions for timing determination coupled with a value for a degree of fuzziness specified for gestation calculation resolving gestation of said first cnxpt or said second cnxpt to be clearly inside, clearly outside, or on the fringe of the purlieu, wherein said first cnxpt or said second cnxpt are resolved to be within a purlieu a weight based upon a specified coefficient times the absolute value of the differential of the relevance of said purlieu in said first cnxpt divided by the signed number of standard deviations from the center of said purlieu of said first cnxpt'"'"'s gestation and the relevance of said purlieu in said second cnxpt divided by the number of standard deviations from the center of said purlieu in said second cnxpt'"'"'s gestation to be added into the result, said overall score providing a metric for the similarity of said first and said second cnxpts based upon gestation relative to purlieu in said organization of knowledge;

74. wherein said second cnxpt represents a concept similar in meaning to the meaning given by the first item in said first identified search base based upon relationships created by users from their own belief or a score value determined by a specified weighted averaging of similarity criteria involving a constraint time frames wherein a constraint relationship info-item is present for both a first cnxpt in said first identified search base, and also in a second cnxpt representing said second cntexxt causes a weight based upon a specified pertinence coefficient times the average relevance weightings of the constraint relationship to said first cnxpt and said second cnxpt to be added into the result, a constraint relationship info-item is present in but one of a first cnxpt in said first identified search base or a second cnxpt representing said second cntexxt causes a weight based upon a specified pertinence coefficient times the average relevance weightings of the constraint relationships to said first cnxpt and said second cnxpt to be to be subtracted from the result forming said score value;

75. wherein said second cnxpt has a stated purlieu, wherein said timeline is formed by ordering conceptual meanings by a time point associated with said purlieu, said time point selected from the group consisting of;

starting, mid-point, end-point, median of distribution, mean of distribution, and any other specified purlieu summarizer, wherein said purlieu is a member of said first identified search base if specified or from the set of all purlieu in said organization of knowledge if no first identified search base is specified;

76. wherein said second cnxpt has a relationship info-item with a stated time point constraint, wherein said timeline is formed by ordering conceptual meanings by said time point constraint, said time point selected from the group consisting of;

initial time, mid-point, point at which cnxpt to which said time point constraint pertains is superseded, median of distribution, mean of distribution, and any other specified time point constraint summarizer, wherein said constraint is a member of said first identified search base if specified or from the set of all constraints in said organization of knowledge if no first identified search base is specified;

77. wherein said second cnxpt has a stated purlieu, wherein said timeline is formed by ordering conceptual meanings by a time point associated with said purlieu, said time point selected from the group consisting of;

starting, mid-point, end-point, median of distribution, mean of distribution, and any other specified purlieu summarizer, wherein said purlieu is a member of said first identified search base if specified or from the set of all purlieu in said organization of knowledge if no first identified search base is specified;

78. wherein said second cnxpt is of a type having a property stating a characterization of value selected from the group of;

a point value, and a calculable value;

applicable to the search result sought, said property calculated to form a value for said second cnxpt according to simple addition, a consensus-based upon all votes regarding said property, an averaging of all votes regarding said property, an analytic, or other algorithm as specified in additional specification, said second cnxpt a member of said first identified search base;

79. wherein said second cnxpt is related to an instance of an entity as expressed in one or more row of a data set having an attribute stating a point value applicable to the search result sought as expressed in a resulting property of said second cnxpt, said property calculated from said attribute to form a value for said second cnxpt according to simple addition of said attribute for all rows, an averaging of said attribute for all rows, an analytic, or other algorithm as specified in additional specification, said second cnxpt a member of said first identified search base;

80. wherein said second cnxpt is of a type having relationships with info-items having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property first resolved to a consensus value based upon all votes regarding said property, said property of each such info-item related to said second cnxpt summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, said second cnxpt a member of said first identified search base;

81. wherein said second cnxpt is of a type having relationships with info-items having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property first resolved to a consensus value based upon all votes regarding said property, said property of each such info-item related to said second cnxpt next summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, wherein said summation must then be distributed across all such third cnxpts of said type having relationships with info-items having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, said third cnxpt not necessarily a member of said first identified search base, said second cnxpt also one said third cnxpt, said second cnxpt and said third cnxpt in said domain of knowledge, said second cnxpt a member of said first identified search base;

82. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property of each fourth cnxpt first resolved to a consensus value based upon all votes regarding said property, said property of each such fourth cnxpt related to said second cnxpt next summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, wherein said summation must then be distributed across all such third cnxpts of said type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, said third cnxpt not necessarily a member of said first identified search base, said second cnxpt also one said third cnxpt, said second cnxpt and said third cnxpt in said domain of knowledge, no fourth cnxpt in same tree in said organization of knowledge as any third cnxpt, said second cnxpt a member of said first identified search base;

83. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property of each fourth cnxpt first resolved to a consensus value based upon all votes regarding said property, said property of each such fourth cnxpt related to said second cnxpt next summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, wherein said summation must then be distributed across all such third cnxpts of said type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, said third cnxpt not necessarily a member of said first identified search base, said second cnxpt also one said third cnxpt, said second cnxpt and said third cnxpt in said domain of knowledge, all fourth cnxpts in same domain of wisdom, no fourth cnxpt in same domain of wisdom as any third cnxpt, wherein the total value of all cnxpts at any level in the domain of knowledge containing a fourth cnxpt constrained to a value specified for said level in said additional specification so that the value imputed to said second cnxpt is first normalized to conform to such constraint, said second cnxpt a member of said first identified search base;

84. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property of each fourth cnxpt first resolved to a consensus value based upon all votes regarding said property, said property of each such fourth cnxpt related to said second cnxpt next summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, wherein said summation must then be distributed across all such third cnxpts of said type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, said third cnxpt not necessarily a member of said first identified search base, said second cnxpt also one said third cnxpt, said second cnxpt and said third cnxpt in said domain of knowledge, all fourth cnxpts in same domain of wisdom, no fourth cnxpt in same domain of wisdom as any third cnxpt, said domains of knowledge organized by common depth framing based upon a factor such as time wherein the total value of all cnxpts at any depth frame in the domain of knowledge containing a fourth cnxpt is constrained to a value specified for said depth frame in said additional specification so that the value imputed to any said second cnxpt is first normalized to conform to such constraint, said second cnxpt a member of said first identified search base;

85. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, and when assembled, to the search result sought, said property of each fourth cnxpt first resolved to a consensus value based upon all votes regarding said property, said property of each such fourth cnxpt related to said second cnxpt next summed to form a value for said second cnxpt according to primary tcept value prediction process means, simple addition, an analytic, or other summing algorithm as specified in additional specification, wherein said summation must then be distributed across all such third cnxpts of said type having relationships with fourth cnxpts having a property stating a characterization of value selected from the group of;

a point value, and value distribution;

applicable to said second cnxpt, said third cnxpt not necessarily a member of said first identified search base, said second cnxpt also one said third cnxpt, said second cnxpt and said third cnxpt in said domain of knowledge, all fourth cnxpts in same domain of wisdom, no fourth cnxpt in same domain of wisdom as any third cnxpt, said domains of knowledge organized by common depth framing based upon a factor such as time wherein the total value of all cnxpts at any depth frame in the domain of knowledge containing a fourth cnxpt is constrained to a value specified for said depth frame in said additional specification so that the value imputed to any said second cnxpt is first normalized to conform to such constraint, wherein the total value of all cnxpts at any depth frame in the domain of knowledge containing a third cnxpt is constrained to a value specified for said depth frame in said additional specification so that the value imputed to any said second cnxpt is further constrained to conform to such constraint for the total at said depth frame of said domain of knowledge containing a third cnxpt, said second cnxpt a member of said first identified search base;

86. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of types specified in additional specifications;

87. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a fxxt specified in additional specifications;

88. wherein said second cnxpt is matched to a first info-item found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first info-item to said second cnxpt, said relationship info-item of a type specified in additional specifications;

89. wherein said second cnxpt is matched to a first info-item found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first info-item to said second cnxpt, said relationship info-item of a fxxt specified in additional specifications;

90. wherein said second cnxpt is matched to a first info-item found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said second cnxpt to said first info-item, said relationship info-item of a type specified in additional specifications;

91. wherein said second cnxpt is matched to a first info-item found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said second cnxpt to said first info-item, said relationship info-item of a fxxt specified in additional specifications;

92. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a temporal ordering, said relationship info-item of a type specified in additional specifications;

93. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a temporal ordering, said relationship info-item of a fxxt specified in additional specifications;

94. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the existence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could logically exist, said relationship info-item of a type specified in additional specifications;

95. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the existence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could logically exist, said relationship info-item of a fxxt specified in additional specifications;

96. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering, causality, or dependence of the occurrence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could causally occur, an occurrence probability distribution stating the likelihood of said concept represented by said first cnxpt actually occurring, a dependency type stating whether said second cnxpt must end or merely start before said first cnxpt may start or merely end, and a timeframe of occurrence probability distribution stating the likelihood of said concept represented by said first cnxpt actually occurring within a timeframe, said relationship info-item of a type specified in additional specifications, said dependence having a type of causality specified in additional specifications, said occurrence probability distribution specified in additional specifications, said timeframe of occurrence probability distribution specified in additional specifications;

97. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering, causality, or dependence of the occurrence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could causally occur, an occurrence probability distribution stating the likelihood of said concept represented by said first cnxpt actually occurring, a dependency type stating whether said second cnxpt must end or merely start before said first cnxpt may start or merely end, and a timeframe of occurrence probability distribution stating the likelihood of said concept represented by said first cnxpt actually occurring within a timeframe, said relationship info-item of a fxxt specified in additional specifications, said dependence having a type of causality specified in additional specifications, said occurrence probability distribution specified in additional specifications, said timeframe of occurrence probability distribution specified in additional specifications;

98. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the existence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could be implemented, said relationship info-item of a type specified in additional specifications;

99. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the existence of the concept represented by said second cnxpt before the concept represented by said first cnxpt could be implemented, said relationship info-item of a fxxt specified in additional specifications;

100. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the proving of the concept represented by said second cnxpt before the concept represented by said first cnxpt could be proven, said relationship info-item of a type specified in additional specifications;

101. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating a required ordering or dependence of the proving of the concept represented by said second cnxpt before the concept represented by said first cnxpt could be proven, said relationship info-item of a fxxt specified in additional specifications;

102. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating prior art, said relationship info-item of a type specified in additional specifications;

103. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated generation, said relationship info-item from said first cnxpt to said second cnxpt, said relationship info-item of a type indicating prior art, said relationship info-item of a fxxt specified in additional specifications;

104. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by application suitability of function against need based upon one or more function traits of said second cnxpt matching against one or more requirements traits of said first cnxpt, according to generate result set membership commonality relationships, imputed association generation by heuristic, and satisfies requirements generate trxrt to trxrt requirement match relationships process means;

105. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by trait of a type specified in said additional specification or by any trait if no type is so specified, according to generate cnxpt categorizations and relationships by clustering, execute document clustering analytic, execute document cross-citation analytic, generate result set membership commonality relationships, imputed association generation by heuristic, and generate trxrt to trxrt-cncpttrrt commonality relationships process means;

106. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by implementation against a constraint in common, according to generate cnxpt categorizations and relationships by clustering, execute document clustering analytic, execute document cross-citation analytic, generate result set membership commonality relationships, imputed association generation by heuristic, matching by conformance to science, and generate trxrt to trxrt conformance match relationships process means;

107. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by purlieu in common, according to generate cnxpt categorizations and relationships by clustering, execute document clustering analytic, execute document cross-citation analytic, generate result set membership commonality relationships, imputed association generation by heuristic, and generate trxrt to trxrt match relationships process means;

108. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by interest, according to interest matching, interest path collection, system function usage data capture, collection of user data, create a ttx by registering interest, register user'"'"'s interest in ttx, natural audience segmentation provided by matching, utilize collective consensus through vote tallying, interest summarization, impute associations from interest shown and navigation, intensity of interest metric analytic, generate cnxpt categorizations and relationships by clustering, execute document clustering analytic, imputed association generation by heuristic, and generate trxrt to trxrt cncpttrrt commonality relationships process means;

109. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by family relationship info-item of a type specified in said additional specification, according to fxxt basic descendant spanning tree extraction process means, and calculate bottom up importance metrics for cnxpt categories process means;

110. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis by suitability or commonality of a type specified in said additional specification, according to fxxt basic descendant spanning tree extraction process means, and calculate bottom up importance metrics for cnxpt categories process means;

111. wherein said second cnxpt is matched to a first cnxpt found in the set of said first identified search base, said matching based upon relationships created by users from their own belief in combination with automated analysis done semantically, according to generate cnxpt categorizations and relationships by clustering, execute document clustering analytic, execute document cross-citation analytic, generate result set membership commonality relationships, imputed association generation by heuristic, execute trait matching by semantic distance calculation, fxxt basic descendant spanning tree extraction process means, and calculate bottom up importance metrics for cnxpt categories process means;

112. wherein said second cnxpt is dependent on a first cnxpt found in the set of said first identified search base, said dependency type of a type specified in said additional specification or by any trait if no type is so specified;

113. wherein said second cnxpt is a precedent depended upon by a first cnxpt found in the set of said first identified search base, said dependency type of a type specified in said additional specification or by any trait if no type is so specified;

114. wherein said second cnxpt is dependent on a first cnxpt found in the set of said first identified search base by a model equation dependency, said model equation specified in said additional specification or by any model equation if no model equation is so specified;

115. wherein said second cnxpt is a precedent depended upon on a first cnxpt found in the set of said first identified search base by a model equation dependency, said model equation specified in said additional specification or by any model equation if no model equation is so specified.

248. The method of claim 1 to also provide for recommenders for result steering, result relevance efficiency, and review tracking for query results, further including:

a. generating a map from a map definition given a domain of wisdom to form a positioned organization of knowledge, the map, by the generation, encompassing recommendations regarding the importance to the user of cnxpts organization of knowledge by positioning the principal children centrally in the context defined by the cntexxt represented by the parent cnxpt of the children, by sizing cnxpts by their importance, and by providing other indicators to speed the user'"'"'s review of the material shown in the map;

b. generating as a result of a query a list where the items in the list are ordered based upon a prediction of how much, on a relative basis, a user would appreciate having been given the item to review prior to being given the items later in the list;

c. presenting the list to the user as a tracking device for the review and action to be taken based upon the list, including a tracking device of the nature of a portfolio for recording the results of the culling of the list and the result of the actions;

and

d. accepting culling, rearrangement, commands based upon a list item, and other uses of the list;

whereby reliable ordering of the entries on a query result list, reliable strengths of relationships between cnxpts, reliable importance sizing of cnxpts, reliable positioning of cnxpts, appropriate decorations of map objects improve the efficiency of use for a user; and

whereby the lack of knowledge while a user is searching for relevant conceptual content is mitigated by the ability of the tool to get the information quickly.

249. The method of claim 1 to also provide for recommenders for result steering, result relevance efficiency, and review tracking for portfolio results, further including:

a. generating a map from a map definition given a domain of wisdom to form a positioned organization of knowledge, the map, by the generation, encompassing recommendations regarding the importance to the user of cnxpts organization of knowledge by positioning the principal children centrally in the context defined by the cntexxt represented by the parent cnxpt of the children, by sizing cnxpts by their importance, and by providing other indicators to speed the user'"'"'s review of the material shown in the map;

b. generating as a result of a query a list with one or more columns where the items in the list are ordered based upon a prediction of how much, on a relative basis, a user would appreciate having been given the item to review prior to being given the items later in the list for review;

c. including on the portfolio for an item information beyond an identification of the item and its order so that the user is immediately provided with pertinent information to allow greater efficiency in determining a next action to take when the item is reviewed;

d. presenting the list to the user as a tracking device for the review and action to be taken based upon the list in the nature of a portfolio for recording the results of the culling of the list and the result of the actions;

and

e. accepting culling, rearrangement, commands based upon a list item, and other uses of the list;

whereby reliable ordering of the entries on a query result list or portfolio, reliable strengths of relationships between cnxpts, reliable importance sizing of cnxpts, reliable positioning of cnxpts, appropriate decorations of map objects improve the efficiency of use for a user. whereby the lack of knowledge while a user is searching for relevant conceptual content is mitigated by the ability of the tool to get the information quickly;

whereby the information overload while the user is querying for, finding, and sifting to obtain relevant conceptual content and external information such as web searching and results from modeling is mitigated by the ability of the tool to order and reorder the information, track culling, present sufficiently complete succinctly, track actions taken, to get the information quickly, to rebuild the information as needed, and to save the information between sessions;

whereby the gaps in understanding while a user is evaluating modelling results for various scenarios can be mitigated by the tracking capability of a portfolio tool; and

whereby the calculation and evaluation requirements while a user is planning, brainstorming, or seeking worthwhile approaches or value based upon conceptual content can be eased by having a tracking and reporting tool such as a portfolio.

250. The method of claim 1 to also provide to a user a recommendation of the most important item to view next in a portfolio by highlighting importance by visual decoration, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least one concept relating to an entry in a portfolio, the concept represented by a cnxpt, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the portfolio, to create a map instance, the map instance associated with a portfolio view of type;

the map definition stating the manner of decoration of most important cnxpts in the portfolio;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, each context represented by a cntexxt also represented by a cnxpt and positioned;

d. generating, according to said map definition, a portfolio instance, the generation causing determination of the most important portfolio lines, the most important line being decorated in the manner prescribed in the map definition;

and

e. accepting navigation by the user of the portfolio, the user being presented with a set of lines on the portfolio, the most important of the lines decorated in a manner different from less important liness in the portfolio;

whereby the map provides a user with a recommendation by attracting the view of the user to lines displayed with a special decoration different from other lesser importance lines.

251. The method of claim 1 to also provide to a user a recommendation stating the most important concept in a context to view next in a conceptual hierarchy by highlighting importance by increased size, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, each context represented by a cntexxt also represented by a cnxpt and positioned;

and

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the most important of the cnxpts in the context consuming more space of the context and larger than less important cnxpts in the context, the navigation in a mode selected from the group of;

data set, and visualization;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more important concepts larger than others.

252. The method of claim 1 to also provide to a user a recommendation stating the most important concept in a context to view next in a conceptual hierarchy by highlighting importance by visual decoration, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge, the map definition stating the manner of decoration of cnxpts by importance in a context;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, each context represented by a cntexxt also represented by a cnxpt and positioned, the most important cnxpt in a context being decorated in the manner prescribed in the map definition;

and

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the most important of the cnxpts in the context consuming more space of the context and decorated in a manner different from less important cnxpts in the context, the navigation in a visualization;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more important concepts with a special decoration different from other lesser cnxpts.

253. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge, the map definition stating the mannerism to ascribe to cnxpts of greatest importance in a context;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, each context represented by a cntexxt also represented by a cnxpt and positioned, the most important cnxpt in a context given the mannerisms prescribed in the map definition;

and

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the most important of the cnxpts in the context consuming more space of the context and given attracting mannerisms different from less important cnxpts in the context, the navigation in a visualization;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more important concepts with a special attracting mannerism different than other lesser cnxpts.

254. The method of claim 52 to also provide generating cnxpt positions by use of a roll-up function, wherein generating a map further comprises rolling-up affinities of cnxpts, dxos, and other txo info-items to form tensors for enforcing object spacing and sizing for a map, wherein:

a. generating, into said enhanced descendant forest, one or more affinitive tensors and one or more affinitive tensor weights by performing roll-up processing on said enhanced descendant forest according to calculate roll-up association weights to form positioning tensors means for generation of affinitive tensors for enforcing object spacing and sizing for said map;

b. generating sibling, cousin, and uncle roll-up associations, between-sibling-ring attractor, and to-uncle attractor tensors with weights for enforcing distance relationships between objects during positioning on said map according to summary tensor generation means;

c. generating between-category repulsor tensors with weights for enforcing distance between objects during positioning on said map according to summary tensor generation means;

d. generating map specific positions for cnxpts for said map according to process trees for visualization generation, position determination and final sizing means for positioning;

e. generating a visualization for display of said map;

f. generating, for each info-item selected from the group of;

cnxpts, dxos, and other txos;

wherein said info-item had previously existed in a just prior generated instance of said map, a prior position tensor between said info-item and a fictitious object at the prior position of said info-item in said just prior generated instance of said map, setting the weight of said prior position tensor to a pre-specified tensor weight as an admixture coefficient;

and

g. generating, for each info-item selected from the group of;

cnxpts, dxos, and other txos;

wherein said info-item had a parent in a just prior generated instance of said map, a prior position in parent tensor between said info-item and a fictitious object at the prior position of said info-item in relation to its parent in said just prior generated instance of said map, setting the weight of said prior position in parent tensor to a pre-specified tensor weight as an admixture coefficient;

whereby classifications derived from a relevant portion of said commonplace data serve as the basis for positioning of cnxpts onto a visualization according to the map skeletal structure provided by the enhanced descendent tree forest, the prior positionings by the user for the same map, and for the maps from which the current map is derived;

whereby the ability is provided to place objects for a multi-dimensional map in a position related to the closeness of said object to others logically according to a map definition and a structuring derived therefrom, and based to some degree on the positioning by the user of the objects in prior work arranging those objects in a visualization; and

whereby the various generated tensors serve as a basis for computing an understandable and associative position of cnxpts into an organization of knowledge from the structure provided by said enhanced descendent tree forest.

255. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought, further including:

a. accepting a definition of a knowledge model comprising a set of zero or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge, the map definition stating the avatar, and its mannerisms, to assign to cnxpts of greatest importance in a context;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, each context represented by a cntexxt also represented by a cnxpt and positioned, the most important cnxpt in a context being visualized by the avatar prescribed in the map definition;

and

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the most important of the cnxpts in the context consuming more space of the context and larger than less important cnxpts in the context, and given an attracting avatar different from less important cnxpts in the context, the navigation in a visualization;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more important concepts with a special attracting avatar different from other lesser cnxpts.

256. The method of claim 1 to also provide determining of the differential between a set of fxxts with respect to a map, further including:

a. accepting a set of fxxts for comparison;

b. accepting the identity of a first fxxt from the set to be taken as a baseline for the comparison;

c. accepting a specification for a comparison metric to comprise a cost function for determining an error cost value inversely indicative of quality of a compared fxxt utilized in a compared map instance of said map against the baseline fxxt in a baseline map instance of said map;

d. accepting an alignment of the baseline map instance and each compared map instance for consistent calculation of the comparison metric, comprising a choice of rotation of the map around the vector;

e. accepting an admixture coefficient for the compared fxxts of the set as a weighting coefficient indicating a proportionality of impact of a compared fxxt in said map;

f. generating a first instance of said map utilizing the baseline said first fxxt with the specified admixture coefficient as an exemplar instance;

g. determining, for each second fxxt not yet formed of the set of fxxts to be compared, a second map instance of said map to compare against the baseline fxxt in said baseline map instance of said map;

and

h. producing a result list of fxxts in the set in order by smallest absolute cost difference from baseline based upon lowest costs determined from comparison of second fxxts to the baseline;

whereby a set of fxxts, often computed by machine learning, may be compared for effectiveness.

257. The method of claim 1 to also provide determining of the differential between a set of fxxts with respect to a map, further including:

a. accepting a set of fxxts for comparison, the set termed a comparison set;

b. accepting the identity of a first fxxt from the comparison set to be taken as a baseline for the comparison;

c. accepting a choice of cnxpts as a basis for alignment of the baseline map instance and each compared map instance for consistent calculation of the comparison metric, comprising a first cnxpt, a second cnxpt, and the vector between said first cnxpt and said second cnxpt;

where the vector is of a vector space described in terms of a particular ordered basis;

where the map is defined to be drawn in dim dimensions;

where the first dim numbers in the ordered list of numbers describing the vector having the initial point at the origin and the terminal point at the center of a cnxpt of the map define the placement position for the cnxpt in the map, further including;

i. setting as a primary default cnxpt a most important root of the baseline map instance having at least one descendant cnxpt that exists as a cnxpt in all of the compared map instances, where said primary default cnxpt exists as a cnxpt in all of the compared map instances;

ii. setting as a secondary default cnxpt a descendant of said primary default cnxpt in the baseline map, where said secondary default cnxpt exists as a most important descendant of said primary default cnxpt among all descendants of said primary default cnxpt that exist as a cnxpt in all of the compared map instances;

iii. accepting a user choice, with said primary default cnxpt as default, of a cnxpt to be said first cnxpt as a basis for alignment;

and

iv. accepting a user choice, with said secondary default cnxpt as default, of a cnxpt to be said second cnxpt as a basis for alignment;

d. accepting an alignment of the baseline map instance and each compared map instance for consistent calculation of the comparison metric, comprising a choice of rotation of the map around the vector between said first cnxpt and said second cnxpt, and setting the length of the radius of the circumscribed bounds of the compared map instance by transform of cnxpt positions to the length of the radius of the circumscribed bounds of the baseline map instance;

the specification for the alignment selected from the group of;

i. placing, if said first cnxpt is a root of the compared map instance, the center of said first cnxpt at the zero vector in the compared map instance, and rotating the map so that all of the first dim minus one numbers in the ordered list of numbers of the vector having the initial point at the center of said first cnxpt and the terminal point at the center of said second cnxpt are equal to their value most close to zero;

ii. placing, if said first cnxpt is not a root of the compared map instance and said second cnxpt is a descendant of said first cnxpt, said first cnxpt of the compared map instance at the zero vector origin; and

rotating the map so that all of the first dim minus one numbers in the ordered list of numbers of the vector having the initial point at the origin and the terminal point at the center of said second cnxpt are equal to their value most close to zero;

iii. placing, if said first cnxpt is not a root of the compared map instance and said second cnxpt is not in the same tree as said first cnxpt, said first cnxpt of the compared map instance at the zero vector origin; and

rotating the map so that all of the first dim minus one numbers in the ordered list of numbers of the vector having the initial point at the origin and the terminal point at the center of said second cnxpt are equal to their value most close to zero;

iv. placing, if said first cnxpt is not a root of the compared map instance and said second cnxpt is an ascendant of said first cnxpt, said second cnxpt of the compared map instance at the zero vector origin; and

rotating the map so that all of the first dim minus one numbers in the ordered list of numbers of the vector having the initial point at the origin and the terminal point at the center of said first cnxpt are equal to their value most close to zero;

v. accepting a null specification for the alignment wherein the center of a compared map instance is placed coincident with the center of the baseline map instance;

and

vi. accepting a user defined specification for the alignment;

e. accepting a specification for a comparison metric for determining a total value inversely indicative of quality of a compared fxxt utilized in a compared map instance of said map against the baseline fxxt in a baseline map instance of said map, the comparison metric termed an error cost function, the comparison metric comprised of the sum of absolute values of specified arguments, the arguments selected from the group of;

i. the difference between a value of a property of a third cnxpt in the compared map instance to the value of said property of said third cnxpt in the baseline map instance, the specification of said property accepted from the user;

ii. the square of the distance from each third cnxpt in the baseline map instance to said third cnxpt in a compared map instance, given the selected alignment, the distance defined to be between the terminal points of two vectors the first constructed by defining dimensions using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by defining like dimensions using a value of like said one or more properties of said third cnxpt in the compared map instance, the initial point at the origin of the respective map instance, the specification of said one or more properties accepted from the user;

and

iii. the square of the difference between the inter-cnxpt distance of each pair of a third cnxpt and a fourth cnxpt in the baseline map instance and the inter-cnxpt distance of the matching pair of a third cnxpt and a fourth cnxpt in the compared map instance, the distance defined to be from the terminal point of a vector from the origin to the third cnxpt to the terminal point of a vector from the origin to the fourth cnxpt;

wherein the vector is of a vector space described in terms of a particular ordered basis set of properties as rows forming the ordered list of elements;

where the map is defined to be drawn in dim dimensions;

where the first dim values in the ordered basis set of properties as rows describing the vector having the initial point at the origin and the terminal point at the center of a cnxpt of the map define the placement position for the cnxpt in the map, further including;

iv. constructed by defining dimensions using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by defining like dimensions using a value of like said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

v. two vectors the first constructed by defining dimensions using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by defining like dimensions using a value of like said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

vi. a distance between the terminal points of two vectors the first constructed by defining dimensions using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by defining like dimensions using a value of said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

vii. the two-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance;

viii. a distance between the terminal points of two vectors the first constructed by adding dimensions to the two-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the two-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

ix. the three-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance;

x. a distance between the terminal points of two vectors the first constructed by adding dimensions to the three-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the three-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

xi. the dim-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance;

xii. a distance between the terminal points of two vectors the first constructed by adding dimensions to the dim-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the dim-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the specification of said one or more properties accepted from the user;

xiii. the two-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance, measured by constructing vectors between the origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt;

xiv. a distance between the terminal points of two vectors the first constructed by adding dimensions to the two-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the two-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the two-dimensional location relative to an origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt, the specification of said one or more properties accepted from the user;

xv. the three-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance, measured by constructing vectors between the origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt;

xvi. a distance between the terminal points of two vectors the first constructed by adding dimensions to the three-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the three-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the three-dimensional location relative to an origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt, the specification of said one or more properties accepted from the user;

xvii. the dim-dimensional distance from a third cnxpt in the compared map instance to said third cnxpt in the baseline map instance, measured by constructing vectors between the origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt;

and

xviii. a distance between the terminal points of two vectors the first constructed by adding dimensions to the dim-dimensional location of a third cnxpt in the baseline map instance using a value of one or more properties of said third cnxpt in the baseline map instance and the second constructed by adding like dimensions to the dim-dimensional location of said third cnxpt in the compared map instance using a value of said one or more properties of said third cnxpt in the compared map instance, the dim-dimensional location relative to an origin defined to be at the center of the lowest common ancestor of said third cnxpt in the compared map instance and said third cnxpt in the baseline map instance to the center of said third cnxpt, the specification of said one or more properties accepted from the user;

f. accepting the identity of a first fxxt from the set to be taken as a baseline for the comparison;

g. accepting an admixture coefficient for the compared fxxts of the set as a weighting coefficient indicating a proportionality of impact of a compared fxxt in said map;

h. generating a first instance of said map utilizing the baseline said first fxxt with said specified admixture coefficient as a baseline map instance as an exemplar instance;

i. determining, for each second fxxt of the set of fxxts to be compared, plus said baseline fxxt if a preference setting is set to a predetermined value, a second map instance of said map to compare against the exemplar map instance;

determining, for each second fxxt not yet formed of the set of fxxts to be compared, a second map instance of said map to compare against said baseline map instance of said map, wherein;

i. generating said second map instance of said map utilizing the comparison said second fxxt with application of said specified admixture coefficient;

ii. determining a cost-improved map definition from one or more determinations of an improved set of fxxt coefficients indicating a proportionality of impact in said map for comparison based upon finding an acceptably near minimum error cost value, the error cost value calculated by the cost function on differences in organization of knowledge from exemplar map to a version of map for comparison after forming the version of map for comparison by fxxt extractions, forest extractions, roll-ups, and positionings, the choice of fxxt coefficients indicating a proportionality of impact used to generate the version of map for comparison based upon calculations selected from the group of;

iii. comparison metric to comprise a cost function for determining an error cost value when comparing a fxxt in a compared map instance of said map for comparison against the baseline fxxt in a baseline map instance of said map by accumulating the error cost from the distances between each third cnxpt in the baseline map instance to said third cnxpt in a compared map instance, wherein the comparison metric contains arguments selected from the group of;

and

iv. computing the degree of multimodality for votes by a plurality of users for a third cnxpt by determining the degree to which the distribution for said votes is other than unimodal;

and

j. producing a result list of fxxts in the set and the absolute cost difference from the exemplar based upon lowest costs determined from comparison of second fxxts to the baseline map instance;

whereby a set of fxxts, often computed by machine learning, may be compared for accuracy in analysis.

258. The method of claim 257 to also provide determining of the differential between a set of fxxts with respect to a exemplar map instance improved by a crowd, further including:

a. generating a first instance of said map utilizing the baseline said first fxxt with the specified admixture coefficient as an exemplar map instance;

b. accepting repositioning of zero or more cnxpt positions in the exemplar map instance from the baseline map instance by one or more specified users to correct believed deficiencies in results of use of said baseline fxxt;

c. determining, for each second fxxt of the set of fxxts to be compared, plus said baseline fxxt if a preference setting is set to a predetermined value, a second map instance of said map to compare against the exemplar map instance;

and

d. producing a result list of fxxts in the set and the absolute cost difference from the exemplar based upon lowest costs determined from comparison of second fxxts to the exemplar;

whereby a set of fxxts may be compared to a refined baseline where users have made required changes.

259. The method of claim 257 to also provide determining of the differential between a set of fxxts with respect to a baseline map instance, further including:

a. applying a coefficient instance of said map utilizing the baseline said first fxxt with the specified admixture coefficient as an exemplar map instance;

b. accepting repositioning of zero or more cnxpt positions in the exemplar map instance from the baseline map instance by one or more specified users to correct believed deficiencies in results of use of said baseline fxxt;

c. determining, for each second fxxt not yet formed of the set of fxxts to be compared plus said baseline fxxt, a second map instance of said map to compare against the exemplar map instance;

and

d. producing a result list of fxxts in the set in order by smallest absolute cost difference from exemplar based upon lowest costs determined from comparison of second fxxts to the exemplar;

whereby a set of fxxts may be compared to a refined baseline where users have made required changes.

260. The method of claim 1 to also provide determining of an emergent property, further including:

a. defining a knowledge model based upon sub-typing comprising a set of zero or more fxxts;

b. generating, using a map definition referencing the set of zero or more fxxts, a derived ontology;

c. generating, using said map definition referencing the set of zero or more fxxts, a skeletal structure for a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map skeletal structure of said map instance is based upon an enhanced descendent forest manner and an enhanced ascendant forest manner combination structure manner of analysis;

d. generating, using said map definition referencing the set of zero or more fxxts, an organization of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon an enhanced descendent forest manner of map assembly, said map based upon sub-typing, wherein a first cnxpt has a plurality of second cnxpts as distinct parents, where each second cnxpt is a super-type of said first cnxpt based upon properties of said first cnxpt;

and

e. determining existence of a property in said first cnxpt not appearing in any second cnxpt in said plurality of second cnxpts;

whereby said first property is an emergent property if there is no parent having it and because the map is definitionally the total of all knowledge at the time of viewing, the emergence is definitionally correct at that time.

261. The method of claim 1 to also provide presentation of commonplace changes made according to the source and authority of a vote, further comprising:

a. repositioning of the map in use by said user and consequent re-rendering of any display of the map in use by said user to adapt to a change made to an info-item in the commonplace to conform to the result of changes made, the changes selected from the group of;

i. changes made by vote entered by any user that alter the consensus regarding beliefs encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the votes termed objective beliefs;

ii. changes made by vote entered by a third user that alter, when weighted heavily relative to the votes of other users by ascent, the accorded concurrence regarding beliefs encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the votes termed expert beliefs of said third user by grant;

iii. changes made by vote entered by a third user that alter, when weighted heavily relative to the votes of other users by agreement, the conformance regarding beliefs encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the votes termed ceded authoritative beliefs of said third user by assignment;

iv. changes made by vote entered by an appointed standard setting user that alter, when weighted heavily relative to the votes of each user not a participant of the standards setting body, the concordance regarding beliefs encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the votes termed standardized beliefs of a standards authority;

v. changes made by vote entered by an appointed authority that alter, when weighted to respect the authority over the votes of each user not an authorized participant of the harmonization effort, the concordance information encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the votes termed harmonization policy information of the participant authorities;

vi. changes made by vote entered by said user that overpower the consensus regarding beliefs encompassed by the commonplace data so substantially that it would cause the data of the map being accessed by said user to be noticeably incorrect, the overweighted votes termed subjective beliefs, the weighting assigned by said user;

and

vii. changes made by vote entered by said user that disregard the consensus regarding beliefs encompassed by the commonplace data, the votes termed user set beliefs;

whereby a user may control the status of what they see in a map according to their own voting;

whereby standards setting bodies may set standards and participate in harmonization;

whereby experts and authorities may be given greater control of topics based upon granted authority.

262. The method of claim 1 to also provide differentiated methods for searching for content during map generation, further including:

a. providing at least one invocation procedure to obtain wisdom, of a sequencing selected from the group of;

i. procedure for obtaining wisdom yielding a list of at least one cnxpt into a derived ontology, the procedure then initiating formation of a map from a map definition referencing a set of zero or more fxxts, wherein the procedure is of a type selected from the group of;

01. a search procedure for obtaining content for at least one domain of wisdom by one or more searches yielding a list of at least one cnxpt, the procedure then initiating a map formation procedure for a pre-determined map definition and passing the search results to the map formation procedure, wherein the searches are defined prior to invocation of said procedure for obtaining content, the assignment of formed map definition to search determined prior to invocation of said procedure for obtaining content;

and

02. a search procedure for obtaining content for at least two domains of wisdom by two or more searches yielding at least two lists of at least one cnxpt, the procedure then initiating a map formation procedure for each of at least two pre-determined map definitions and passing at least one of said at least two lists of at least one cnxpt as search results to each of the map formation procedures for each of at least two pre-determined map definitions for building said pre-determined map definitions, wherein the searches are defined prior to invocation of said procedure for obtaining content, the assignment of map definition to search determined prior to invocation of said procedure for obtaining content;

and

ii. auxiliary procedure for obtaining wisdom invoked by a map formation procedure, the auxiliary procedure specified in the map definition referencing a set of zero or more fxxts, the result of the auxiliary procedure added into a derived ontology, wherein the procedure is of a type selected from the group of;

01. an auxiliary procedure obtaining content for a domain of wisdom by performing a search yielding a list of at least one cnxpt and zero or more associations, the search specified in the map definition;

02. an auxiliary procedure obtaining content for zero or more domains of wisdom by performing one or more searches each yielding a list of zero or more cnxpts and zero or more associations, wherein each search is specified in the map definition;

and

03. a fxxt-resolution procedure for obtaining content for one domain of wisdom by performing a resolution for one fxxt specification stated in the map definition, the fxxt-resolution procedure yielding derived ontology containing a list of zero or more cnxpts and zero or more associations;

whereby variations of the invocation of maps allow for spawning other maps, expanded collection methods for wisdom, and ability to generate multi-forest and multi-purpose maps.

263. The method of claim 1 to also provide the ability to find a classification for a technical invention not well defined, the method further comprising:

a. defining a technology derivation map describing the historic, contemporary, and possible future technologies showing the genealogy of technologies wherein similar technological concepts are in closer proximity than dissimilar technological concepts;

b. generating the technology derivation map;

c. displaying the technology derivation map on a first portion of the display screen, the plurality of cntexxts of the technology derivation map as a network display;

d. displaying simultaneously sub-contexts of at least one context in the subset of the plurality of contexts;

e. creating a goal, stating zero or more properties of said goal, the goal representing the concept the user has in their mind or is forming, ideating, or conjuring;

f. accepting one or more user commands causing the goal to be classified into a different context identified by a cntexxt, the intent of the move being to narrow the set of contexts where said user might find the technology concept being conjured, the movement of the goal caused by a method selected from the group of;

i. executing a search query of said goal, the query defined or redefined by the user, the query causing movement of said goal to the cntexxt closest matching to the query results of the goal query;

and

ii. navigating to traverse the goal to a next cntexxt;

and

g. accepting a user command indicating that the concept being conjured and represented by the goal should be within the context moved to, the meaning of the user command a response to the status of the idea in the context, the command selected from the group of;

i. as the inventive technology is not in the located context but should be, wherein;

01. finalizing said goal by converting said goal to a cnxpt with the same properties;

02. associating said cnxpt hierarchically to the context by a hierarchical association, said cnxpt a differentiable offshoot of the context;

03. accepting a command to stake a claim for the idea the user identified, reified from the goal, and allowed to concretize;

and

04. generating, if said search goal has a result set other than of cnxpts, occurrence relationships between said cnxpt and each relevant result set item information txo or irxt found;

and

ii. as the concept is in the located context represented by a cnxpt, abandon the goal, allowing the user to set properties of the found cnxpt according to those on the goal if not conflicting with existing properties in the found cnxpt;

whereby the user is given an ability to locate a context best suited to holding an idea;

whereby rather than a decision tree classification the user is given the option of extending decision tree branches by locating an appropriate parent and then creating a new leaf;

whereby the new cnxpt can fill white space of the parent;

whereby the user is given the option to set properties of the new idea that differentiate it from the context and siblings within the context although the user may be reticent to expose the idea; and

whereby the differentiation may be by timeframe where the new cnxpt should be the parent rather than the child.

264. The method of claim 1 to also provide forming a structure for results from a query, further comprising:

a. organizing into a structure the set of ttxs found by the query, wherein;

i. obtaining results from the operation of the query, the set of ttxs resulting from executing a ttx sub-setting operation selected from the group of;

01. a find query resulting in a list of cnxpts;

02. a query result comprising a set of ttxs;

03. a query result comprising a set of cnxpts and zero or more related ttxs and zero or more associations;

04. a reduction result comprising a set of cnxpts and structural information;

05. a derived ontology defined over a set of cnxpts;

06. a fxxt extraction comprising a set of cnxpts and associations;

07. a flow extraction comprising a set of cnxpts and associations;

08. output of an execution of an analytic comprising a set of ttxs;

09. output of an execution of an analytic comprising a set of cnxpts and zero or more related ttxs and zero or more associations;

10. result of selection from a data set comprising a set of ttxs;

11. result of selection from a data set comprising a set of cnxpts and zero or more related ttxs and zero or more associations;

12. result of selection from a portfolio comprising a set of ttxs;

13. result of selection from a portfolio comprising a set of cnxpts and zero or more related ttxs and zero or more associations;

14. selection of a uniquely identified categorization comprising a set of cnxpts and zero or more related ttxs and zero or more associations;

15. selection of a uniquely identified clump extract set comprising a set of cnxpts with positions and zero or more related ttxs with positions and zero or more hierarchical tensors;

16. output of a filter application comprising a set of ttxs;

17. output of a filter application comprising a set of cnxpts and zero or more related ttxs and zero or more tensors;

18. a user ad hoc selection set of ttxs;

and

19. a user ad hoc selection set of cnxpts;

ii. creating a structure based upon the nature of the result of the ttx sub-setting operation, the structuring of the result of a type selected from the group of;

01. forming, for the result of the ttx sub-setting operation being a list of ttxs not in a result set, wherein;

creating a ttx result set with a ttx result set item for each ttx in the query result list;

performing tallying and ordering of the ttx result set specific to the type of ttx result set;

and

setting, as the model for the result set, the properties of the ttx result set items as a simple list otherwise devoid of structure, including zero or more identified summaries of properties, to generate a query result specific surrogate model snapshot updatable upon change in list;

forming, for the result of a query returning an area of consideration, creation of the area;

forming, for the result of a selection of a portfolio, creation of a partial portfolio;

forming, for the result of a filter application a structuring like that of the domain of the search;

02. forming, for a list of cnxpts result of the ttx sub-setting operation, the operation performed in a basis map, all of the listed cnxpts appearing within the basis map, wherein;

creating a result set with a result set item for each cnxpt in the query result list;

performing tallying and ordering of the cnxpt result set;

creating an area of consideration from the set of cnxpts according to form area of consideration from results means;

generating a named derived ontology from the cnxpts in the result set and from all tensors directly connecting any two cnxpts in the result set, converting the tensors to be weighted associations in the named derived ontology;

generating a temporary map from the skeletal structure formed for the basis map a temporary compressed skeletal structure for the area of consideration by collapsing the hierarchy of the skeletal structure of the basis map where the set of cnxpts of the area of consideration do not include cnxpts in the skeletal structure of the map, wherein the positions of the set of cnxpts of the area of consideration are not recomputed;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model stated by the cnxpt definitions of the temporary organization of knowledge in the temporary map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

03. forming, for the result of the ttx sub-setting operation being a list of cnxpts in the nature of a reduction, the results additionally comprising the calculations, associations, and tensors needed to determine how the cnxpts will participate in a skeletal structure and where the cnxpts will be positioned, although the structure not having been completed, the cnxpts not necessarily in the basis map, wherein;

creating a named derived ontology from the set of cnxpts in the query result list, and provided calculations, associations, and tensors;

creating a new temporary map having the named derived ontology as a basis;

generating a skeletal structure for the temporary map according to fxxt basic descendant spanning tree extraction means;

extracting an enhanced forest from the skeletal structure formed for the temporary map;

performing roll-ups for the temporary map;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model of the temporary organization of knowledge in the temporary map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

04. forming, for a derived ontology result of the ttx sub-setting operation, wherein;

creating a new temporary map having the named derived ontology as a basis;

generating a skeletal structure for the temporary map according to fxxt basic descendant spanning tree extraction means;

extracting an enhanced forest from the skeletal structure formed for the temporary map;

performing roll-ups for the temporary map;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model of the temporary organization of knowledge in the temporary map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

05. forming, for the result of the ttx sub-setting operation being a list of cnxpts not in a result set, the list in the setting of a basis map, none of the cnxpts of the list appearing in the basis map, wherein;

creating a list with a list item for each cnxpt in the query result list;

and

executing the model embodied in cnxpts of the list as if all cnxpts were roots of a map otherwise devoid of structure, to generate a query result specific model snapshot updatable upon change in list;

06. forming, for the result of the ttx sub-setting operation being a list of cnxpts not in a result set in the setting of a basis map, one or more of the cnxpts of the list appearing in the basis map, wherein;

generating a named derived ontology from the cnxpts in the query result list and from all tensors directly connecting any two cnxpts in the query result list, converting the tensors to be weighted associations in the named derived ontology;

adding to the named derived ontology a summarized tensor between each two cnxpts of the query result list having between them a hierarchical structure in the basis map by collapsing the set of hierarchical tensors of said hierarchical structure into said summarized tensor, wherein as no tensors connect cnxpts of the query result list not in the basis map those cnxpts become roots of the skeletal structure of the temporary map;

creating a new temporary map having the named derived ontology as a basis;

generating a skeletal structure for the temporary map according to fxxt basic descendant spanning tree extraction means;

extracting an enhanced forest from the skeletal structure formed for the temporary map;

performing roll-ups for the temporary map;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model embodied in cnxpts of the query result list as if all cnxpts not in the basis map were roots of the skeletal structure of the basis map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

07. forming, for list of cnxpts result of the ttx sub-setting operation, the operation performed in a basis map, all of the listed cnxpts appearing within the basis map, wherein;

creating a result set with a result set item for each cnxpt in the query result list;

performing tallying and ordering of the cnxpt result set;

creating an area of consideration from the set of cnxpts according to form area of consideration from results means;

generating a named derived ontology from the cnxpts in the result set and from all tensors directly connecting any two cnxpts in the result set, converting the tensors to be weighted associations in the named derived ontology;

generating a new temporary map from the skeletal structure formed for the basis map a temporary compressed skeletal structure for the area of consideration by collapsing the hierarchy of the skeletal structure of the basis map where the set of cnxpts of the area of consideration do not include cnxpts in the skeletal structure of the map, wherein the positions of the set of cnxpts of the area of consideration are not recomputed;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model of the temporary organization of knowledge in the temporary map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

and

08. forming, for the result of the ttx sub-setting operation being a list of cnxpts in a result set in the setting of a basis map, one or more of the cnxpts of the list appearing in the basis map, wherein;

creating a result set with a result set item for each cnxpt in the query result list;

performing tallying and ordering of the cnxpt result set;

generating a named derived ontology from the cnxpts in the result set and from all tensors of the basis map directly connecting any two cnxpts in the result set, converting the tensors to be weighted associations in the named derived ontology;

adding to the named derived ontology a summarized tensor between each two cnxpts of the result set having between them a hierarchical structure in the basis map by collapsing the set of hierarchical tensors of said hierarchical structure into said summarized tensor, wherein as no tensors connect cnxpts of the result set not in the basis map those cnxpts become roots of the skeletal structure of the temporary map;

creating a new temporary map having the named derived ontology as a basis;

generating a skeletal structure for the temporary map according to fxxt basic descendant spanning tree extraction means;

extracting an enhanced forest from the skeletal structure formed for the temporary map;

performing roll-ups for the temporary map;

performing positioning for the temporary map to generate a temporary organization of knowledge;

and

executing the model embodied in cnxpts of the result set as if all cnxpts not in the basis map were roots of the skeletal structure of the basis map, to generate a query result specific model snapshot updatable upon change in temporary organization of knowledge;

whereby a query resulting in a list of ttxs is structured;

whereby a query resulting in a list of ttxs is summarized;

whereby a query resulting in a list of cnxpts provides the model the cnxpts carry;

whereby a model is executed or a surrogate model is generated to provide a snapshot changeable as changes are made to the list of ttxs or to the structure.

265. The method of claim 264, to extract a predetermined set of characteristics of cnxpts into a data package, further comprising:

a. retrieving a query result from a query producing a set of cnxpts the query result including a specific model snapshot updatable upon change in a temporary organization of knowledge;

b. applying zero or more filters determining inclusion based upon characteristics of cnxpts to eliminate one or more cnxpts of said query result;

c. extracting a plurality of value tuples of predetermined characteristics of said cnxpts in said set of cnxpts;

and

d. generating said data package of the set of said plurality of value tuples.

266. The method of claim 264 to also provide visualization of results of query for ttxs, further comprising:

a. generating a visualization of the set of cnxpts resulting from executing a ttx sub-setting operation, by the organization of the resulting set of ttxs selected from the group of;

i. generating an ordered list with zero or more summarization tallies the result set of ttxs resulting from executing a ttx sub-setting operation;

ii. generating an unordered list with zero or more summarization tallies the list of ttxs resulting from executing a ttx sub-setting operation;

iii. generating as a secondary map visualization the temporary map resulting from executing a ttx sub-setting operation;

iv. generating as a overlay visualization of the basis map the area of consideration of cnxpts resulting from executing a ttx sub-setting operation;

v. generating an ordered result set list with zero or more summarization tallies the result set of cnxpts resulting from executing a ttx sub-setting operation;

and

vi. generating an unordered list with zero or more summarization tallies the list of cnxpts resulting from executing a ttx sub-setting operation;

b. presenting the visualization to the user;

and

c. accepting a request to alter the visualization to affect the underlying ttx information.

267. The method of claim 1 to also provide forming a model from a map, comprising:

a. forming a model from an ontology, wherein;

i. forming a plurality of set extraction specifications partitioning the contents of an ontology into one or more identified extraction sets, the nodes of the ontology being object classes, the relationships of the ontology being object classes to support node classes, the instances of the nodes of the ontology having storage to hold zero or more values and formulas to determine said zero or more values;

ii. accepting a structuring of an ontology as a basis for modeling by specifying a weighting coefficient indicating a proportionality of impact for an extraction set wherein said extraction set is included into a named derived ontology;

iii. extracting the extraction sets of ontology components into a named derived ontology, wherein the strength of every relationship instance added to the named derived ontology during extraction becomes the weighting coefficient indicating a proportionality of impact multiplied by the relationship strength in the original ontology, wherein the node importance of every node instance added to the named derived ontology during extraction becomes the weighting coefficient indicating a proportionality of impact multiplied by the node importance in the original ontology;

iv. developing a skeletal structure from the named derived ontology according to fxxt basic descendant spanning tree extraction means, respecting the weighting coefficient indicating a proportionality of impact of said extraction sets as incorporated in the named derived ontology relationships and nodes;

and

v. calculating a model result from the structured named derived ontology by computing the zero or more values of each node instance, respecting the skeletal structure, the model result comprising the zero or more values of each node instance;

whereby a commonplace becomes a resource for controlling a model.

268. The method of claim 1 to also provide improving a model by exemplar, comprising:

a. improving a model according to user perceptions, wherein;

i. accepting for use as comparators zero or more normative results anticipated of the modeling, each normative result specific to an identifiable model result;

ii. computing an error metric cost function for the differential between the modeling results and the normative results;

iii. adjusting the weighting coefficients indicating a proportionality of impact assigning a weighting variation to the extraction sets to reduce the cost value result of said error metric cost function wherein the model results based upon the weighting variation are nearer to said normative results based upon the cost value result of said error metric cost function;

and

iv. accepting said set of newly assigned weighting variation weighting coefficients indicating a proportionality of impact as an acceptable set for a model to achieve a more satisfactory predictive result;

whereby a map becomes a tool for improvement of a model over time based upon the expectations established by a user.

269. The method of claim 1 to also provide retaining of thoughts of a user in a structure, wherein:

a. initiating, wherein said user begins a session of use of a map with a prior condition selected from the group of;

i. at the start of the session a goal object exists and has not been deleted or converted to a cnxpt, wherein;

01. requesting from said user generating a hidden goal object to serve as a goal;

and

ii. at the start of the session no goal object exists that has not been deleted or converted to a cnxpt, wherein;

01. generating a hidden goal object to serve as a goal;

b. adding information collected from searching process to the goal, comprising choices made during navigation, jump searching;

and

c. accepting a goal from said user;

whereby the goal serves to collect all of the searching and querying that occurs to attain the goal, and then encapsulates the result into a cnxpt that represents the ttx actually resulting after the user resolves his thoughts;

whereby a goal serves as a learning device to retain information either about a specific topic a user is seeking even if novel, or about the purpose for use of the system when in a particular map or particular sitting;

whereby information regarding navigation is attached to the goal to retain the interest the user had regarding topics when in a setting having a purpose as cast by the goal;

whereby navigation is converted to relationship information to show the connection of the goal to topics viewed in the session;

whereby for some period of its existence, the ttx represented by the cnxpt begun as a goal may appear to be poorly defined, but over time, the representative, as the collection point for information regarding the ttx, will likely become more and more well defined;

whereby goals declare the existence of an abstract concept without the user knowing that he has done so;

whereby a goal may hold a query script and the result sets resulting from the query, navigation tours, user indications from a navigation, a name, a description, and other information;

whereby information resources accessed during the life of the goal are retained with the goal as occurrences to show the relevance of the information resource to the goal.

270. The method of claim 1, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought in a map instance, further including:

a. define a search specification, requesting a result selected from the group of;

i. charge theories from a list of pairs of cnxpts in rule to charge theory applicability pairings in said first identified search base;

ii. evidence items from a list of pairs of cnxpts in evidence to case issue applicability pairings in said first identified search base;

iii. evidence items from a list of pairs of cnxpts in evidence items against fact pairings in said first identified search base;

iv. fact items from a list of pairs of cnxpts in fact to theory of the case applicability pairings in said first identified search base;

v. facts from a list of pairs of cnxpts in evidence items against fact pairings in said first identified search base;

vi. facts from a list of pairs of cnxpts in facts against rule element pairings in said first identified search base;

vii. general precedents from a list of pairs of cnxpts in precedent to rule applicability pairings in said first identified search base;

viii. general rules from a list of pairs of cnxpts in rule to doctrine applicability pairings in said first identified search base;

ix. general rules from a list of pairs of cnxpts in specific rule to general rule applicability pairings in said first identified search base;

x. jurisdictions from a list of pairs of cnxpts in specific rule to jurisdiction'"'"'s law applicability pairings in said first identified search base;

xi. precedents from a list of pairs of cnxpts in precedent to rule applicability pairings in said first identified search base;

xii. rule items from a list of pairs of cnxpts in rule to charge theory applicability pairings in said first identified search base;

xiii. rules from a list of pairs of cnxpts in element to rule applicability pairings in said first identified search base;

xiv. rules from a list of pairs of cnxpts in rule to doctrine applicability pairings in said first identified search base;

xv. specific rule elements from a list of pairs of cnxpts in element to rule applicability pairings in said first identified search base;

xvi. specific rule elements from a list of pairs of cnxpts in facts against rule element pairings in said first identified search base;

xvii. specific rule elements from a list of pairs of cnxpts in specific rule to general rule dependency pairings in said first identified search base;

xviii. specific rules from a list of pairs of cnxpts in specific rule to general rule applicability pairings in said first identified search base;

xix. specific rules from a list of pairs of cnxpts in specific rule to jurisdiction'"'"'s law applicability pairings in said first identified search base;

xx. theories of the case from a list of pairs of cnxpts in fact to theory of the case applicability pairings in said first identified search base;

xxi. model equations from a list of pairs of cnxpts in model equation dependency pairings in said first identified search base;

xxii. dependent elements from a list of pairs of cnxpts in dependency pairings in said first identified search base;

and

xxiii. precedent elements from a list of pairs of cnxpts in dependency pairings in said first identified search base;

b. accepting zero or more additional parts of a first or next wisdom request command providing zero or more ordering specifications stating an ordering metric to apply to said first form of result after completion of said search if either said form of result, said type of wisdom sought, or said additional specifications indicate that an ordering is to be performed, according to finding, searching, query and retrieval means, said ordering by ordering metric to be applied in the order of specification of said additional part;

c. accepting zero or more additional parts of said first or next wisdom request command providing, in each part, an action to apply to said first form of result after completion of said specification for search, according to finding, searching, query and retrieval means, said action to apply selected from the group of;

i. navigating to a cntexxt based upon in a displayed view of said first form of result;

ii. presenting a list, area, portfolio, result set or other display of said first form of result holding identity indicators found in said search;

iii. allowing user to interact with said first form of result presented;

iv. submission of said first form of result to an analytic for invocation;

v. exporting said first form of result;

vi. storing said first form of result;

and

vii. altering said co-location, flow, or other map to show said first form of result;

d. accepting, wherein user is allowed to interact with said first form of result presented in combination with indication to refine a search result by culling, zero or more additional parts of said first or next wisdom request command providing, in each part, an action to apply to said first form of result after completion of said search, according to finding, searching, query and retrieval means.

271. The method of claim 1 to also provide searching by executing stored instructions that perform operations to cause the computer system to locate wisdom sought, further including:

a. accepting a user search query during a phase of system use selected from the group;

i. during selection of a map definition to generate a map instance for use to select information selected from the group of;

01. a domain of wisdom;

02. output from a machine learning algorithm;

and

03. data of a certain security classification;

ii. during map definition by supplying fxxt specifications in the map definition to select information selected from the group of;

01. a domain of wisdom;

02. a version of data;

03. a specific version of output from a machine learning algorithm;

04. exemplar data;

05. data entered by a specific user demographic;

06. a subjective perspective;

and

07. a recommendation;

and

iii. during use of a map instance to select information selected from the group of;

01. zero or more info-items;

02. zero or more external information resources;

03. zero or more cnxpts;

04. a knowledge gap at a time horizon of nine months;

05. a product gap at a time horizon of three years ;

06. tcepts available at a time horizon;

07. market segment value at a time horizon;

08. a non-existent concept a user has been thinking about;

09. a non-existent concept an investor wishes to invest in;

10. the competitive value of a product at a time horizon years into the future in terms of sales anticipated in a selected set of market segments given that the product will have specific features which satisfy the market segment requirements that may also be satisfied by competing products;

11. the relevant and admissible evidence of public corruption involved in a lawsuit, shone in the order useful to a defense presentation in an opening statement;

12. the product changes suggested to resolve TRIZ contradictions for a product planned for next year;

13. the set of historic concepts that a scholar should know well in a field of study including those concepts that are not yet resolved but will potentially change the nature of the field in many years into the future;

14. the answer to a set of symptoms for an obscure and model specific technical issue on a three year old computer that is of a product line that has been named the same for 30 years but has had a new design every six months;

15. the limit of knowledge regarding a sub-field of microbiology involved in a product liability lawsuit where a question regarding what the defendant was capable of considering at the time of the purported issue with the product that should have caused a recall;

16. the most recent and effective solutions to a home improvement issue;

17. products available to solve a home improvement issue properly;

18. the current portfolio value of a set of investments in technology by my venture capital group;

19. the 13 year future horizon projection of portfolio value of a set of investments in technology by my venture capital group given competitive pressures and changes in market requirements given new technologies;

20. how well a particular machine learning algorithm performs on a given set of data compared to seven other good performers and crowd wisdom;

21. what information coming in is planted misinformation;

what are the disagreements currently in the crowd;

22. how does my opinion vary from others regarding the completion date of a project given my beliefs regarding requirements causing unplanned changes;

23. what is the collective opinion of the four law firm teams regarding the best order for presenting evidence during the trial given the responses by the defense;

24. how should are agency harmonize our classifications for tariffs with our trading partners in the area of automotive plastics to ensure that we aid the effort in responding to climate change;

25. how will our department do in product development in the next twenty years given the competitive strategy of the 37 regional competitors if we adopt this set of non-carbon releasing techniques;

26. how should our departments be set up to improve these product lines given the effectiveness of these team leads;

27. where am i in learning about the field of topology;

28. what is possible for altering this product over the next fifteen years given the changes in technologies just now being studied;

29. how different is my organization of my research compared to other doctoral students;

30. what are the seminal texts in this field and what are their teachings;

31. what are the apparent causes of this new malady given our data, suggestions, intuitions, beliefs, and wild guesses and how far away from the objective opinion is my perspective;

32. where are the inventors in this field going toward innovations that will lead to break-out products;

33. what are the success factors for the inventors in our company according to past developments and market acceptance;

and

34. what patents do we have that are competitive and what are their lineage and future directions;

whereby a large number of searches are available according to the degree of interaction and data collection available for the commonplace.

272. The method of claim 1 to also provide an understanding of where the understanding of each segment of a field of knowledge will cross over the line to become sheer science fiction and plain lack of knowledge, further including:

a. accepting a definition of a knowledge model comprising a set of one or more fxxts based on information stored regarding the field of knowledge, the information stored comprising a plurality of cnxpts and a plurality of associations, a plurality of cnxpts and a plurality of associations are marked with at least one fxxt of said set of one or more fxxts based on information stored regarding the field of knowledge;

b. accepting a map definition specifying use of said set of one or more fxxts based on information stored regarding the field of knowledge, the map definition specifying how the map instances generated from it will be organized, the organizing to be time ordered where a root of a tree in the forest of knowledge will have existed as a new understanding of those in the field at a point in the past and the leaves of the forest will be un-firm beliefs and showing no actual understanding, the root connected at each level to the leaves by apparent derivations to conceptual understandings within the fabric of the overall understanding of the field each having an estimate of the origination of the conceptual understanding;

c. generating, using said map definition, a map instance;

and

d. accepting navigation toward the leaves of the forest, a wall displayed at a point selected from the group of;

i. between the known and unknown displayed just beyond the concepts having no credence as actually being known and certainly not understood;

ii. between information considered to be useful and information thought to be useless;

iii. between information developed to a stated phase and information thought to be less developed than the requirements of the stated phase, the phase selected from the group of;

01. patent issued;

02. research paper published;

03. research paper peer reviewed;

04. topic discussed only as speculative;

05. product planned using the concept;

06. consensus opinion that the concept is valid;

07. discussions of topic marked top secret compartmentalized;

08. discussions of topic de-classified;

09. technique reviewed but not allowed for use except in cases of last hope;

and

10. techniques fully accepted as standard practices;

and

iv. between information considered to be useful at a point in time and information for which an understanding by anyone did not occur until a point after the point in time;

whereby a definitive wall between the completeness of understanding at a level versus a lack of knowledge can be determined and presented to a user; and

whereby a user can see what is in the box when told to think outside of the box regarding a field of understanding.

273. The method of claim 1 to present a map for associative searching, further including:

a. accepting a map definition wherein at least one hierarchical association between at least two cnxpts states a topic to sub-topic relationship between said at least two cnxpts causing an organization of a resulting map instance by subject matter;

b. forming a map instance from said map definition;

c. determining a first context in said map instance, the context represented by a first cnxpt;

d. presenting the positioned map instance to said user;

e. accepting a command to select, by navigation, a subsequent context based upon intent to access subject matter dissimilar to current subject matter, the subsequent context represented by a second cnxpt defined to represent the subject matter dissimilar to current subject matter;

wherein said similarity is defined according to the purpose of the map;

wherein the degree of dissimilarity is roughly proportional to the accumulated distance covered by the navigation from the current context to each subsequent context, each subsequent context an uncle, cousin, or sibling of the current context;

and

f. focusing on the area of the map instance containing the context represented by the second cnxpt;

whereby a map representing a domain of wisdom may be used for associative searching wherein the conceptual content is co-located by its meaning.

274. The method of claim 1 to also provide for collaboratively working within a commonplace of information, further comprising:

a. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

b. providing an interface for users to view, navigate and enter commands to interface with said commonplace;

c. preparing, by at least one processor, at least one consensus organization of knowledge of said domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means;

d. granting or rejecting access to said commonplace for a given type of interaction;

e. displaying a map instance to a user for initial viewing;

f. forming a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt on a map instance, in one or more phases selected from the group of;

i. connection opportunity offered;

ii. connection requested;

iii. selecting an object of wisdom to act upon;

iv. requesting display of a result set for culling;

v. requesting making contact with a listed person, project consortia, or organization;

vi. requesting contact with at least one person knowledgable regarding a cnxpt representing a concept within a context represented, the cnxpt of said domain of wisdom;

vii. scheduling participation;

viii. stating an opinion;

ix. stating that a connection between two cnxpts should exist;

x. stating status of a task;

xi. stating interest;

xii. offering an incentive;

xiii. offering a funding incentive;

xiv. negotiating for deliverable acceptance;

xv. negotiating for assignment;

xvi. requesting display of a structural view of cntexxts based upon wisdom found;

and

xvii. requesting the navigating to a cntexxt based upon wisdom found;

and

g. accepting and processing a user command and effecting changes therefrom, said user command selected from the group of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace and effect change;

iii. to navigate around a visualization of said commonplace;

and

iv. to request a search for wisdom;

whereby said commonplace becomes a resource with a purpose suitable to said user based on the best available data at a time point as ideas are collected and an authorized user is able to see what is in said commonplace, adjust said commonplace data, and add to said commonplace new ideas.

275. The method of claim 1, to extract a derived ontology subset of the commonplace of information to provide a domain of wisdom basis for a map, further comprising:

a. detailing a map definition;

b. detailing zero or more fxxt specification steps defining a fxxt;

c. accepting from the map definition representing a knowledge model of a domain of wisdom a set of zero or more fxxt instances each fxxt having a coefficient indicating a proportionality of impact of the fxxt on any result of analysis regarding the map;

d. creating, a new empty named derived ontology to hold references to extracted instances and classes of info-item;

said named derived ontology named by said new resultant fxxt by identity;

said named derived ontology when filled to be comprised of a plurality of references to info-items, cnxpt instances and association instances among the plurality of cnxpt instances where each association includes a weight indicating a strength of the association instance, where each info-item instance including a weight indicating importance of the info-item instance of a type;

e. interpreting said map definition;

further including;

i. accepting for processing a definition of a first map listing zero or more fxxts stating sources of wisdom to be referenced as contents in the map;

ii. resolving values for zero or more parameters for processing of said first map;

iii. accepting for analysis, if said map definition lists any fxxt, a first specification step of a first fxxt instance defining tasks to perform for said first fxxt instance;

iv. resolving, if said map definition lists no fxxt, a null fxxt identity;

v. resolving, if said map definition lists any fxxt, values for zero or more parameters of said first specification step of said first fxxt instance;

and

vi. registering, if said map definition lists any fxxt, for proper later invocation zero or more fxxt specifications;

f. creating zero or more temporary derived ontologies, setting an accumulated contextual coefficient indicating proportionality of impact for each temporary derived ontology to a default value;

g. preparing for triggered processing for membership testing for info-items into said named derived ontology of the commonplace of information by interpreting a first specification step of a first fxxt instance listed on said map definition requires trigger-ability;

h. determining membership of an info-item reference in said named derived ontology of the commonplace of information where there are zero or more first fxxts specified on said map definition, by one or more observations before forest extraction is attempted, by detecting zero or more modes for fxxt specification processing by one or more observations;

i. producing into the resulting said named derived ontology by repeating until no classes remain in any temporary instance or class list, zero or more instances of classes of info-items of type;

j. merging into said named derived ontology the summarized references in every temporary derived ontology;

k. performing, prior to release of the resulting said named derived ontology to forest extraction and until no changes are made to the resulting said named derived ontology and a fxxt specification step of a fxxt listed on said map definition requires trigger-ability, triggered interpretation of each fxxt specification step of each such fxxt to determine, recursively, membership of an info-item in the resulting said named derived ontology;

l. invoking, if a fxxt specification step of a fxxt listed on said map definition requires trigger-ability, extraction of a forest on the resulting said named derived ontology;

m. annealing by triggering all trigger-able actions, repeatedly until no changes are made in the resulting said named derived ontology during a round of triggering;

n. annealing, upon completion of forest extraction, by triggering all trigger-able actions, repeatedly until no changes are made in the resulting said named derived ontology during a round of triggering;

and

o. exposing the resulting said named derived ontology, as a data set.

276. The method of claim 1 to also provide generation of a map combining a precedence graph with a hierarchy forest where at least one cnxpt exists in both precedence and hierarchy, further comprising:

a. generating, for hierarchical force directed determination, affinitive association based positioning vectors;

b. rolling up, for precedence aspect force directed position determination, flow associations into flow roll-up precedence tensors to have an effect in positioning of forcing a cnxpt to be in a position relative to a predecessor on a map;

and

c. generating, for map segment force directed position attractor determination, flow tensors based upon previously established map segmentations;

whereby tensors are created to force the ancestors of a cnxpt in a hierarchical presentation to be in positions;

whereby tensors are created to force the predecessors of a cnxpt in a directed graph presentation to be in positions;

whereby generating a map for a domain of wisdom structured as an organization of knowledge of cnxpts results in one or more forms from;

a list, a hierarchical manner, a directed graph manner, or a structure comprising a combination thereof;

whereby the form generated is based on information derived from the included cnxpts and the stated relationships among those cnxpts;

whereby positional relationships between cnxpts are determined from associations of one or more of the types;

hierarchical, flow, precedence, directed, undirected, and affinitive.

277. The method of claim 1 to also provide forest extraction for a map structure, wherein generating the hierarchical skeletal structure for a map definition comprises:

a. ordering into a queue the summarized directed associations of the derived ontology resulting from fxxt extraction by summarized directed association weight, highest weight implying least cost, greatest first, wherein each directed association has a first role considered to be a from role held by a first cnxpt and a second role considered to be a to role held by a second cnxpt, wherein the to role to from role directionality would represent a transitive concept relationship generally of a type selected from the group of;

child to parent, sub category to super category, employee to employer, finish state to start state, dependent to independent, end to start point, succeeding to preceding, outcome to cause, sub-assembly to assembly, detail account to summary account, element to law, tactic to strategy, integer to claim, data set to data collection, class member to class, and leaf to root;

b. forming an empty skeletal structure to be filled with hierarchical tensors and singleton cnxpts;

c. filling the skeletal structure with all cnxpts extracted into a derived ontology for the map, as singletons;

d. examining, while the queue is not empty, each current front summarized directed association in the queue, the front association always having a highest weight of those in the queue, to utilize the highest weight associations in priority order in a minimal cost spanning forest algorithm, wherein;

i. designating the current front summarized directed association for consideration;

ii. adding, if the minimal cost spanning forest algorithm would utilize the current front summarized directed association as an edge in the spanning forest, a hierarchical tensor representing the current front summarized directed association into said skeletal structure;

and

iii. removing the front summarized association from said queue;

whereby the summarized associations are used to form a spanning forest composed of hierarchical tensors between cnxpts.

278. The method of claim 1 to also provide determining of categorization quality of dissection for ingesting, further including:

a. updating the consensus organization of each comparison categorization from said commonplace augmented by all info-items generated from said plurality of members of a returned set of information each a source object suggesting a meaning according to utilize collective consensus through vote tallying means;

b. determining a proper placement of said dissection cnxpt in each said comparison categorization augmented by all info-items generated from said plurality of members of a returned set of information each a source object suggesting a meaning according to map generation means, wherein if a predetermined system setting is set to a first predetermined value said map generation does not alter the positioning of cnxpts existing before performing a search resulting in plurality of members of a returned set, wherein if a predetermined system setting is set to a second predetermined value said map generation does alter the positioning of cnxpts existing before performing a search resulting in plurality of members of a returned set;

c. determining a normalized relevance score for relevance of said dissection concept represented by a dissection cnxpt to each said basis cnxpt, from a predefined formula to compute a sum across all said comparison categorizations wherein a predetermined coefficient based upon the comparison categorization is multiplied against a factor determined from the distance in said comparison categorization of the placement of said dissection cnxpt against each basis cnxpt in a vicinity of a predetermined size from said dissection cnxpt, said relevance score is attached to said binding point info-item for each said derived source object suggesting a meaning for said dissection concept represented by a dissection cnxpt;

d. determining a cumulative relevance score for each said result set item info-item by summing all said relevance scores attached to said binding point info-items for each said derived source object suggesting a meaning stemming from said dissecting of said source object suggesting a meaning;

e. determining, optionally, a normalized value for each said cumulative relevance score for said result set;

f. assigning the order property of each created result set item info-item in said result set to a value converted from said relevance strength assigned wherein the most relevant rsxitems will be sorted to appear at the top of a result set display for culling;

g. making said result set active for culling by displaying result set in an editable format;

h. defining a map to be organized by a classification, wherein similar concepts are in closer proximity than dissimilar concepts;

i. generating a map instance for said map;

and

j. calculating quality corrections according to prediction correction mechanism.

279. The method of claim 1 to also provide constructing of a flow map, further including:

a. assigning a cnxpt pair to a flow by relating the cnxpt pair with a directed association, and performing a marking selected from the group of;

marking the association as a flow of type, marking the association as a member of a fxxt usable as a source for flow associations in one or more map definitions, marking the cnxpts of the cnxpt pair as usable in a flow of type, and setting one or more trait trxrts for each cnxpt of the cnxpt pair with a meaning that the cnxpt is usable in a flow of type;

b. detailing a map definition specifying a resulting map to be a flow of type;

c. performing fxxt extraction, generating, using said map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to one or more associations and two or more cnxpts into the derived ontology;

d. generating, using said map definition, a flow specific derived ontology for the one or more domains of wisdom by reprocessing the associations processed during fxxt extraction to summarize only directed associations for the type of flow sought, including directed associations from fxxts designated before or during extraction as for the type of flow sought by the definition of said map, placing references to one or more summarized flow specific associations and two or more cnxpts into the flow specific derived ontology;

e. inverting, for the purpose of positioning cnxpts, depending upon the flow type and the directional orientation policy specified in said map definition, the sense of the association directionality for all hierarchical associations in the flow specific derived ontology;

f. generating structuring tensors, using said map definition policies, from the summarized hierarchical associations in the flow specific derived ontology, hierarchical tensors forming a skeletal structure for one or more organizations of knowledge for said one or more domains of wisdom wherein the resulting map skeletal structure of said map instance is organized into a descendant spanning forest and zero or more resulting structures selected from the group of;

an enhanced descendent forest, an enhanced descendent forest with augmentation, an ascendant spanning forest, an enhanced ascendant forest, an enhanced ascendant forest with augmentation, a directed graph, and a graph;

g. determining, for each cnxpt in one or more of the cnxpt pairs related by a flow tensor in the spanning forest, the set of elastic surface representative fractional fragments indicated by the map policies and the properties of said cnxpt, if any, to set the strength weight and length of the flow tensor to indicate the policy driven approximate positioning for said cnxpt to be positioned in a fictitious elastic surface canvas for said flow;

h. determining from the policies of the map definition the basis for calculating roll-up, utilizing re-inverted sense or un-inverted generated hierarchical tensors from tree-extraction to prepare for roll-up to ensure that the root is considered as top and leaves are at the bottom logically;

i. generating flow roll-up tensors, and summary flow tensors with weights for enforcing the child cnxpt'"'"'s anchoring location on said elastic surface of a fictitious elastic surface canvas during positioning on said map by anchoring a parent cnxpt to a representative fractional fragment of said fictitious elastic surface canvas based upon said child'"'"'s anchoring location;

j generating positioning for domain of wisdom member cnxpts according to process trees for organization of knowledge generation, position determination and final sizing means for calculation, based upon policies stated in the map definition, wherein said positionings of said cnxpts of the cnxpt pairs related by a flow tensor are computed by tree of the forest, the tree placed into a representative fractional segment of said fictitious elastic surface canvas for initial computation only, each tree of said map according to information selected from the group of;

the map definition, information associated with each cnxpt by trait or time frame or purlieu or property, and information derived from outside of said cnxpt;

k. determining, independently for each tree of the spanning forest, the canvas size of the segment of the representative fractional segment of said elastic surface needed to display the tree for each tree of the forest, the dimensionality of the canvas specified in the map definition, and assembling the segments;

and

l. providing to the user said one or more domains of wisdom for utilization;

whereby the ability is provided to place objects for a 2D, 3D, or 4D map in a position related to the ordering of said object directly or relative to the positioning of others in a flow;

whereby generating an organization of knowledge or a visualization from a map utilizes a combination, calculated pairwise by unique cnxpt pair, of the weights of the associations that are marked by fxxts in the set of fxxts listed in the map definition;

whereby determining the latent variables positioning the cnxpts of a domain of knowledge into a logically correct 2 to 4 dimensional diagram satisfying the subjective perspective of a user or the objective perspective of a crowd forms a presentation;

whereby a cause independent Bayesian network with mechanisms ordered by strength to effect weak cause elimination may be drawn automatically.

280. The computer-implemented method of claim 279, further comprising:

a. extracting at least one cnxpt representing a state from which a decision determinative of a task initiation, at least one cnxpt representing a predecessor task, at least one cnxpt representing a successor task, and at least one association connecting said cnxpt representing a decision to said cnxpt representing said a predecessor task, and at least one association connecting said cnxpt representing said predecessor task to said cnxpt representing said successor task indicative of the conditional completion of the successor task, by fxxt extraction based upon consensus voting;

and

b. depicting at least one predecessor task as a cnxpt in a flow graph organization of knowledge wherein said cnxpt is determinative of the completion of a successor task and the flow graph organization of knowledge is structured to place said predecessor task cnxpt earlier in the time aspect of the organization of knowledge of the map than said successor task cnxpt.

281. The method of claim 1 to also provide modeling on the basis of one or more maps and one or more modeling rules, further including:

a. accepting a set of one or more modeling rules;

b. creating an empty first derived ontology;

c. determining the nature of each modeling rule to plan model execution, the nature selected from the group of;

i. rules that determine whether a cnxpt or an association should or should not be in said first derived ontology;

ii. rules that invoke an algorithm or analytic;

iii. rules that are held in a property of a cnxpt and are intended to be interpreted before or during map generation;

iv. rules that determine a value of a property of a cnxpt or an association that could affect the skeletal structuring of a map being generated from said first derived ontology;

v. rules that determine whether an association should or should not be used in the skeletal structure of a map to be generated from said first derived ontology;

vi. rules that depend upon results of generating forests but not later steps of map generation;

vii. rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied prior to roll-ups;

viii. rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied during roll-ups;

ix. rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied after roll-ups;

x. rules that could affect the positioning of info-items on a map being generated from said first derived ontology and that must be applied during positioning;

xi. rules that depend upon results of positioning but not later steps in map generation;

xii. rules that affect positioning after map completion;

xiii. rules that affect a value of a property of a cnxpt or an association but do not depend upon positioning of cnxpts;

xiv. rules not considered in positioning process;

xv. rules associated with a cnxpt depending upon its display positioning;

xvi. rules associated with an association depending upon its display positioning;

xvii. rules affecting a target cnxpt depending upon the logical positioning of the target cnxpt relative to a base cnxpt, the position of the target cnxpt relative to the base cnxpt selected from the group of;

sibling, uncle, parent, child, neighbor, first child, last child, all children, all parents, all siblings, all children of primary parent, all children of particular parent, all other children of primary parent, all other children of particular parent, all neighbors within a particular distance sub-tree, ancestor, descendant, in-bound adjacent neighbor, out-bound adjacent neighbor, in-flow adjacent neighbor, out-flow adjacent neighbor, root, leaf of particular subtree, cousin, secondary parent, root of different tree, senior root of forest, just prior cnxpt in breadth-first walk, next cnxpt in breadth-first walk, just prior cnxpt in level-order walk, next cnxpt in level-order walk, just prior cnxpt in pre-order walk, next cnxpt in pre-order walk, just prior cnxpt in post-order walk, next cnxpt in post-order walk, just prior cnxpt in in-order walk, next cnxpt in in-order walk, just prior cnxpt in depth-first walk, next cnxpt in depth-first walk, member of identified area, member of area occupied by base but not including base, member of identified area other than base, same cnxpt present in different tree, same cnxpt present in different map, different cnxpt present in same tree and directly related by association, different cnxpt present in different tree but directly related by association, different cnxpt present in different map but directly related by association;

xviii. rules affecting a target association depending upon the logical positioning of the target association relative to a base cnxpt;

xix. rules calculating a value of a property of a cnxpt;

xx. cell rules defined for all members of a cnxpt class calculating a value of a property of a cnxpt instance based upon a formula specified for the property in the cnxpt class that the cnxpt is an instance of;

xxi. cell rules defined for a cnxpt instance calculating a value of a property of the cnxpt instance based upon a formula specified for the property in the cnxpt instance;

xxii. rules calculating a value of a property of an association;

xxiii. cell rules defined for all members of an association class calculating a value of a property of an association instance based upon a formula specified for the property in an association class that the association is an instance of;

xxiv. cell rules defined for an association instance calculating a value of a property of the association instance based upon a formula specified for the property in the association instance;

xxv. rules for determining an area comprising zero or more cnxpts and zero or more associations having one or more of said zero or more cnxpts in a role, where specified further rules are to be applied;

xxvi. rules determining inclusion of a cnxpt into an area based upon a characteristic of the cnxpt;

xxvii. rules affecting a cnxpt in an area;

xxviii. rules determining exclusion of a cnxpt from an area based upon a characteristic of the cnxpt;

xxix. rules controlling a filter determining visibility of a cnxpt from an area based upon a characteristic of the cnxpt;

xxx. rules controlling a filter determining visibility of a cnxpt based upon a characteristic of the cnxpt;

xxxi. rules that are held in a property of a cnxpt and are intended to be interpreted after map generation;

and

xxxii. rules that affect display of an info-item;

d. executing one or more cnxpt sub-setting operation selected from the group of;

a query yielding a result set of zero or more cnxpts, a query yielding a result set of zero or more associations and the cnxpts having roles on the zero or more associations, a map holding a result set of zero or more cnxpts and zero or more associations, a reduction, an existing derived ontology, a fxxt extraction, a flow extraction, execution of an analytic, a result set of zero or more cnxpts, an area having zero or more cnxpts, a result set of zero or more associations and the cnxpts having roles on the zero or more associations, selection of a data set, selection of a portfolio, selection of a uniquely identified categorization, selection of a uniquely identified clump extract set, a filter application, a user ad hoc selection set of zero or more associations and the cnxpts having roles on the zero or more associations, and a user ad hoc selection set of zero or more cnxpts;

to obtain a set of cnxpts and associations in a first derived ontology resulting from said sub-setting operation;

e. executing all rules that determine whether a cnxpt or an association should or should not be in said first derived ontology;

f. executing all rules that determine a value of a property of a cnxpt or an association that could affect the skeletal structuring of a map being generated from said first derived ontology;

g. extracting a descendent tree forest from said first derived ontology according to fxxt basic descendant spanning tree extraction means while utilizing modeling rules that determine whether an association should or should not be used in the skeletal structure of a map to be generated from said first derived ontology;

h. executing production of enhanced descendent forest, basic ascending forest, and enhanced ascending forest using the descendant spanning forest and said first derived ontology;

i. executing all rules that depend upon results of generating forests but not later steps of map generation;

j. executing all rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied prior to roll-ups;

k. executing roll-ups on the generated forests while executing rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied during roll-ups;

l. executing all rules that determine a value of a property of a cnxpt or an association that could affect the positioning of a map being generated from said first derived ontology and that must be applied after roll-ups;

m. executing positioning on the generated forests after roll-ups, utilizing all rules that could affect the positioning of info-items on a map being generated from said first derived ontology and that must be applied during positioning, according to process trees for visualization generation, position determination and final sizing means;

n. executing all rules that depend upon results of positioning but not later steps in map generation;

o. determining efficient derivation trees from each rule of a type selected from the group of;

the set of modeling rules that are defined for the model, the properties defined by formulas of each cnxpt class, and the properties defined by formulas of each cnxpt instance;

to trigger activation of a rule when an event of type occurs, the event type selected from the group of;

a rule input changes, an input of a property formula changes, the object set to which a rule would apply changes, an event that would cause the output of a rule to change, an iterative loop cycle begins, a termination condition on an iterative loop has occurred, and a termination of rule activation occurs because no rule should be triggered;

p. interpreting modeling rules iteratively based upon the derivation trees, the modeling rules selected from the group of;

i. rules that invoke an algorithm or analytic;

ii. rules that affect positioning after map completion;

iii. rules that affect a value of a property of a cnxpt or an association but do not depend upon positioning of cnxpts;

iv. rules not considered in positioning process;

v. rules associated with a cnxpt depending upon its display positioning;

vi. rules associated with an association depending upon its display positioning;

vii. rules affecting a target cnxpt depending upon the logical positioning of the target cnxpt relative to a base cnxpt, the position of the target cnxpt relative to the base cnxpt selected from the group of;

sibling, uncle, parent, child, neighbor, first child, last child, all children, all parents, all siblings, all children of primary parent, all children of particular parent, all other children of primary parent, all other children of particular parent, all neighbors within a particular distance sub-tree, ancestor, descendant, in-bound adjacent neighbor, out-bound adjacent neighbor, in-flow adjacent neighbor, out-flow adjacent neighbor, root, leaf of particular subtree, cousin, secondary parent, root of different tree, senior root of forest, just prior cnxpt in breadth-first walk, next cnxpt in breadth-first walk, just prior cnxpt in level-order walk, next cnxpt in level-order walk, just prior cnxpt in pre-order walk, next cnxpt in pre-order walk, just prior cnxpt in post-order walk, next cnxpt in post-order walk, just prior cnxpt in in-order walk, next cnxpt in in-order walk, just prior cnxpt in depth-first walk, next cnxpt in depth-first walk, member of identified area, member of area occupied by base but not including base, member of identified area other than base, same cnxpt present in different tree, same cnxpt present in different map, different cnxpt present in same tree and directly related by association, different cnxpt present in different tree but directly related by association, different cnxpt present in different map but directly related by association;

viii. rules affecting a target association depending upon the logical positioning of the target association relative to a base cnxpt;

ix. rules calculating a value of a property of a cnxpt;

x. cell rules defined for all members of a cnxpt class calculating a value of a property of a cnxpt instance based upon a formula specified for the property in the cnxpt class that the cnxpt is an instance of;

xi. cell rules defined for a cnxpt instance calculating a value of a property of the cnxpt instance based upon a formula specified for the property in the cnxpt instance;

xii. rules calculating a value of a property of an association;

xiii. cell rules defined for all members of an association class calculating a value of a property of an association instance based upon a formula specified for the property in an association class that the association is an instance of;

xiv. cell rules defined for an association instance calculating a value of a property of the association instance based upon a formula specified for the property in the association instance;

xv. rules for determining an area comprising zero or more cnxpts and zero or more associations having one or more of said zero or more cnxpts in a role, where specified further rules are to be applied;

xvi. rules determining inclusion of a cnxpt into an area based upon a characteristic of the cnxpt;

xvii. rules affecting a cnxpt in an area;

xviii. rules determining exclusion of a cnxpt from an area based upon a characteristic of the cnxpt;

xix. rules controlling a filter determining visibility of a cnxpt from an area based upon a characteristic of the cnxpt;

xx. rules controlling a filter determining visibility of a cnxpt based upon a characteristic of the cnxpt;

xxi. rules that are held in a property of a cnxpt and are intended to be interpreted after map generation;

and

xxii. rules that affect display of an info-item;

and

q. returning control to the supervising process while monitoring for triggering due to a change of data or organization of info-items;

whereby efficient modeling including interpretation of cell-like formulas for properties of cnxpts is performed.

282. The method of claim 1 to also provide for crystalizing meaning of cnxpts with scant documentation, further comprising:

a. distilling by suppressing overlapping information regarding a first cnxpt to automatically crystalize the essence of the concept represented by the first cnxpt in a generated map wherein the first cnxpt is classified as a sub-type of an ancestor concept represented by a second cnxpt, wherein;

i. acting on subject identifiers of the first cnxpt where the identifier contents overlap the contents of an identifier of the ancestor concept represented by a second cnxpt and the overlap is identifiable and separable, by trimming the identifiable overlapping information by suppressing it for the map, the subject identifiers selected from the group of;

01. subject identifier occurrence relationships from the first cnxpt to a txo indicating that the topic represented by the txo is relevant to and somewhat identifies the subject represented by the referencing first cnxpt and also a subject identifier occurrence relationship of the same sign exists from the second cnxpt to the same txo indicating that the topic represented by the txo is relevant to and somewhat identifies the subject represented by the referencing second cnxpt in the map;

02. subject identifier occurrence relationships from the first cnxpt to a txo indicating that the topic represented by the txo is relevant to and identifies the subject represented by the referencing first cnxpt to a positive degree less than the degree of a subject identifier occurrence relationship existing from the second cnxpt to the same txo indicating that the topic represented by the txo is relevant to and somewhat identifies the subject represented by the referencing second cnxpt in the map;

03. subject identifier occurrence relationships from the first cnxpt to a txo indicating that the topic represented by the txo is clearly not relevant to and distinguishes the subject represented by the referencing first cnxpt as shown by a negative degree and the degree is less negative than that of a subject identifier occurrence relationship existing from the second cnxpt to the same txo indicating that the topic represented by the txo is clearly not relevant to and distinguishes the subject represented by the referencing second cnxpt in the map;

04. associations from the first cnxpt to a txo indicating that the topic represented by the txo is relevant to and somewhat identifies the subject represented by the referencing first cnxpt and also an association of the same direction exists from the second cnxpt to the same txo indicating that the topic represented by the txo is relevant to and somewhat identifies the subject represented by the referencing second cnxpt in the map;

05. associations from the first cnxpt to the second cnxpt identified after the final stage of map generation as they have been replaced by the tensors used for forming the skeletal structure, but only suppressing them where the association is to be utilized as all or a part of a subject identifier in the map;

06. a result set item entry in a result set used as a subject identifier of the first cnxpt, whether from a query or a result of culling, the result set item also appearing in a result set used as a subject identifier of the ancestor concept represented by the second cnxpt in the map;

07. a first descriptive phrase of the subject description of the first cnxpt where the phrase is the same as a descriptive phrase of the subject description of the ancestor concept represented by a second cnxpt, by suppressing the use of the descriptive phrase in the subject description of the first cnxpt in the map;

08. a search query used as a subject identifier of the first cnxpt, the query having a scope that would sweep up the same results as a search query used as a subject identifier of the ancestor concept represented by the second cnxpt, by suppressing the results produced in common with the query of the second cnxpt in the map;

and

09. a keyword associated with the first cnxpt and also with the second cnxpt indicating that the topic represented by the keyword is relevant to and somewhat identifies the subject represented by the first cnxpt and the second cnxpt in the map;

and

ii. determining that there is information of a comparable form that is associated with the first cnxpt that is also associated with a second cnxpt, the information of a comparable form selected from the group of;

01. a first trait of the first cnxpt, the trait having a first value, where the first trait value is close to the trait value of the same trait of the ancestor concept represented by a second cnxpt, by suppressing the use of the first trait of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

02. a first element trait of the first cnxpt, the element trait stating an element of a rule of applicability or one of a set of facts that must all be proven, where the first element trait value is the same as an element trait of the ancestor concept represented by a second cnxpt, by suppressing the use of the first element trait of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

03. a first TRIZ principle challenge trait value of the first cnxpt, the TRIZ principle challenge trait stating as a value one specific contradiction found applicable to the first cnxpt within a pattern of observed technical contradictions in design, where the first TRIZ principle challenge trait value is the same as a TRIZ principle challenge trait value of the ancestor concept represented by a second cnxpt, by suppressing the use of the first TRIZ principle challenge trait value of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

04. a first TRIZ principle trait value of the first cnxpt, the TRIZ principle trait stating as a value one desired answer to an observed technical contradiction in design seen applicable to the first cnxpt, where the first TRIZ principle trait value is the same as a TRIZ principle trait value of the ancestor concept represented by a second cnxpt, by suppressing the use of the first TRIZ principle trait value of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

05. a first product feature trait of the first cnxpt, the product feature trait having a first value, where the first product feature trait value is very similar to the product feature trait value of the same product feature trait of the ancestor concept represented by a second cnxpt, by suppressing the use of the first product feature trait of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

06. a first market area trait of the first cnxpt, the market area trait having a first value, where the first market area trait value is very similar to the market area trait value of the same market area trait of the ancestor concept represented by a second cnxpt, by suppressing the use of the first market area trait of the first cnxpt where it is utilized as all or a part of a subject identifier in the map;

and

07. a first vote agreeing generally to the subject of the first cnxpt where the first vote states as scope of agreement to the subject essentially the same scope as given in a vote agreeing to the subject of the ancestor concept represented by a second cnxpt, by suppressing the use of the first vote for the first cnxpt where the vote is utilized as all or a part of a subject identifier in the map;

whereby a cnxpt may be seen more readily as differentiated from its ancestors.

283. The method of claim 1 to also provide generation of a map combining a precedence graph with a hierarchy forest where at least one cnxpt exists in both precedence and hierarchy, further comprising:

a. generating, for hierarchical force directed determination, affinitive association based positioning vectors from all rolled up summarized affinitive associations having endpoints at different depths in the extracted spanning forest, the rolled up associations selected from the group of;

uncle roll-up associations, and cousin roll-up associations;

to yield zero or more tensors selected from the group of;

to-uncle attractor tensors, and between-sibling-ring attractor tensors;

b. rolling up, for precedence aspect force directed position determination, precedence-basis flow indicating hierarchical association relationships with a marking selected from the group of;

dependency, process flow, causality, surrogate causality, conditioned-upon, precedence, and surrogate associations each between a surrogate first cnxpt representing a fixed point of a timing precedence constraint to a second cnxpt;

into flow roll-up precedence tensors to have an effect in positioning of forcing a cnxpt to be in a position relative to a predecessor on a map, the flow roll-up precedence tensors selected from the group of;

flow between-sibling-ring attractor tensors, and flow to-uncle attractor tensors;

and

c. generating, for map segment force directed position attractor determination, zero or more flow tensors each from a cnxpt to a flow aspect position, the flow tensor based upon a constraint selected from the group of;

a previously established map segmentation, a map segment centroid position, a process flow line, a map edge, a position established for a senior precedence cnxpt or surrogate cnxpt, a hierarchical flow tensor for an earliest or senior precedence cnxpt or surrogate cnxpt;

whereby tensors are created to force the ancestors of a cnxpt in a hierarchical presentation to be in positions;

whereby tensors are created to force the predecessors of a cnxpt in a directed graph presentation to be in positions;

whereby generating a map for a domain of wisdom structured as an organization of knowledge of cnxpts results in one or more forms from;

a list, a hierarchical manner, a directed graph manner, or a structure comprising a combination thereof;

whereby the form generated is based on information derived from the included cnxpts and the stated relationships among those cnxpts;

whereby positional relationships between cnxpts are determined from associations of one or more of the types;

hierarchical, flow, precedence, directed, undirected, and affinitive.

284. The method of claim 1 to also provide ensembling of machine learning results, with tuning by comparison to exemplar, further including:

a. combining relationships found between conceptual objects by a plurality of machine learning algorithms into a map generation utilizing fxxt marking to encapsulate the machine learning results, wherein;

i. define a map to utilize the set of fxxts;

ii. assigning to each first fxxt a weighting coefficient indicating a proportionality of impact of said first fxxt to allow for prioritization of the information in one fxxt over another;

iii. marking the results of each machine learning algorithm with a different fxxt identity;

iv. assigning as admixture coefficients a weighting coefficient indicating a proportionality of impact to each machine learning result fxxt in the map definition;

and

v. summing the information in various fxxts as adjusted by the weighting coefficient indicating a proportionality of impact for each fxxt so that, for any hierarchical association between the same two cnxpts a single representative hierarchical association is obtained, and so that, after map structuring, for any association between the same two cnxpts a single representative affinitive association is obtained and a single value of each property of each cnxpt is obtained;

b. performing a comparison a regression to determine the best admixture weighting by comparing for best quality against an exemplar, the exemplar source selected from the group of;

crafted by hand, obtained from a reliable method, determined from a harmonization of crowd beliefs, and obtained by adversarial testing;

whereby a unified ensembling structure is provided for combining machine learning results using admixture coefficients to generate maps.

285. The method of claim 1 to also provide to a user a recommendation stating the most important concept in a context to view next in a conceptual hierarchy by highlighting strength of recommendation by increased size, the recommendation updated, further including:

a. accepting a definition of a knowledge model comprising a set of one or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations, the information in at least one fxxt stemming from votes of users;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, the importance calculation based upon the strength of recommendation, each context represented by a cntexxt also represented by a cnxpt and positioned;

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the highest strength recommendation of the cnxpts in the context consuming more space of the context and larger than less strongly recommended cnxpts in the context, the navigation in a mode selected from the group of;

data set, and visualization;

e. accepting user interaction and voting on the map instance, the interest shone and the voting stored into the commonplace and accessible through a fxxt referenced in the map definition;

and

f. generating a new map instance from the map definition upon demand;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more strongly recommended concepts larger than others.

286. The method of claim 1 to also provide to a user a recommendation stating the most important concept in a context to view next in a conceptual hierarchy by highlighting strength of recommendation by increased size, the recommendation updated, further including:

a. accepting a definition of a knowledge model comprising a set of one or more fxxts based on information stored regarding at least the concept relating to the context, the information stored comprising one or more cnxpts and zero or more associations, the information in at least one more heavily weighted fxxt stemming from interest shone and votes of the user;

b. accepting a map definition specifying use of said set of zero or more fxxts based on information stored regarding at least the concept relating to the context, to create a map instance of type selected from the group of;

tree, decision tree, forest, and Bayesian network;

or other hierarchical organization of knowledge;

c. generating, using said map definition, a map instance, the generation causing positioning of concepts represented by cnxpts based upon strongest hierarchical associations and importance of concepts, the importance calculation based upon the strength of recommendation, each context represented by a cntexxt also represented by a cnxpt and positioned;

d. accepting navigation by the user from the root of the hierarchy, the user being presented with a set of cnxpts when entering a context represented by a cntexxt, the highest strength recommendation of the cnxpts in the context consuming more space of the context and larger than less strongly recommended cnxpts in the context, the navigation in a mode selected from the group of;

data set, and visualization;

e. accepting user interaction and voting from the user on the map instance, the interest shone by the user and the voting by the user stored into the commonplace and accessible through a fxxt referenced in the map definition;

and

f. generating a new map instance from the map definition upon demand;

whereby the map provides a user with a recommendation of what concept to view in each context around a concept by displaying more strongly recommended concepts larger than others, where the interest shone and voting by the user are taken into consideration more strongly than that of other users.

287. The method of claim 1, to ensemble machine learning results with crowd sourced information, further including:

a. combining relationships found between conceptual objects by a plurality of machine learning algorithms as well as by a crowd into a map definition utilizing fxxt marking to encapsulate the results by source, wherein;

i. define a map to utilize the set of fxxts;

ii. marking the data from user votes or other sources with distinct fxxt identities;

iii. marking the results of each machine learning algorithm with a different, distinct fxxt identity;

iv. assigning as admixture coefficients a weighting coefficient indicating a proportionality of impact to each fxxt in the map definition to allow for prioritization of the information in one fxxt over another;

v. summing the information in various fxxts as adjusted by the weighting coefficient indicating a proportionality of impact for each fxxt so that, for any hierarchical association between the same two cnxpts a single representative hierarchical association is obtained, and so that, after map structuring, for any association between the same two cnxpts a single representative affinitive association is obtained and a single value of each property of each cnxpt is obtained;

vi. generating a map instance from the map definition;

vii. accepting additional user voting;

viii. storing user votes;

and

ix. utilizing user votes upon later instantiation of said map;

whereby a unified ensembling structure is provided for combining machine learning results and crowd wisdom using admixture coefficients to generate maps.

288. The method of claim 1 to also provide controlled combination of sparse data of various qualities and sources to obtain modeling results by use of fxxts in ensemble, further including:

a. combining relationships found between conceptual objects by a plurality of sources selected from the group of;

machine learning algorithms, a crowd, public sources, private sources, and historic data;

into a map definition utilizing fxxt marking to encapsulate the results by source, the types of relationships represented by associations which are to some degree correlated to a needed relationship in a model, using some relationships that would be discarded if better information was available, wherein;

i. define a map to utilize the set of fxxts;

ii. marking the data from different batches and sources with distinct fxxt identities;

iii. marking each batch of results of each machine learning algorithm with a different, distinct fxxt identity;

iv. assigning as admixture coefficients a weighting coefficient indicating a proportionality of impact to each fxxt in the map definition to allow for prioritization of the information in one fxxt over another;

v. summing the information in various fxxts as adjusted by the weighting coefficient indicating a proportionality of impact for each fxxt so that, for any hierarchical association between the same two cnxpts a single representative hierarchical association is obtained, and so that, after map structuring, for any association between the same two cnxpts a single representative affinitive association is obtained and a single value of each property of each cnxpt is obtained;

vi. generating a map instance from the map definition;

vii. obtaining modeling results based upon the map;

viii. accepting and storing additional user voting;

ix. accepting and storing additional data from other sources, replacing superseded data;

and

x. utilizing improved data upon later instantiation of said map;

whereby the technique improves the norm where decisions regarding the future are based upon wild guesses;

whereby the technique allows use of assumptions to improve the norm where any guess is better than no guess for priors in a Bayesian model;

whereby sparse data causes an inability to connect the dots, resulting in disjointed forests of trees if just the assured relationships are used;

whereby the technique improves the norm where available input numbers are often sparse due to the cost, time lost, poor modeling, and fear that more data is needed that slow obtainment;

whereby use of a surrogate relationship between concepts that runs roughly like a needed relationship that is sparse will give better results than no data;

whereby use of a surrogate relationship, that is itself sparse, between concepts that runs roughly like a needed relationship that is also sparse will give better results than no data;

whereby data is sparse for new concepts, but in most cases the new concept is a little like an older concept which can serve its analogous data to fill in what is needed for the new concept;

whereby for data anticipated to be of high-dimensionality sparse data may have lower dimensionality;

whereby a market segment may be well defined and its sub-segments known, so that the requirements of each market would be known for the present and past horizons, but the segments and requirements for a future of 50 years would be difficult to obtain, yet the use of the present numbers as a well understood surrogate for the 20 year horizon would be considered reasonable, yet sparse;

whereby projecting into the future requires the reliance on sparse data, but over time that sparse data will be filled out and the same modeling equations will produce better results, such that a prediction of a ten year horizon will improve when re-predicted in five years because the five years will see the improvement in the sparse data used;

whereby intelligence makes use of these sorts of meta-facts because the veracity of their information is always suspect; and

whereby use of sparse data encapsulated by a fxxt can more effectively be managed.

289. The method of claim 1 to also provide controlled combinations of replacement information to fill in for data elements that are missing or deficient to obtain modeling results by use of fxxts in ensemble, with improvement, further including:

a. incorporating surrogate data into a map, wherein;

i. marking by zero or more first surrogate fxxts a set of first surrogate relationships represented by first surrogate associations between cnxpts, the cnxpts referenced by the roles of the first surrogate associations, the surrogate relationships merely of a similar nature to relationship data seen as the appropriate data needed for a map, the appropriate data in a set of first base fxxts, the appropriate data deficient for one or more reasons selected from the group of;

missing, sparse, partially available, noisy, of low veracity, preliminary estimates, only wildly guessed, available for only an incomplete range of a demographic, available for only an incomplete range of type, and available for only an incomplete dimensionality;

ii. marking by zero or more second surrogate fxxts a set of concepts represented by first surrogate cnxpts, the surrogate cnxpts merely of a similar nature to concept data seen as the appropriate data needed for a map, the appropriate data in a set of second base fxxts, the appropriate data deficient for one or more reasons selected from the group of;

missing, sparse, partially available, noisy, of low veracity, preliminary estimates, only wildly guessed, available for only an incomplete range of a demographic, and available for only an incomplete range of type;

iii. marking by zero or more third surrogate fxxts a set of surrogate info-items, the surrogate info-items merely of a similar nature to data seen as the appropriate data needed for a map, the appropriate data in a set of third base fxxts, the appropriate data deficient for one or more reasons selected from the group of;

missing, sparse, partially available, noisy, of low veracity, preliminary estimates, only wildly guessed, available for only an incomplete range of a demographic, and available for only an incomplete range of type;

iv. marking by zero or more fourth surrogate fxxts a set of surrogate values, the surrogate values merely of a similar nature to data seen as the appropriate data needed for a map, the appropriate data in a set of fourth base fxxts, the appropriate data deficient for one or more reasons selected from the group of;

missing, sparse, partially available, noisy, of low veracity, preliminary estimates, only wildly guessed, available for only an incomplete range of a demographic, available for only an incomplete range of type, and available for only an incomplete dimensionality;

v. marking each batch of results of each machine learning algorithm with a different, distinct fxxt identity;

and

vi. accepting a map definition combining relationships found between conceptual objects by a plurality of sources selected from the group of;

surrogate fxxts, base fxxts, machine learning algorithms, a crowd, votes of the user, public sources, private sources, and historic data;

into a map definition utilizing fxxt marking to encapsulate the results by source, using surrogate data that would be discarded if better information was available, the map definition referencing said first surrogate fxxts, said second surrogate fxxts, said third surrogate fxxts, said fourth surrogate fxxts, said first base fxxts, said second base fxxts, said third base fxxts, and said fourth base fxxts, and assigning as admixture coefficients a weighting coefficient indicating a proportionality of impact to each fxxt in the map definition to allow for prioritization of the information in one fxxt over another, assigning to each surrogate fxxt a coefficient indicating a proportionality of impact of the fxxt on any result of analysis, the surrogate coefficient indicating a proportionality of impact of the fxxt on any result of analysis less than the coefficient indicating a proportionality of impact of the fxxt on any result of analysis of the corresponding base fxxt, the difference in coefficients greater where the base data is of better quality, and lower where the base data has more deficiencies;

b. generating a map instance from the map definition;

wherein;

i. performing fxxt extraction, forming a union of the information in various fxxts and then summarizing the information as adjusted by the weighting coefficient indicating a proportionality of impact for each fxxt so that, for any hierarchical association between the same two cnxpts a single representative hierarchical association is obtained, and so that, after map structuring, for any association between the same two cnxpts a single representative affinitive association is obtained and a single value of each property of each cnxpt is obtained;

generating, using said map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to one or more associations and two or more cnxpts into the derived ontology;

ii. generating structuring tensors, using said map definition policies, from the summarized hierarchical associations in the derived ontology, hierarchical tensors forming a skeletal structure for one or more organizations of knowledge for said one or more domains of wisdom wherein the resulting map skeletal structure of said map instance is organized into a descendant spanning forest and zero or more resulting structures selected from the group of;

an enhanced descendent forest, an enhanced descendent forest with augmentation, an ascendant spanning forest, an enhanced ascendant forest, an enhanced ascendant forest with augmentation, a directed graph, and a graph;

iii. determining, the policy driven approximate positioning for cnxpts;

iv. determining from the policies of the map definition the basis for calculating roll-ups;

v. generating roll-up tensors, and summary tensors;

vi. generating positioning for domain of wisdom member cnxpts according to process trees for organization of knowledge generation, position determination and final sizing means for calculation, based upon policies stated in the map definition;

vii. determining canvas sizes based upon the map definition, and assembling the segments;

c. obtaining modeling results based upon the map;

d. providing to the user said one or more domains of wisdom for utilization;

e. accepting and storing additional user voting;

f. accepting and storing additional data from other sources, replacing superseded and unneeded surrogate data, changing fxxt specifications of the map definition as needed;

and

g. utilizing improved data upon later instantiation of the map definition;

whereby the technique improves the work flow of generating and updating models, allowing the user to use surrogate data in place of final data, to control use of versions of data, to retain supervision votes in a controlled, versioned manner, to ensemble data from various sources in an admixture structure, and using wild guesses regarding the future;

whereby the technique improves the norm where decisions regarding the future are based upon wild guesses;

whereby the technique allows use of assumptions to improve the norm where any guess is better than no guess for priors in a Bayesian model;

whereby sparse data causes an inability to connect the dots, resulting in disjointed forests of trees if just the assured relationships are used;

whereby the technique improves the norm where available input numbers are often sparse due to the cost, time lost, poor modeling, and fear that more data is needed that slow obtainment;

whereby use of a surrogate relationship between concepts that runs roughly like a needed relationship that is sparse will give better results than no data;

whereby use of a surrogate relationship, that is itself sparse, between concepts that runs roughly like a needed relationship that is also sparse will give better results than no data;

whereby data is sparse for new concepts, but in most cases the new concept is a little like an older concept which can serve its analogous data to fill in what is needed for the new concept;

whereby for data anticipated to be of high-dimensionality sparse data may have lower dimensionality;

whereby a market segment may be well defined and its sub-segments known, so that the requirements of each market would be known for the present and past horizons, but the segments and requirements for a future of 50 years would be difficult to obtain, yet the use of the present numbers as a well understood surrogate for the 20 year horizon would be considered reasonable, yet sparse;

whereby projecting into the future requires the reliance on sparse data, but over time that sparse data will be filled out and the same modeling equations will produce better results, such that a prediction of a ten year horizon will improve when re-predicted in five years because the five years will see the improvement in the sparse data used;

whereby intelligence makes use of these sorts of meta-facts because the veracity of their information is always suspect; and

whereby use of sparse data encapsulated by a fxxt can more effectively be managed.

290. The method of claim 1 to also find values of positioning latent variables of meaning in subjective perspective in multi-concept organization in a specific use case, further including:

a. accepting a map definition from a user including specifying at least one fxxt holding votes entered by said user, said fxxt given a non-zero weighting coefficient indicating a proportionality of impact sufficient to cause the votes of the user to be influential on the resulting positions of at least one info-item;

b. generating a map instance from said map definition according to map generation means, wherein;

i. extracting at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means, wherein said organization of knowledge of at least one domain of wisdom includes information from said at least one fxxt holding votes entered by said user;

ii. generating, using said map definition specifying at least one fxxt holding votes entered by said user, a skeletal structure for a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map skeletal structure of said map instance is based upon a manner of analysis selected from the group of;

a spanning forest manner, a descendent forest manner, an enhanced descendent forest manner, an ascendant forest manner, an enhanced ascendant forest manner, and a structure comprising a combination thereof;

iii. generating, using said map definition specifying at least one fxxt holding votes entered by said user, one or more organizations of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly selected from the group of;

a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, a directed graph manner, a graph manner, a horizontal manner, a depth augmented manner, a time augmented manner, a purlieu augmented manner, and a structure comprising a combination thereof;

wherein vertical and horizontal are mere duals for labeling in combinations;

iv. determining from the policies of the map definition the basis for calculating roll-ups, utilizing re-inverted sense or un-inverted generated hierarchical tensors from tree-extraction to prepare for roll-up to ensure that the root is considered as top and leaves are at the bottom logically;

v. generating roll-up tensors;

vi. determining from the policies of the map definition the basis for positioning;

and

vii. generating positioning for domain of wisdom member cnxpts according to process trees for organization of knowledge generation, position determination and final sizing means for calculation, based upon policies stated in the map definition, wherein said positionings of said cnxpts are computed;

c. providing to the user said one or more domains of wisdom for utilization in a form selected from the group of;

i. providing access to the data contained in said one or more organizations of knowledge for one or more domains of wisdom of said map instance for utilization directed at a solution of a problem the user is considering;

and

ii. displaying a visual derivative of said one or more organizations of knowledge for one or more domains of wisdom of said map instance to said user;

and

d. accepting user commands for adding and refining said commonplace;

whereby the positions generated for cnxpts express an organization of knowledge entirely based upon the purpose of the map, that being often a categorization or a precedence;

whereby the solutions for the positions express a solution of a set of unknowns that have not been observed although the data underlying the positions may have been entered as supervision by users;

whereby the the solutions for the positions are inferred from observed values comprising inputs from data collections, modeling, a crowd, or especially from a specific user, but are often not directly determinable;

whereby the the solutions for the positions are often inferred from unobserved values comprising inputs from random factors, surrogate relationships and commonalities;

sketchy modeling data, sketchy or low veracity crowd perceptions, or wild guesses from a specific user, these inputs useful where other inputs are lacking; and

whereby the positions express the subjective perceptions of the user.

291. The method of claim 1 to also find values of positioning latent variables of meaning in objective perspective in multi-concept organization in a specific use case, further including:

a. accepting a map definition from a user specifying, if at all, a fxxt holding votes entered by said user if said fxxt is given a weighting coefficient indicating a proportionality of impact sufficiently low so to cause the votes of the user to be no more influential than would be a vote by any other user if any other user had entered a vote on the resulting position of that info-item;

b. generating a map instance from said map definition according to map generation means, wherein;

i. extracting at least one consensus organization of knowledge of at least one domain of wisdom from said commonplace according to utilize collective consensus through vote tallying means;

ii. generating, using said map definition, a skeletal structure for a map instance;

iii. generating, using said map definition, one or more organizations of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly selected from the group of;

a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, a directed graph manner, a graph manner, a horizontal manner, a depth augmented manner, a time augmented manner, a purlieu augmented manner, and a structure comprising a combination thereof;

wherein vertical and horizontal are mere duals for labeling in combinations;

iv. determining from the policies of the map definition the basis for calculating roll-ups, utilizing re-inverted sense or un-inverted generated hierarchical tensors from tree-extraction to prepare for roll-up to ensure that the root is considered as top and leaves are at the bottom logically;

v. generating roll-up tensors;

vi. determining from the policies of the map definition the basis for positioning;

and

vii. generating positioning for domain of wisdom member cnxpts according to process trees for organization of knowledge generation, position determination and final sizing means for calculation, based upon policies stated in the map definition, wherein said positionings of said cnxpts are computed;

c. providing to the user said one or more domains of wisdom for utilization in a form selected from the group of;

i. providing access to the data contained in said one or more organizations of knowledge for one or more domains of wisdom of said map instance for utilization directed at a solution of a problem the user is considering;

and

ii. displaying a visual derivative of said one or more organizations of knowledge for one or more domains of wisdom of said map instance to said user;

and

d. accepting user commands for adding and refining said commonplace;

whereby the positions generated for cnxpts express an organization of knowledge entirely based upon the purpose of the map, that being often a categorization or a precedence;

whereby the solutions for the positions express a solution of a set of unknowns that have not been observed although the data underlying the positions may have been entered as supervision by users;

whereby the the solutions for the positions are inferred from observed values comprising inputs from data collections, modeling, a crowd, or from a specific user, but are often not directly determinable;

whereby the the solutions for the positions are often inferred from unobserved values comprising inputs from random factors, surrogate relationships and commonalities;

sketchy modeling data, sketchy or low veracity crowd perceptions, or wild guesses from users, these inputs useful where other inputs are lacking;

whereby the positions express the objective truth; and

whereby the positions express latent variable values possibly limited in dimensionality by the map definition.

292. The method of claim 1, to predict in models where basis information is sparse, further including:

a. combining types of concepts represented by surrogate cnxpts and relationships represented by surrogate associations, each of which are to a less than complete degree correlated to a probative relationship in a model, even though some of the surrogate concepts and relationships would not be used in the map in a situation where the better probative information was available, wherein;

i. accepting a definition of a knowledge model comprising a set of one or more fxxts based on information stored that is probative to a purpose, the information stored comprising a plurality of cnxpts and a plurality of associations, a plurality of cnxpts and a plurality of associations marked with at least one fxxt of said set of one or more fxxts based on probative information stored;

ii. accepting an augmentation of the definition of the knowledge model comprising surrogate information, the surrogate information thought to be correlated to the probative information of one or more fxxts;

the probative information missing, unreliable, or sparse, and the surrogate information a stopgap until the probative knowledge model becomes sufficiently complete, the surrogate information comprising an additional surrogate set of one or more fxxts, the information stored comprising zero or more cnxpts and zero or more associations, the surrogate information selected from the group of;

01. surrogate associations that are not probative but are thought to be correlated to probative associations of one or more fxxts, each association relating a total of two cnxpts comprising zero to two probative final cnxpts and zero to two surrogate placeholders substituting for a probative final cnxpt, each association analogous to a temporary bridge constructed to allow traffic between one side of a river to the other even if not connected at the substantial abutments where the permanent bridge would be;

02. surrogate cnxpts that are each a placeholder for a final statement object explaining a concept, the surrogate cnxpt as placeholder believed to be incomplete in description or modeling specification, the existence of the surrogate cnxpt as placeholder dubious although the existence as a representative of a different cnxpt sustainable just as a spare tire is known not to be appropriate for long term use but is still a tire that will work, the modeling structure of the surrogate cnxpt believed to be a close fit to that of the cnxpt for which it is a placeholder;

iii. accepting a map definition specifying use of said a set of one or more fxxts based on information stored that is probative to a purpose and the surrogate set of one or more fxxts;

iv. assigning to each first fxxt of the set of one or more fxxts based on information stored that is probative a weighting coefficient indicating a proportionality of impact prioritizing their use higher than the corresponding fxxt of the additional surrogate set of one or more fxxts;

v. generating, using a map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to zero or more associations and zero or more cnxpts into the derived ontology, summing the information in various fxxts as adjusted by the weighting coefficient indicating a proportionality of impact for each fxxt so that, for any hierarchical association between the same two cnxpts a single representative hierarchical association is obtained, and so that, after map structuring, for any association between the same two cnxpts a single representative affinitive association is obtained and a single value of each property of each cnxpt is obtained;

vi. generating, using said map definition referencing the set of zero or more fxxts, a skeletal structure for a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map skeletal structure of said map instance is based upon choices of hierarchical associations based upon their summed weight, choosing a probative association over a surrogate for structuring the skeleton as soon as enough evidence appears that the probative association is usable, the comparison of hierarchical associations not necessarily regarding a comparison of a probative association and its stopgap replacement so that in analogue the comparison is like enabling a new road from a detour so that as a new section of the new road is completed a slower detour route is abandoned in each different leg of a new road being built as different projects;

generating, using said map referencing the set of zero or more fxxts, one or more organizations of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly;

and

i. providing to the user said one or more domains of wisdom for utilization.

293. The method of claim 1 to also provide referencing of values of cnxpt properties in a map from another map for modeling, further including:

a. accepting a map definition for a first map, said first map involving at least one first cnxpt class or first cnxpt instance;

b. accepting a map definition for a second map, said second map involving at least one second cnxpt class or second cnxpt instance;

c. defining a cnxpt equation in a first property of said first cnxpt class or said first cnxpt instance in said first map, the equation referencing a value from a property of one or more said second cnxpts in one or more said second maps to determine a value for said first property of an instance of said first cnxpt class or said first property of said first cnxpt instance;

d. generating said first map;

e. generating said second map;

f. resolving the equations of said first property of said first cnxpt class or said first cnxpt instance in said first map;

whereby modeling of a map having cnxpts referencing cnxpts in a second map may impute values from the current condition of the second map for use in determining results in the first map.

294. The method of claim 293, to predict the value of a technology, further including:

a. performing value analysis for a first tcept in a first map based upon the competitive share of value computed for each zero or more second appcept representing a market in a second map, wherein a competitive share is based upon the probable satisfying of the market represented by said second appcept by said first tcept.

295. The method of claim 1, to generate a list of investment opportunities due to market gaps, further including:

a. generating a list of technology function cntexxts each represented by a first cnxpt having a set of zero or more offshoot second tcepts representing a newer function than said first cnxpt where the predicted market value for said cntexxt represented by a first cnxpt is greater than the sum of the competitive values imputed to said set of zero or more offshoot second tcepts for a given target time horizon.

296. The method of claim 1, to generate a list of possible technologies not as yet defined, further including:

a. applying an automatic technique for analysis and ingesting of external information sources, wherein;

i. accepting a definition of a knowledge model comprising a set of one or more fxxts based on information stored regarding technologies and markets, the information stored comprising a plurality of cnxpts and a plurality of associations;

ii. accepting a map definition specifying use of said set of one or more fxxts based on information stored regarding techniques and markets, the map definition specifying that the map instances generated from it will be one forest of technologies and a second forest of application of technologies, each of a hierarchical manner and each of a time augmented manner;

and

iii. generating, using said map definition, a map instance;

and

b. generating a list of technology function cntexxts each represented by a first cnxpt having a set of zero or more offshoot second tcepts each representing a newer function than the encompassing said first cnxpt representing a cntexxt where the predicted market value for said cntexxt represented by a first cnxpt is greater than or equal to the sum of the competitive values imputed to said set of zero or more offshoot second tcepts for a given target time horizon;

whereby a list of technology definitions is created automatically for review.

297. The method of claim 1 to also link a prediction to a transaction, further including:

a. linking a prediction value to a first property of a cnxpt representing value of a a consortium to use in structuring consortium transaction and establishing a cnxpt property with an equation to sum the first property values of each investment, by investment percentage, to a property of a cnxpt representing a consortium owner to show rights during negotiation.

298. The method of claim 1, to determine the irrationality of a user regarding a set of similar beliefs, further including:

a. detecting a multimodal distribution for the distribution of votes over time of a single user regarding the veracity of a set of cnxpts that represent similar beliefs, wherein;

i. computing the degree of multimodality for votes by a first user for each second cnxpt in a cntexxt represented by a first cnxpt by determining the degree to which the distribution for said votes is other than unimodal;

and

ii. determining if said degree of multimodality is greater than a pre-specified value.

299. The method of claim 1, to determine the level of disagreement between users regarding a belief, further including:

a. detecting a multimodal distribution for the distribution of votes over time of a set of users regarding the veracity of a set of cnxpts that represent similar beliefs, wherein;

i. computing the degree of multimodality for votes by a plurality of users for a first cnxpt by determining the degree to which the distribution for said votes is other than unimodal;

and

ii. determining if said degree of multimodality is greater than a pre-specified value.

300. The method of claim 1 to also provide hierarchical admixture model for topic modeling, further including:

a. accepting a definition of a map with multiple fxxts and cnxpts having modeling cells;

b. specifying an admixture coefficient for each fxxt as a weighting coefficient indicating a proportionality of impact of a fxxt in the map instance;

c. generating a map instance having a model from the map definition;

and

d. computing the model results;

whereby the map instance generated presents cnxpts serving as binding points and class instances having structure useful for modeling, the structure established based upon the contents of the fxxts and influenced strongly or weakly by the admixture ensemble coefficients.

301. The method of claim 1 to also provide ensembling of evidence, further including:

a. accepting a definition of a map with multiple fxxts, wherein evidence is an occurrence of one or more cnxpts referenced in one or more fxxts;

wherein one or more fxxts stem from a situation selected from the group of;

i. fxxt formed to indicate associations relating cnxpt pairs with evidence connected in common to the cnxpt pair members;

ii. fxxt formed to indicate associations relating cnxpt pairs where evidence connected to the first cnxpt pair member and evidence connected to the second cnxpt pair member show a reason to believe that the two members are related;

iii. fxxt formed by machine learning showing relationship between two or more cnxpts;

iv. fxxt formed by machine learning showing importance of one or more cnxpts;

v. fxxt formed to indicate cnxpts whose veracity is high based upon the evidence connected to the cnxpt;

and

vi. fxxt formed to indicate importance of a cnxpt based upon relevance of evidence connected to the cnxpt;

b. specifying an admixture coefficient for each fxxt as a weighting coefficient indicating a proportionality of impact of a fxxt in the map;

and

c. generating the map instance having evidence as an occurrence of one or more cnxpts;

whereby the map generated presents cnxpts supported by varying strengths of evidence such that modeling can assemble evidence based upon the structure of the map instance.

302. the method of claim 1 to also provide document import, further including:

a. generating into said commonplace info-items representing documents from external sources, the info-items indicating details of documents as source objects according to import collateral information resource means;

b. updating said commonplace by generating information from source objects according to enter information resource for a ttx, and execute document cross-citation analytic means;

c. ingesting the information from each source object for determining ttx information for generation of derived source objects represented by zero or more new ttx info-items into said commonplace according to relevance based relationship building, result set collateral information resource import, and retrieve import from analytic and convert means;

d. dissecting the imported document derived source objects to obtain concepts form each derived source object suggesting a meaning more clarified from said ingesting;

e. adding from each said derived source object suggesting a meaning a new cnxpt as a binding point info-item;

f. determining relevance of each concept of said derived source object represented by a cnxpt according to utilize collective consensus through vote tallying means to obtain result set items for create unstructured data query script step means during result set processes means where a query was used to spur the import and ingesting of said derived source object according to perform query means, execute hit importance ranking analytic, generate scanning hit review queue entry, and result set conversion to properties, occurrences, and categorizations means;

whereby document information is imported into the commonplace.