SYSTEM AND METHOD FOR FUZZY CONCEPT MAPPING, VOTING ONTOLOGY CROWD SOURCING, AND TECHNOLOGY PREDICTION

• US 20170235848A1
• Filed: 09/13/2016
• Published: 08/17/2017
• Est. Priority Date: 08/29/2012
• Status: Active Grant

• Current Assignee: Dennis Van Dusen, John A. Wise
• Original Assignee: Dennis Van Dusen, John A. Wise
• Inventors: Van Dusen, Dennis, Wise, John A.
• Granted Patent: US 11,080,336 B2
• Time in Patent Office: Days
• 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

13. (canceled)

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

a. providing a computer storage to store a commonplace of information comprising a plurality of cnxpts and relationships among the plurality of cnxpts;

b. defining a knowledge model comprising a set of fxxts based on information stored within the plurality of cnxpts and the relationships, fulfilling at least one condition selected from the group consisting of;

at least one cnxpt is associated with at least one fxxt, and, at least one cnxpt participates in a relationship associated with at least one fxxt;

c. generating, using a set of fxxts, a visualization map for a domain of wisdom comprising an organization of knowledge of cnxpts connected with each other via relationships in one of a hierarchical manner, a directed graph manner, a graph manner, or a structure comprising a combination thereof; and

d. displaying a visual representation of the visualization map to the user;

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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

1. The method of claim 16, to empower users to obtain knowledge by participating in a wisdom of crowds crowdsourcing process where concepts are assembled into a commonplace of information having improving depth and quality, comprising:

a. providing a system and software for empowering users to obtain knowledge by participating in a wisdom of crowds crowdsourcing process where concepts are assembled into a commonplace of information having improving depth and quality, having;

i. a commonplace of information means containing a plurality of info-items;

ii. one or more computers with server functions for holding said commonplace of information;

iii. one or more computers with server functions for managing said commonplace of information;

iv. server system software for commanding functionality of at least one operating system, database, file manager, internet request responder server, data delivery server, page content generator, interpreter, specialized content generator, document manager, external document manager interconnection, external internet server interconnection, and zero or more devices attached to said computers with server functions;

v. one or more computers hosting workbench functions for providing workbench users access to said commonplace;

vi. workbench system software for managing said workbench functions and invoking server application functions at the request of said workbench functions;

vii. communications management software executing in said computers with server functions for managing said commonplace of information for distributing information and collecting information to be added to said commonplace;

viii. communications management software executing in said one or more computers hosting workbench functions to control those computer'"'"'s communication connection, synchronization, and transfer of information with said computers with server functions for managing said commonplace of information;

ix. server application software executing on said computer servers for managing the distributing of information content derived from said commonplace to said one or more computers hosting workbench functions through said attached devices;

x. workbench application software executing on said one or more computers hosting workbench functions managing the local computing and storage of said one or more computers hosting workbench functions to present a local version of said content through a user interface to said user and to accept user commands;

xi. distributed application software executing in part on one or more said servers and in part on said one or more computers hosting workbench functions;

xii. workbench application software executing on said one or more computers hosting workbench functions managing the local graphics processor of said one or more computers hosting workbench functions to present a local, visible representation resulting from said content through a user interface to said user and to accept user navigation or information alteration commands;

xiii. server system software for initiation of the managing of said server functions, said database functions, and said attached devices of said computers with server functions for managing said commonplace of information;

xiv. server system software for managing said commonplace and the organization of said commonplace information when distributed to said computers with server functions;

xv. server system software for initiation of said communications management functions on each of said one or more computers hosting workbench functions to control those computer'"'"'s communication connection, synchronization, and transfer of information with said computers with server functions for managing said commonplace of information;

xvi. application software for local or distributed processes for managing said user interface functions at said workstations and performing user requested actions;

xvii. application software for utilize collective consensus through vote tallying functions to calculate consensus and impute associations;

xviii. application software for map generation functions for performing categorization within and generating maps from said commonplace by;

01. a fxxt extraction;

02. a structure generation selected from the group consisting of;

forest extraction;

tree extraction; and

graph extraction; and

03. a positioning of cnxpts;

xix. server system software for initiation of the server application software executing on said computer servers for managing the distributing of information content derived from said commonplace to said one or more computers hosting workbench functions through said attached devices;

xx. application software on said computers hosting workbench functions for said degree of control over participation by said user;

xxi. application software on said computers hosting workbench functions for said degree of control over access, the control selected from the group consisting of;

general access, controlled access while establishing protection for said idea, granting right to publish said idea, granting access to project team members involved with applying said idea, and access to obtain legal protection for said idea if previously unknown in the art;

b. allowing user access to said commonplace of information;

whereby said user is empowered to;

see what ideas have been categorized into said commonplace, add to said commonplace known and newly conceived ideas, categories, and categorizations, add meta-data about said ideas, categories, and categorizations, vote on the categorization of said ideas and categories, incrementally add said newly conceived ideas according to immediate creativity capture, add information to existing ideas or categories, harmonize categorizations, state and apply steps to alter and filter data to generate categorizations, associatively search the categorized ideas on a map user interface, plug in additional application functionality, invoke application functions on said workbench, invoke application functions executing on said server from said workbench as workbench functions, view categorizations dynamically altered by the wisdom of crowds consensus, view categorized ideas dynamically altered by the wisdom of crowds consensus, reduce innovation inefficiencies through information reuse, share analysis, participate in crowdsourcing to collect the wisdom of crowds, and participate in said marketplaces, and where information regarding interest in said ideas, said idea'"'"'s value and the appropriateness of the idea for application specific situations may be offered by the provider of the service, where a service provider may, if permitted by service agreement, collect, track, and mine the demographic characteristics of said users to allow reporting on user interest or expertise, and where a service provider may, if permitted by service agreement, collect, track, and mine the demographic characteristics of organizations to allow reporting on entity progress, reliability, risk, and value.

2. The method of claim 16, to make available to a user a stigmergic commonplace of information, comprising:

a. providing a computer storage to store a commonplace of information comprising a domain of wisdom comprised of a plurality of cnxpts and relationships among the plurality of cnxpts without regard to any ordering or structure outside of the meaning of a relationship with optional directionality, each relationship between a pair of cnxpts optionally including a stated weight indicating a strength of the relationship between the pair of cnxpts such that a predefined default value is assumed for weights not stated;

b. accepting as a definition of a knowledge model a set of at least one fxxt marking information stored within the plurality of cnxpts and the relationships, each fxxt in said set having a coefficient, defaulting to 1, indicating a proportionality of impact of the fxxt on any result of analysis regarding the knowledge model;

c. generating, using said set of at least one fxxt making up a knowledge model, the coefficient indicating proportionality of impact of each member of said set of at least one fxxt, the weighted relationships between cnxpts that are marked by one or more of each member of said set of at least one fxxt, and the optionally weighted cnxpts that are marked by one or more of each member of said set of at least one fxxt, a map for the domain of wisdom comprising a forest structure of cnxpts connected by relationships in a hierarchical manner where such relationships are available and chosen by priority order from the set of said weighted relationships between cnxpts that are marked by one or more of each member of said set of at least one fxxt; and

d. optionally displaying a visual representation of the map to the user.

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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

3. The method of claim 2, wherein generating the map comprises identifying at least one initial cnxpt for the structuring based on the weighting coefficients assigned to the members of the set of fxxts and the weights of the relationships of the relationships and cnxpts marked by said set of fxxts.

4. The method of claim 3, wherein generating the map further comprises designating a relationship to connect in the map a parent and a child such that said relationship exists in the set of relationships and cnxpts marked by said set of fxxts and has as an end a parent cnxpt in a set of cnxpts not having the child cnxpt of the relationship as a member.

5. The method of claim 2, wherein generating the map further comprises applying the weighting coefficient assigned to a fxxt to the weights of the relationships associated with the fxxt by multiplication.

6. The method of claim 2, wherein generating the map further comprises applying the weighting coefficient assigned to a fxxt to the weights of the cnxpts associated with the fxxt.

7. The method of claim 5, wherein the relationships cnxpt has a relationship with a highest summarized weight according to the vote tallying means.

8. The method of claim 2, wherein generating the map comprises:

a. performing a roll-up analysis that analyzes, for each relationship of a cnxpt, a cumulative weighting selected from the group consisting of;

a weighting of a relationship the cnxpt has with an uncle of the cnxpt in the structure including weights inherited from ascendants and descendants of the cnxpt and weights inherited from ascendants and descendants of the uncle; and

a weighting of a relationship the cnxpt has with a sibling of the cnxpt in the structure including weights inherited from descendants of the cnxpt and weights inherited from descendants of the sibling; and

b. modifying, based on the roll-up analysis, a value within the map selected from the group consisting of;

the weight of a relationship, and the importance of a cnxpt.

9. The method of claim 2, to position cnxpts on a map being generated, further comprising:

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

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

parent cnxpt of the child cnxpt, an uncle cnxpt of the child cnxpt, and a sibling cnxpt of the child cnxpt; and

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

10. The method of claim 2 to improve quality of the generated map, further comprising:

a. deriving a consensus based on interactions of the generated map by the user; and

b. modifying the map based on the derived consensus.

11. The method of claim 2 to improve quality of the generated map as described by an exemplar, further comprising:

a. accepting an exemplar stating normative placement positions of cnxpts;

b. computing an error metric based upon the positions of generated map cnxpts relative to the normative placements; and

c. determining an alternative set of fxxt weighting coefficients such that a generated alternative map based upon the alternative set of fxxt weighting coefficients results in a value of the error metric based upon positions of generated map cnxpts relative to the normative placements to be lower;

12. The method of claim 10, further comprising modifying at least one of the subset of fxxts, the weights assigned to the subset of fxxts, the weights of the relationships, and a relationship between a cnxpt and a fxxt based on the derived consensus.

14. The method of claim 10, wherein the interactions comprise at least one of traversing the tree structure, re-positioning the cnxpts within the map, creating a new relationship between two cnxpts within the map, adding a cnxpt within the map, defining a new fxxt, and modifying a weight of a relationship within the map.

15. The method of claim 10, 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 consisting of:

changing the parent of a cnxpt;

creating a new relationship between two cnxpts within the map, adding a cnxpt within the map, and modifying a weight of a relationship within the map.

17. The method of claim 16, wherein each relationship between a pair of cnxpts in the commonplace includes a weight indicating a strength of the relationship between the pair of cnxpts, wherein generating the cmmv comprises generating the cmmv using the weights of the relationships between cnxpts that are associated with the subset of fxxts.

18. The method of claim 17, wherein generating the cmmv comprises generating the cmmv using a coefficient, stating the proportionality of impact of a fxxt, assigned by the user to at least one fxxt within the subset of selected fxxts.

19. The method of claim 18, wherein a different coefficient, stating the proportionality of impact of a fxxt, is assigned to a different fxxt within the subset of selected fxxts.

20. The method of claim 19, wherein generating the cmmv further comprises applying the coefficient assigned to a fxxt to the weights of the relationships associated with the fxxt to generate weighted relationships in the organization of knowledge.

21. The method of claim 19, wherein generating the cmmv further comprises tallying the weights of the relationships garnered from the subset of fxxts selected by a user to generate, without fxxt differentiating, weighted relationships in the organization of knowledge.

22. The method of claim 20, wherein the organization of knowledge comprises a tree structure of cnxpts and relationships.

23. The method of claim 20, wherein the organization of knowledge comprises a tree structure of cnxpts and highest weighted summarized relationships.

24. The method of claim 22, wherein generating the cmmv comprises:

a. ordering into a queue the summarized relationships derived from the relationships associated with at least one of the subset of selected fxxts by summarized relationship weight, greatest first;

b. designating the current front summarized relationship in the queue as a connecting relationship in the structure generated if said summarized relationship connects a cnxpt pair wherein no more than one cnxpt of said cnxpt pair had yet been added to said structure being generated;

c. removing the front summarized relationship from said queue;

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

25. The method of claim 22, wherein generating the cmmv comprises designating a cnxpt associated with at least one of the subset of selected fxxts as a root cnxpt for the tree structure.

26. The method of claim 23, wherein generating the cmmv further comprises designating a cnxpt that has an existing relationship with the root cnxpt as a child cnxpt of the root cnxpt.

27. The method of claim 23, wherein the root cnxpt has the highest cumulative weight of relationships.

28. The method of claim 20, wherein the organization of knowledge comprises a forest of trees structure of cnxpts and relationships.

29. The method of claim 20, wherein generating the cmmv comprises:

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

b. modifying the weights of the relationships within the cmmv based on the roll-up analysis.

30. The method of claim 20, wherein generating the cmmv further comprises computing a precedence directed acyclic graph from the summarized relationships

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

31. The method of claim 20, wherein generating the cmmv further comprises computing an activity diagram from the summarized relationships

whereby a graphical representation of a workflow of stepwise precedence ordered activities and actions allowing for choice of alternative activity or action, iterations of sets of activities, and concurrency of activities is produced.

32. The method of claim 20, further comprising:

a. deriving a consensus based on interactions of the generated cmmv by the user; and

b. modifying the cmmv based on the derived consensus.

33. The method of claim 32, further comprising modifying at least one of:

the subset of fxxts, the coefficients assigned to the subset of fxxts, the weights of the relationships, the importances of the cnxpts, the existences of the cnxpts, a marking of a cnxpt as being a part of a fxxt, and a marking of a relationship as being a part of a fxxt.

34. The method of claim 32, further comprising stating an opinion regarding at least one of:

the coefficients assigned to the subset of fxxts, the weights of the relationships, the importances of the cnxpts, the existences of the cnxpts, a marking of a cnxpt as being a part of a fxxt, and a marking of a relationship as being a part of a fxxt.

35. The method of claim 32, wherein the interactions comprise at least one of traversing the tree structure, re-positioning the cnxpts within the cmmv, creating a new relationship between two cnxpts within the cmmv, adding a cnxpt within the cmmv, defining a new fxxt, and modifying a weight of a relationship within the cmmv.

87. The method of claim 16, for providing ontology statistical analysis and modeling, comprising:

a. forming a plurality of set extraction specifications partitioning an ontology'"'"'s contents into either in or not in said set extraction;

b. accepting a structuring of an ontology as a basis for modeling by specifying a weighting coefficient for each said set extractions such that any such said set extraction is included into a model basis if the assigned coefficient is not zero;

c. extracting said set extractions of ontology components with non-zero coefficients into said model basis;

d. developing a structure from said model basis according to the weightings of said set extractions;

e. calculating a model result from said model basis;

f. accepting a normative result anticipated of the modeling;

g. computing an error metric for the differential between the modeling result of the structuring and the normative solution;

h. adjusting the coefficients assigning weighting to said set extractions to reduce said error metric such that a secondary model result is nearer to said normative result;

i. accepting said set of assigned coefficients as an acceptable set for a model to achieve a satisfactory predictive result;

88. The method of claim 16, for ensemble modeling related to concepts within a commonplace of information, comprising:

a. providing modeling tools fuzzy set based numerical analysis;

b. accepting a definition of a commonality determination rule stating an enrolling of a modeling tool for fuzzy set based numerical analysis tuned to operate on said commonplace and said categorizations produced according to applications software map generation means, and;

c. providing modeling tools for fuzzy set based numerical analysis tuned to operate on said commonplace and said categorizations produced by said applications software map generation means; and

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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

89. The computer-implemented method of claim 88, wherein each cnxpt additionally participates in said ensemble modeling as a computing object in an object-oriented paradigm, wherein the cnxpt has at least one internal construct chosen from the set consisting of:

an attribute, a property, a method variable, and a method result;

wherein the construct is assigned at least one value according to a specification of a type selected from the set consisting of;

a value primitive, a null, a default, a method result, an equation specification optionally referencing exposed constructs of cnxpts from the set consisting 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, and user specified parameters;

wherein specific cnxpt membership in a referenced set is optionally identified after generation of a structuring of a plurality of cnxpts from said commonplace of information.

90. The method of claim 16, for determining initial relevance score of a source object, comprising:

a. providing a computer storage to store a commonplace;

b. providing to users access to view, navigate and enter commands to interface with said commonplace;

c. establishing structural information defining a knowledge model for a domain of wisdom;

d. configuring the processor to determine a measure of similarity of concept pairs by generating imputed relationships between similar concepts represented by cnxpts;

e. configuring the processor to determine a measure of commonalities of features or properties of each concept of a concept pair by generating imputed relationships between such concepts represented by cnxpts;

f. configuring the processor to determine a measure of commonality of a first information resource represented by a first irxt and a second information resource represented by a second irxt by presence of a first item in said first information resource and by presence of a second item in said second information resource information, said items so juxtaposed indicating similarity to a quantifiable degree in said information, such that an imputed relationship info-item is generated between said first and said second irxts with a predetermined type and a strength based upon the value given by said being similar to a quantifiable degree, said first item and a mere example of said second each of a type selected from the group consisting of;

provenance indicator, location found, coding key, object meta-data field, 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, finding, 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 whether or not represented by a cnxpt, context whether or not represented by a cnxpt, classification category whether or not represented by a cnxpt, meta-data value, other description, and a topical element;

g. configuring the processor to determine a measure of commonality of a first concept and a second concept of a concept pair by presence of a first irxt related by an occurrence of said first concept represented by a first cnxpt and by presence of a second irxt related by an occurrence of said second concept represented by a second cnxpt, said first irxt related by a relationship info-item of a type predetermined to indicate similarity to a quantifiable degree given by the strength of said relationship info-item, such that an imputed relationship info-item is generated between said first and said second concepts represented by said first and said second cnxpts with a predetermined type and a strength based upon the value given by said being similar to a quantifiable degree;

h. configuring the processor to determine a measure of commonality of a first concept and a second concept of a concept pair by presence of a first item in information related by an occurrence of said first concept represented by a first cnxpt and by presence of a second item in information related by an occurrence of said second concept represented by a second cnxpt, said items so juxtaposed indicating similarity to a quantifiable degree in said information, such that an imputed relationship info-item is generated between said first and said second concepts represented by said first and said second cnxpts with a predetermined type and a strength based upon the value given by said being similar to a quantifiable degree, said first item and a mere example of said second each of a type selected from the group consisting of;

provenance indicator, location found, coding key, object meta-data field, 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, finding, 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 whether or not represented by a cnxpt, context whether or not represented by a cnxpt, classification category whether or not represented by a cnxpt, meta-data value, other description, and a topical element;

i. configuring the processor to determine a measure of commonality of a first concept and a second concept of a concept pair by shared location in a structure related by an occurrence of said first concept represented by a first cnxpt and by an occurrence of said second concept represented by a second cnxpt and to generate an imputed relationship info-item between said first and said second concepts represented by said first and said second cnxpts with a predetermined type and a strength based upon distance apart in said structure wherein siblings are given a highest strength;

j. accepting, previously, a set of objects suggesting meaning considered previously;

k. accepting, previously, opinions regarding the relevance of said object suggesting meaning considered previously against at least one cnxpt, said curation opinion termed a vote, the degree of relevance determined by a predetermined weighting calculated from the vote weight times the accuracy level found for said user from previous voting, said accuracy level termed the authority level of said user;

l. configuring, previously, the processor to determine a result set ranked relevance set cluster of items relevant to a concept from opinions previously expressed regarding the relevance of said items to said concept during culling of a plurality of result sets associated with said concept, each opinion causing a vote, each vote stating a measure of relevance of a previously culled result set item to a cnxpt representing a concept or context based upon a coefficient predetermined for the user stating the opinion and a metric for result set item culling outcomes, such that a relevance improvement metric causes a proportionally higher relevance score, a mere example of said improvement metric selected from the group consisting of;

item saved by user, item cited by user, item added to result set manually, item relevance value stated by user, item marked as relevant, number of views of item initiated from result set view, total length of all views of item initiated from result set view, number of times seen as result of search in said organization of knowledge, number of users entering an opinion regarding the result set item relevance, number of times item selected for navigation, number of views within a recent period, number of views within a stated period, whether a search goal holding said result set was resolved as a proper cntexxt satisfying the search goal criteria, and whether a cntexxt sought for a search goal holding said result set was not found but its appropriate parent category was found;

such that a relevance diminishment metric causes a proportionally lower relevance score, a mere example of said diminishment metric selected from the group consisting of;

item viewed but not marked relevant, item abandoned and not viewed, age of last view, item rejected by user, item deleted by user, and whether a goal was abandoned;

each vote regarding relevance to be added to said result set item for said cnxpt and for the user performing the culling optionally adjusting for or reflecting the expertise of said user, wherein an authoritative deletion command causes a value representing not relevant no matter when entered and will override any prior command for said document, a user marking of a quantitative relevance score overrides other scoring, and a navigation command of itself causes no change in the relevance score;

m. configuring the processor to determine a consensus cluster of previously ingested items relevant to a concept represented by a cnxpt from votes stating opinions regarding result set item relevance, information resources represented by irxts connected to said cnxpt by an occurrence, and structuring from imputed relationship info-items, stated relationship info-item from votes, resolution of concept integration, and all other relationship info-items affecting a structuring of cnxpts representing concepts, or any result of an action causing cnxpt positioning, and alterations of occurrences based upon differentiation improvement analytics in any organization of knowledge, such that the information resources represented by irxts related as occurrences to said cnxpt form a resolved cluster for said concept represented by said cnxpt without regard to any organization of knowledge, the set of members of said resolved cluster for said cnxpt termed, at the time point of use, a weighted seed set of objects for said cnxpt whether or not so determined for the purpose of defining a seed set and whether or not entered as a member of a seed set;

n. configuring the processor to determine a result set item importance as a trending sum of the count of votes ever registered for said result set item in said cnxpt against which the vote is cast plus a predefined value times the number of times the document was read plus a predefined value times the number of times the document was marked as highly relevant or important by a user;

o. configuring the processor to determine the shared praxis for each said cnxpt for the level of an organization of knowledge used heavily by users said shared praxis a trending measure of the standard deviation of the position calculated for said cnxpt based upon the segregated opinion of each highly interested individual user regarding said cnxpt, such that a distribution is formed to determine if the consensus regarding said cnxpt'"'"'s meaning is converging;

p. receiving a selection of at least one domain of wisdom and at least one organization of knowledge having at least one cnxpt, said organization of knowledge against which said source object suggesting a meaning is to be ranked, said organization of knowledge termed a comparison categorization, each cnxpt of said comparison categorization termed a basis concept represented by a basis cnxpt;

q. configuring a processor to retrieve said source object suggesting a meaning indicated as a result of a search;

r. performing a search resulting in plurality of members of a returned set of information each a source object suggesting a meaning such that the organization of such set is selected from the group consisting of;

list of items returned from a search, selection set returned from a Tindall, list of result records selected from a data set, the items listed in a result set previously generated, the list of the items in an area of consideration previously generated, the list of the items in an area of interest previously generated, the list of the items in a visualization selected, the list of the items in a visualization indicated, and the list of items returned from a query;

s. ingesting said returned set of information, wherein;

i. a provenance binding point source info-item is formed for said returned set of information found externally to the commonplace to allow for attachment of provenance property information to said binding point info-item, if said source info-item is not yet created for said returned set of information found;

ii. a structure binding point info-item is formed for said returned set of information to allow for attachment of structural property information to said binding point info-item, said binding point an irxt info-item, if not yet created;

iii. zero or one meaning binding point info-item is formed for said returned set of information to allow for attachment of identity indicator properties and meaning property information to said binding point info-item, said binding point consisting of a cnxpt info-item, if not yet created, 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 can or should be, do, appear, occur, involve, considered, known, perform, assembled, fit in, or participate, said binding point for attachment of purlieu characterizing the when, ordering, occurrence, gestation timeframe, existence timeframe, or duration said conceptual meaning can or should be relevant to, said cnxpt optionally to be retained only for the purpose of initial relevance generation;

t. ingesting one or more source object suggesting a meaning by converting each said member of said returned set of information to a result set item info-item in a result set of said commonplace, each result set item info-item representing a source object suggesting a meaning, to provide for said source object suggesting a meaning a binding point for relevance information against a plurality of basis cnxpts, wherein;

i. a structure binding point info-item, if not yet created, is formed for each source object suggesting a meaning to allow for attachment of structural property information to said binding point info-item, said binding point an irxt info-item, said binding point formed for a structure selected from the group consisting of;

an information resource, a row of a data set, a name value pair of a data set, a section of an information resource, and a structural component of a member of a returned set of information;

ii. a meaning binding point info-item is formed for each source object suggesting a meaning to allow for attachment of identity indicator properties and meaning property information to said binding point info-item, said binding point consisting of a cnxpt info-item, 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 can or should be, do, appear, occur, perform, assembled, fit in, or participate, said binding point for attachment of purlieu characterizing the when, ordering, or duration said conceptual meaning can or should be relevant to, said cnxpt optionally to be retained only for the purpose of initial relevance generation;

iii. ingesting each identifiable structural relationship found involving said member of said returned set of information and an irxt already in said commonplace by creating a relationship info-item of predetermined type and predetermined strength between the irxt of said member of said returned set of information and said irxt already in said commonplace;

u. dissecting, or accepting a dissection of, said source object suggesting a meaning into zero or more first derived source objects suggesting a meaning, wherein;

i. a structure binding point info-item, if not yet created, is formed for each first derived source object suggesting a meaning to allow for attachment of structural property information to said binding point info-item, said binding point an irxt info-item;

ii. a meaning binding point info-item is formed for each said first derived source object suggesting a meaning by converting said first derived source object'"'"'s properties to the format of a commonplace first cnxpt info-item of a predetermined type to allow for attachment of identity indicator properties and meaning property information to said binding point info-item, said binding point a dissection concept represented by a dissection cnxpt, 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 can or should be, do, appear, occur, perform, assembled, fit in, or participate, said binding point for attachment of purlieu characterizing the when, ordering, or duration said conceptual meaning can or should be relevant to, said first dissection cnxpt optionally to be retained only for the purpose of initial relevance generation, said binding point info-item to provide a binding point for relevance information against a plurality of basis cnxpts;

iii. ingesting each identifiable structural relationship found involving said first derived source object suggesting a meaning and an irxt already in said commonplace by creating a relationship info-item of predetermined type and predetermined strength between the irxt of said first derived source object suggesting a meaning and said irxt already in said commonplace;

v. ingesting each identifiable relationship found external to said commonplace involving said first source object suggesting a meaning and an identified entity represented by an info-item in said commonplace by creating a relationship info-item of predetermined type and predetermined strength between said first source object suggesting a meaning and said info-item representing said entity;

w. imputing a cnxpt to cnxpt relationship info-item of predetermined type and predetermined strength from each irxt to irxt relationship info-item ingested into said commonplace involving said first source object suggesting a meaning;

x. setting said result set item info-item creator to reference said user identifier;

y. setting said result set item info-item source to reference said its source info-item identifier;

z. assigning the reviewed property of each created result set item info-item in said result set to a value representing not yet reviewed;

aa. assigning the scopx property of each created result set item info-item in said result set to a value stemming from the language or scoping of the source of said member of said organized set of information;

bb. attaching an infxtypx to each created result set item info-item in said result set to a value for a category membership based upon the source of said member of said organized set of information;

cc. assigning the relevance strength of each created result set item info-item in said result set to a relevance rank obtained from said search if available or to a predetermined default value;

dd. setting other properties from the information returned from said search, findall, data set list, or query it stems from;

ee. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

ff. integrating said new dissection cnxpt into said commonplace by providing a default vote, with an authority level commensurate with the known quality of the source object it stems from, regarding the veracity of the meaning of the dissection concept;

gg. integrating, by executing zero or more commonality process and imputation process means analytics, said new dissection cnxpt 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 dissection cnxpt to the meaning of an existing cnxpt of even roughly similar type, said vote in the form of a new similarity relationship info-item of predetermined type between said new dissection cnxpt and said existing cnxpt;

whereby quality can be measured by a prediction correction mechanism as corrections in a crowd sourcing system that provides a categorization basis for newly added search results where consensus builds on the definition of a seed set that may be extremely nebulous at its inception, and other previously added search results to set an initial relevance and to direct the refinement of the relevance ranking by culling;

whereby due to the ability of the method in combination with commonality, fxxt extraction, consensus, and mapping means a series of different categorizations with a resulting combined relevance calculated will reflect a dispersal of information resource or ingested information across the set of cnxpts with relevance rankings consistent with the pertinence of said information resource or ingested information to a specific cnxpt;

whereby collecting and managing information resource indicators is beneficial;

whereby fine grained structuring of search results and search result parts may be relevance ranked and categorized on the basis of multiple categorization domains;

whereby provenance, creator, citations, source type, the search engine or database the rsxitem was found in, an estimate of veracity, source structure, a ranking from a meta-search engine, patterns in the metadata, thesauri, key concept elements, combination metrics, and actual document contents are used to create correlation criteria to determine relevance;

whereby prior culling sets increased levels of relevance recorded for those items selected, those abstracts read, those articles read extensively, those articles reacted to negatively, those visited, and lower relevance levels for those not viewed, dismissed, deleted;

whereby presence of duplicates in the result set will increase relevance;

whereby operations on information resources and database information during information retrieval query sessions assist to classify the information resources by query relevance to classify the information resources into categorical groupings, to extract categorization definitions from the information resources, to extract categorization relationships from the information resource information, or to perform other specialized operations within categorization procedures or query processing;

whereby concept based stigmergic approach augments content-based analytics and similarity to seed set and control samples to continually improve the value of expert determinations of relevance in an augmented computer learning process, reducing or eliminating the criticality of a seed set specification;

whereby rather than using a seed set as a sample of the document universe for comparison as with predictive coding, the wealth of tools available and improvements in categorization of several organizations from prior workflows are all applied progressively with human correction by various levels of subject matter expertise applied on a prioritized resource allocation basis to minimize the effect of the initial determinations made on any seed set to teach the analytic engine to predict categorizations for any added documents;

whereby the primary reference data is cumulative across predictive coding or curation projects;

whereby the language of the reference data is of less effect due to the conceptualization of meanings and conceptualization is cumulative across projects;

whereby the approach focuses the machine learning not on specific concepts highlighted by a subject matter expert but upon all concepts at summary or at great levels of specificity assembled cumulatively, and adaptively;

whereby in circumstances where relevance determination is needed to determine scoring responsive to specific issues or assertions such as to a specific legal theory, for applicability of attorney-client privilege, for study of technology at a specific timeframe or in a specific locale, the use of additional expert defined seed sets is not required;

whereby categorization is performed in parallel across many categorizations with relevance scoring varying accordingly and allowance of adaptive seed sets in each categorization;

whereby subjective relevancy information is collected and incorporated into an objective assessment, inferring from prior statements that something is less relevant because it is too general or older to create effective and accurate metrics so that the same basic correlation criteria can be used in a general way;

whereby data arguing can be applied for integrating concepts;

whereby quality improvement is possible for analytics and calculation formulas;

whereby data of all types may be categorized and used for initial relevance determination.

91. The method of claim 1, to provide an engagement platform in a wisdom of crowds process where concepts may be accessed, added, or refined in a commonplace of information, further comprising:

a. defining a cntexxt from a cnxpt on a conceptual level such that said cntexxt is but what appears to be a vessel for the meaning of the cnxpt;

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 the shape of an avatar;

d. displaying a plurality of cntexxts on the display;

e. displaying a structure generated on a basis selected from the group consisting 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 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;

h. arranging, in a structure generated according to a categorization, the cnxpts within a cntexxt according to the strength of similar of cnxpts including the cnxpts external to the cntexxt such that conceptually similar objects are in closer proximity than less similar objects;

i. arranging, in a structure generated according to a conditionality, dependence, or other directed graph basis, a first cnxpt in a position along an ordering line in a chosen aspect, the ordering implied by the directedness of the graph, with a second cnxpt wherein the second cnxpt is a subsequent cnxpt to the first cnxpt in the basis of the structuring;

j. simultaneously depicting in the rendering 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;

k. accepting navigation of and other user interaction commands related to the objects of the depictions displayed;

whereby users are empowered to add to and refine said content of said commonplace;

whereby said user entering a command will see his command take effect locally and his vote become authoritative, depending upon subscription level, for his work;

whereby votes may be collected to be considered in utilize collective consensus through vote tallying process means;

whereby context of a vote can be taken into consideration;

whereby expertise of a user can be taken into consideration and subscriptions can have differentiated value to customers;

whereby said user may explore new ideas and contribute their own concepts and defining how they are related to other ideas;

whereby available data sources and available categorization structures such as PTO classifications and fields of science indices may be tapped to provide content to said commonplace;

whereby documents rated as relevant to concepts provide hierarchical structuring relationships;

whereby the voting structure coordinates curation and allows sharing of responsibility and sharing of work product with a part of or the whole user community;

and whereby a wisdom of crowds result is formed.

92. The method of claim 91 further comprising:

a. wherein a first cnxpt is differentiated from a second cnxpt by a display trait selected from the group consisting of color, size, texture, avatar, position, shading, transparency, cntexxt membership, and labeling;

whereby users are made aware of differentiations between cnxpts.

93. The method of claim 91 further comprising:

a. depicting a relationships connecting a pair of a first cnxpt and a second cnxpt by presenting a display artifact indicating a relationship between a first cntexxt holding the first cnxpt and a second cntexxt holding the second cnxpt;

94. The method of claim 91 further comprising:

a. accepting and responding to a command selected from the group consisting of;

i. command to initiate display of different subject matter for generating a predetermined depiction;

ii. command to display information regarding a cntexxt;

iii. command to display information regarding a cnxpt;

iv. command to select a cntexxt for further action;

v. command to highlight on the display those cnxpts similar to a selected cnxpt in a predetermined measure of similarity;

vi. command to move a cnxpt;

vii. and

viii. command to display information regarding the relationship between a first cnxpt and a second cnxpt;

whereby users are made able to interact with cnxpts.

95. The method of claim 91 further comprising:

a. accepting and responding to a command selected from the group consisting of;

i. command to display a list of information resources relevant to a cnxpt;

ii. command to display an information resource relevant to a cnxpt;

iii. command to vote that an information resource is relevant to a cnxpt;

iv. command to vote that an information resource is not relevant to a cnxpt;

v. command to vote that an information resource should be added to the list of information resources relevant to a cnxpt;

vi. and

vii. command to vote that an information resource should be removed from the list of information resources relevant to a cnxpt;

whereby users are made able to interact with documents relevant to a cnxpt.

96. The method of claim 91 further comprising:

a. accepting and responding to a command selected from the group consisting 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 functions;

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 should be 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;

xv. and

xvi. command to initiate a what if modeling;

whereby users are made able to interact with properties of an info-item for modeling;

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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

97. The method of claim 91 further comprising:

a. dynamically re-rendering the display to adapt the displayed depiction to a change made to a cnxpt in the commonplace having an impact on the display;

whereby users are made aware of changes to a cnxpt.

98. The adding and refining said commonplace utilizing said collective consensus to populate said commonplace of improving scope and quality of claim 2, to curate added information, wherein in no set order:

a. accepting one or more commands from a user selected from the list of commands consisting 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 such that 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 should be altered such that;

01. a first cntexxt representing a concept represented internally by a cnxpt should be moved to show a closer or a more distant connection to a second concept as pertinent to and is to be so marked in the aspect of the map displayed as defined by the fxxt specification interpreted to produce said map;

02. a first cntexxt representing a concept represented internally by a cnxpt should be moved to show a closer or a more distant connection to a second concept in a specified relationship info-item and pertinent to and is to be so marked with zero or more specified fxxts;

03. a first cntexxt representing a concept represented internally by a cnxpt should be related by a relationship info-item to show first cntexxt as a child of a second cntexxt representing a concept represented internally by a cnxpt, the vote indicated and parent identified by dropping said first cntexxt onto said second cntexxt wherein said parent-child relationship info-item is pertinent to and is to be so marked in the aspect of the map displayed as defined by the fxxt specification interpreted to produce said map;

04. a first cntexxt representing a concept represented internally by a cnxpt should be related by a relationship info-item to show first cntexxt as a child of a second cntexxt representing a concept represented internally by a cnxpt, the vote indicated and parent identified by dropping said first cntexxt onto said second cntexxt wherein said parent-child relationship info-item is pertinent to and is to be so marked with zero or more specified fxxts;

05. a first cntexxt representing a concept represented internally by a cnxpt should be related by a relationship info-item of specified type to show first cntexxt as a second endpoint of said relationship info-item and a second cntexxt representing a concept represented internally by a cnxpt should be a first endpoint of said relationship, the vote indicated and second cnxpt identified by dropping said first cntexxt onto said second cntexxt wherein said relationship info-item is pertinent to and is to be so marked in the aspect of the map displayed as defined by the fxxt specification interpreted to produce said map;

06. a first cntexxt representing a concept represented internally by a cnxpt should be related by a relationship info-item of specified type to show first cntexxt as a second endpoint of said relationship info-item and a second cntexxt representing a concept represented internally by a cnxpt should be a first endpoint of said relationship, the vote indicated and second cnxpt identified by dropping said first cntexxt onto said second cntexxt wherein said relationship info-item is pertinent to and is to be so marked with zero or more specified fxxts;

07. a first cnxpt having a characteristic with specific value such that said value is pertinent to and is to be so marked with zero or more specified fxxts;

08. a first cnxpt having a specific trait such that said trait is pertinent to and is to be so marked with zero or more specified fxxts;

09. a first cnxpt having a specific purlieu such that said purlieu is pertinent to and is to be so marked with zero or more specified fxxts;

10. a first cnxpt having an occurrence with a specific information resource or internal resource serving as an information resource such that said occurrence is pertinent to and is to be so marked with zero or more specified fxxts;

11. a first cnxpt should or should not be marked as pertinent to a specified fxxt;

12. a first cnxpt should not have a characteristic such that said characteristic is pertinent to zero or more specified fxxts;

13. a first cnxpt should not have a trait such that said trait is pertinent to zero or more specified fxxts;

14. a first cnxpt should not have a purlieu such that said purlieu is pertinent to zero or more specified fxxts;

15. a first cnxpt should not have a occurrence such that said occurrence is pertinent to zero or more specified fxxts;

16. a first info-item instance should not exist in said commonplace;

17. a first cnxpt should not exist as pertinent to zero or more specified fxxts or generally if specified;

18. a first relationship info-item instance should not exist as pertinent to zero or more specified fxxts or generally if specified;

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;

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 such as people involved, time, institution, funding agency, application, industry of information resources;

n. determining commonalities for known information entered as characteristics such as people involved, time, institution, funding agency, application, industry of occurrences;

o. determining commonalities for known information entered as characteristics such as people involved, time, institution, funding agency, application, industry of cnxpts;

p. imputing commonality relationships according to generate commonality relationships process means for commonalities determined, marking each relationship info-item by a specified fxxt;

whereby users are empowered to add to and refine said content of said commonplace;

whereby said user entering a command will see his command take effect locally and his vote become authoritative, depending upon subscription level, for his work;

whereby votes may be collected to be considered in utilize collective consensus through vote tallying process means;

whereby context of a vote can be taken into consideration;

whereby expertise of a user can be taken into consideration and subscriptions can have differentiated value to customers;

whereby said user may explore new ideas and contribute their own concepts and defining how they are related to other ideas;

whereby available data sources and available categorization structures such as PTO classifications and fields of science indices may be tapped to provide content to said commonplace;

whereby documents rated as relevant to concepts provide hierarchical structuring relationships;

whereby the voting structure coordinates curation and allows sharing of responsibility and sharing of work product with a part of or the whole user community; and

whereby a wisdom of crowds result is formed.

99. The curation consensus of information 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. integrating closeness of semantic meaning of a second ttx instance to a first ttx instance already situated in a categorization by semantic meanings, comprising;

b. 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 relationship 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;

i. a ttx is more specific and included in the parent ttx;

ii. a tcept was invented later than its parent;

iii. a tcept was based upon a iv. a ttx was defined;

v. a ttx was entered as a query;

vi. a ttx was moved or pasted as a child of the parent;

vii. a ttx is somehow related to the parent;

viii. a ttx is caused to be related to another ttx;

ix. a ttx is similar or equivalent to another ttx;

c. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity to be between said instances of said cnxpt type;

d. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between cnxpts to have said single default fxxt during processing;

e. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

f. determining effective weights for summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

whereby entities are integrated.

100. The curation consensus of claim 1 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. providing curating application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

b. providing application software map generation means for performing categorization and generating maps;

c. providing application software display and delivery means for controlling presentations of results to users and accepting navigation and other user commands;

d. initiating execution of server application software executing on said computer servers for managing the distributing of information content derived from said commonplace to said one or more computers hosting workbench functions through said attached devices;

e. initiating execution of workbench application software on one or more of said one or more computers hosting workbench functions managing the local computing and storage of said one or more computers hosting workbench functions to present a local version of said content through a user interface to a user and to accept user commands;

f. establishing a commonplace into said computer storage;

g. loading of said commonplace with structural information defining a knowledge model;

h. granting access to said commonplace;

i. initiating execution of the means for managing user interface functions and performing automated tasks resulting from user actions;

initiating execution of continuous processing functions according to continuous processing process means;

k. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process 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;

l. initiating execution of the means for display and delivery of a visualization of said organization of knowledge of at least one domain of wisdom;

m. adding and refining said commonplace; and

n. utilizing said collective consensus;

whereby data originating from thousands to hundreds of millions of data sources rather than the typical few tens of data sources, with varying authorities and ownership, of multiple types and veracity pertaining to a wide scope of different subject matter of unsettled meaning in ways varying upon use case, quality rules, data, and schema are continuously evolving, the data and categorizations obtained from any manner of source or created by individual users at various stages of preparation but adjustable based upon crowd consensus, or generated as the interim categorizations and data collections created to service a user, are kept separate and useful, in new logical views of data within the context of each user'"'"'s use cases, in combinations in a predetermined sufficiency of efficiency, control, and protection with a set of tools with limited costly redundancy available for manual or automatic processing modes, for importing, curating by company, person or crowd, transforming, manipulating, searching, retrieving, analyzing, modeling, sharing, communicating, reaching decisions to agree or disagree about meanings and characteristics, reaching decisions agreeing or disagreeing about relationships and their strengths, integrating only where appropriate, visualizing, extracting, and exporting the data even at the user level of deployable solution development, while respecting varying user attitudes regarding reliability of data, being timely updateable asynchronously on an incremental basis by disparate sources, iteratively improved for quality, iteratively improving machine training and learning, available for use and interest tracking on predetermined data elements, all providing the reuse of work by others to reduce user costs, and providing a dynamic crowd assisted curation and data management platform for implementation of knowledge tools for specific application domains such as configuration management, issue management, software design and analysis, research curation, enterprise resource planning, financial modeling, causality and root-cause analysis, harmonization, classification management, product strategy development, product management, competitive analysis, predictive coding, e-discovery, document management, link analysis, link management, investment portfolio analysis, patent clearance, big data analysis, economic modeling, technology obsolescence analysis, and legal analysis.

101. The method of claim 5, wherein retaining of cnxpts in a fxxt extraction retains relatively more important cnxpts of a less important cnxpt type by applying a weighting coefficient function based also upon cnxpt strength to amplify diversity within a set of cnxpts marked by a fxxt.

102. The method of claim 5, wherein retaining of relationships in a fxxt extraction retains relatively more important relationships of a less important relationship type by applying a weighting coefficient function based also upon relationship strength to amplify diversity within a set of relationships marked by a fxxt.

103. The method of claim 8, wherein generating the map comprises:

a. 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;

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

c. forming an empty priority queue;

d. enqueuing 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;

e. 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;

f. 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;

g. 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;

h. 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;

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

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

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

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

whereby all uncle roll-up affinitive associations of a cnxpt with any single opposite end cnxpt from fxxt and forest extraction are combined into a single weighted value to-uncle attractor tensor, with either one or zero fxxts, and with at most one opposing end cnxpt identifier;

whereby all between-sibling-ring attractor-tensors from the ranking of inter-cnxpt relationship strengths based upon the sibling roll-up affinitive associations between siblings for the child cnxpts of each parent cnxpt in the fxxt being considered, and for the root cnxpts;

whereby all sibling roll-up affinitive association weights of a cnxpt with any single opposite end cnxpt into a single weighted value between-sibling-ring attractor tensor, with either one or zero fxxts, and with at most one opposing end cnxpt identifier;

whereby additional tensors are generated to force positions of sibling cnxpts to be nearer to related siblings than to unrelated siblings;

whereby the tensor strength for between-sibling-ring tractor tensors is to ensure that each cnxpt stays at an appropriate distance from its sibling cnxpts based upon the inter-sibling strengths.

104. The method of claim 103, wherein generating the map 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;

whereby tensors are created to force the ancestors of a cnxpt to be in positions such that the cnxpt itself is positioned inside the ancestor as well as being in the defined segment.

105. The method of claim 103, wherein generating the 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 such that the cnxpt itself is positioned inside the ancestor as well as being in the defined segment.

106. The method of claim 8, wherein generating a horizontal map with flows with respect to a vertical categorization forest hierarchy and at least one of precedence, flow order, conditionality, and defined map segmentation, further comprising:

a. generating, for hierarchical categorization force directed determination, affinitive association based positioning vectors, comprising;

i. 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;

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

iii. forming an empty priority queue;

iv. enqueuing 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;

v. 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;

vi. 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;

vii. 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;

viii. 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;

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

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

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

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

b. rolling up, for precedence aspect force directed position determination, flow hierarchical 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 set of markings consisting 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 where the intent was to complete as close as possible relative to the termination point; and

a negative would reflect a termination constraint where the intent was to complete as early as possible relative to the termination point;

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 would occupy a phase according to timing factor from the calculation of the technique, such that the earliest listed endpoint cnxpt or earliest predecessor endpoint cnxpt in any chain is assigned to the first phase;

marking the sequence number of the phase a first cnxpt belongs in as the depth of said first cnxpt such that the earliest phase has sequence number 0 and depth 0;

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 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, so as to attract said third cnxpt to the line perpendicular to the progression line of precedence;

vi. forming an empty priority queue;

vii. enqueuing 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;

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

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 map relative to a 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 set of markings consisting 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 its weight 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-basis list entries positioning precedence relation endpoint cnxpts according to a positioning function, wherein if either 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;

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

whereby tensors are created to force the ancestors of a cnxpt to be in positions such that the cnxpt itself is positioned inside the ancestor as well as being in the defined segment of a map.

107. The method of claim 106, wherein generating the 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 such that the cnxpt itself is positioned inside the ancestor as well as being in the defined segment.

108. The method of claim 9, to position cnxpts on a vertical forest map being generated, further comprising:

a. initializing fxxt specific ttx map data set of cnxpt centroid points;

b. deriving a position of a root cnxpt in an extracted forest of extracted trees of cnxpts based on tensors of the root cnxpt with other root cnxpts;

c. determining an error from a possible better position based upon factors chosen from the set consisting 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 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 consisting 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 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 such that a cnxpt is positioned inside its ancestor as well as being in the defined segment and closes to its uncles.

109. The method of claim 108, wherein generating the map comprises:

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

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

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

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

whereby error correction is prioritized to make position correction efficient by making corrections needed early on in the positioning process more obvious in a calculation of an error function.

110. The method of claim 106, to position cnxpts on a horizontal map with flows with respect to a vertical categorization forest hierarchy and at least one of precedence, flow order, conditionality, and defined map segmentation, further comprising:

a. determining the slice level in the vertical forest to be represented in the horizontal map if a slice level is set for the horizontal map;

b. determining, if a fixed slice level is specified, from the slice level in the vertical forest and a predetermined function stating the horizontal map position on the height access of the vertical map for a given level in the vertical forest, a position for the horizontal map plane;

c. determining, if no fixed slice level is specified, from a predetermined function stating the horizontal map position on the height access of the vertical map based upon a default, a position for the horizontal map plane;

d. initializing fxxt specific ttx map data set of cnxpt centroid points;

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, wherein the slice level is not at the root level for all roots, wherein;

i. determining an error from a possible better position based upon factors chosen from the set consisting of;

out of map distance, cnxpt sizing, cnxpt overlap, Euclidean distance from centroid of a root cnxpt to a prior position, Euclidean distance from centroid of a first root cnxpt to centroid of a second root cnxpt, Euclidean distance from centroid of a cnxpt to centroid of a constraint surrogate cnxpt, Euclidean distance from centroid of a root cnxpt to centroid of a representative fraction of the map canvas where cnxpt belongs;

f. for each next depth, process each cntexxt in the depth in turn in a bread first walk of the vertical map, in decreasing order of importance of a cnxpt of the depth to its vertical parent, wherein

i. determining an error from a possible better position based upon factors chosen from the set consisting 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 in the horizontal map plane from centroid of a first flow sibling cnxpt to centroid of a second flow sibling cnxpt if each flow sibling is at or above the vertical forest depth, Euclidean distance from centroid of an uncle to centroid of a child cnxpt, Euclidean distance in the horizontal map plane from centroid of a flow uncle to centroid of a flow child cnxpt if said flow uncle and said flow child are both at or above the vertical forest depth, Euclidean distance from centroid of a parent to centroid of a child cnxpt, Euclidean distance in the horizontal map plane from a predecessor cnxpt centroid to successor cnxpt if both at or above the vertical forest depth, 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 canvas where said cnxpt belongs if both at or above the vertical forest depth, such that if any moved cnxpt has ancestors in the vertical map and said move cnxpt is the most important cnxpt of its parent cnxpt the parent and all siblings of said parent are moved in a corresponding horizontal direction and distance;

ii. 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 consisting of;

parent cnxpt of the child cnxpt, an uncle cnxpt of the child cnxpt, a flow sibling cnxpt of the child cnxpt, a predecessor cnxpt, a flow sibling cnxpt of the child cnxpt;

a flow uncle cnxpt of the child cnxpt, a position constraint, and a constraint surrogate cnxpt;

g. modifying the map based on the positioning of the cnxpt; and

h. 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 such that a cnxpt is positioned inside its ancestor as well as being in the defined segment and closes to its uncles.

111. The forming a visualization of the categorization of claim 2 to also construct a visualization map, further including the following steps in the order named:

a. detailing a fxxt specification defining said categorization to perform and defining a map detailing one or more foci for said fxxt;

b. structuring said commonplace to extract content to said map;

c. interpreting said fxxt specification for said fxxt to extract said fxxt from said commonplace by marking cnxpts and associations as members of said fxxt;

d. choosing visualization structuring propositional hierarchical associations from said marked associations of said fxxt to form spanning trees by generating hierarchical tensors that point specifically to at most one parent cnxpt in said fxxt to generate descendant tree forest according to fxxt descendant tree extraction means for tree extraction;

e. generating cnxpt importance metadata for said fxxt member cnxpts according to bottom up importance summarization means for summarizing importance;

f. generating tensors according to process trees for affinitive tensor generation means for generation;

g. generating positioning for said fxxt member cnxpts according to process trees for visualization generation, position determination and final sizing means for calculating object positions for visualization; and

h. utilizing said map;

such that a visualizable virtual map is formed from said commonplace where classifications are derived from a relevant portion of said commonplace data, and said fxxt member cnxpts are positioned onto said visualization in position related to the closeness of the object to others logically according to the structure of said classifications as given by said tensors as derived from said associations and according to said fxxt specification and said object positions are adjusted to reduce conflicting positions;

whereby users may obtain subject matter maps for a specific purpose from a commonplace to more efficiently understand said contents of said commonplace and a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification and an extracted set of cnxpts to be positioned on said map in said visualization of said fxxt, said map produced has cnxpt members of said fxxt positioned in a taxonometric categorization of said fxxt with positioning based upon said associations involving said cnxpts and the strengths of said associations, and said categorization map is navigable by said user for associative searching and serendipitous discovery, and said contents of said commonplace as shown in said visualization embody a shared information collection and a shared analysis for categorization.

112. The constructing a visualization map of claim 111 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 said fxxt member cnxpts according to process trees for visualization generation, position determination and final sizing means for calculation;

such that said bias tensors are considered in said determination of positioning of said dxo objects for visualization for said fxxt member cnxpts;

whereby the ability is provided to reduce the movement of cnxpts on successive generations of said map while moving said cnxpts into a position related to the closeness of said dxo object to others logically according to changes made in said commonplace between generations of said map.

115. The method of claim 16, to improve machine learning efficiency by correcting a stigmergic commonplace derived, at least in part, from a machine learning process, comprising:

a. providing computer storage to contain a commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. preparing, by at least one processor, 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 process means;

f. accepting commands to ingest data automatically;

g. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

h. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

i. managing an addition or refinement of said commonplace received from the user by performing at least one of;

i. accepting votes regarding information based upon entered commands and navigation;

ii. track strength of categorizations by tallying of votes according to utilizing of said collective consensus process means for said plurality of votes by said user;

iii. harmonizing categorizations by altering extracted categorization to form an altered organization of knowledge; and

iv. performing cleanup according to data cleanup process means;

j. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting of;

k. accepting at least one user command indicating a vote regarding how an info-item should be changed based upon the user'"'"'s own cognitive structure, the indication selected from the group consisting of;

i. to view content of said commonplace;

ii. to navigate around a visualization of said commonplace; and

iii. to request a search for wisdom;

iv. to traverse from a first context represented by a first cntexxt represented internally by said first cnxpt on the 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 such that 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;

v. to re-categorize the info-item;

vi. to indicate 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;

vii. to state that a first concept is a differentiable offshoot of second concept, such that said second concept represented by a second cnxpt is to be a parent in a parent child relationship info-item with said first concept represented by a first cnxpt;

viii. to state that a first concept is of a temporally differentiable timeframe occurring after a second concept, such that said second concept represented by a second cnxpt is to be the parent in a parent child relationship info-item with said first concept represented by a first cnxpt;

ix. to state that a first concept is within a context defined by a second concept, such that said second concept represented by a second cnxpt is to be the parent in a parent child relationship info-item with said first concept represented by a first cnxpt where said parent child relationship info-item indicates context membership; and

x. to state that a first concept is dependent in a precedence upon the existence, initiation, or completion of a second concept, such that said second concept represented by a second cnxpt is to be the predecessor in a predecessor successor relationship info-item with said first concept represented by a first cnxpt;

xi. to alter the relationship between a pair of info-items;

xii. to add a property and set its value;

xiii. to remove a property;

xiv. to set a property to a different value;

xv. to remove an info-item;

xvi. a command to add an info-item;

xvii. to alter a textual entry;

xviii. a selection from a list of differentiation types;

xix. a selection of a list of characteristics of said first concept represented by said cntexxt and also setting a differentiated value for said characteristic;

xx. 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;

xxi. the stating of one or more words describing a differentiation type not listed;

xxii. 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;

xxiii. 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;

xxiv. 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;

xxv. 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;

xxvi. 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;

xxvii. 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;

xxviii. 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;

xxix. citing 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 first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for;

xxx. citing 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 first concept represented by said cntexxt and not precisely excluded from encompassing the present purlieu of said first concept represented by said cntexxt;

xxxi. to add or refine content of said personal commonplace and effect change by entering content change votes;

whereby the imprecise definitions of concepts represented by cnxpts can be indicated as incomplete needing definition improvement, subdivided by creation of two more precisely identified cnxpts that become children of the original cnxpt, combined with another cnxpts, deleted, or refined by the user or others who may be inexpert and thus require veracity weighting; and

whereby categorizations can be developed from an imprecise to a fuzzy to a harmonized state in a personal data arguing process over time to obtain, in the face of change or indecision, automated resolution assistance that is tunable, measurable, and repeatable; and

whereby use of identity indicator rankings leads to a higher degree of clarity by ranking, the use of fxxts reduces conflicts between meanings caused by similarity of terms across different categorization bases, use cases; and

whereby use of votes and consensus structures provides for reapplying corrections where new data is ingested that contains the same error; and

whereby these operations can be performed rapidly, aided by automation, checked for quality and prioritized acceptance in a workflowed and prioritized review by the user, and redone under improved approaches; and

whereby said commonplace becomes a resource with a purpose suitable to said user 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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by others and acquiring new knowledge, and aided by accepted assistance of many participants correcting and integrating previous knowledge and applying machine algorithms to continually evolve understanding of the phenomena, based on the best available data at a time point, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of hundreds of thousands ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data of attributes and records with efficient use of human guidance weighted by expertise;

whereby fxxts provide provenance and use case applicability, cnxpt typing, and relationship info-item typing, cnxpt and relationship info-item aging, cnxpt and relationship info-item applicability by age, process phasing identification, user process temporaries identification, interim search result identification, and other differentiations and each user can have their own personal curation process and result, each user session can be differentiated, interim and temporary results are uniquely identifiable, data sets and DataSets are identifiable, data may be consigned for sale, fxxt structures and cause structures may be to identified and combined, operations may be performed based on different relationship info-item or cnxpt types, models may be applied to the same categorization forest but based upon different relationship info-item weights, cnxpt importances, relationship info-item or cnxpt type interpretation, or based upon the position of the relationship info-item or cnxpt within a categorization forest, different model formulas or default or initial values by fxxt, access control, as well as other differentiations by fxxt.

116. The method of claim 16, to provide a curatable personal stigmergic commonplace, comprising:

a. providing a computer storage to store a personal commonplace;

b. providing an interface for user to view, navigate and enter commands to interface with said commonplace;

c. establishing a personal commonplace and loading structural information defining a knowledge model for a domain of wisdom into the computer storage;

d. preparing, by at least one processor, 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;

e. displaying to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

f. receiving, from the user, a choice of a categorization context instance represented by cntexxt within said categorization to use as a focus point;

g. managing an addition or refinement of said commonplace received from the user by performing at least one of;

i. accepting votes regarding information based upon entered commands and navigation;

ii. track strength of categorizations by tallying of votes according to utilizing of said collective consensus process means for said plurality of votes by said user;

iii. harmonizing categorizations by altering extracted categorization to form an altered organization of knowledge; and

iv. performing cleanup according to data cleanup process means;

h. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting of;

i. to view content of said commonplace;

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; and

iv. to request a search for wisdom;

v. to traverse from a first context represented by a first cntexxt represented internally by said first cnxpt on the 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 such that 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 being conjured by said user should be 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, such that said second concept represented by a second cnxpt is to be a parent in a parent child relationship 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, such that said second concept represented by a second cnxpt is to be the parent in a parent child relationship 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, such that said second concept represented by a second cnxpt is to be the parent in a parent child relationship info-item with said first concept represented by a first cnxpt where said parent child relationship 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, such that said second concept represented by a second cnxpt is to be the predecessor in a predecessor successor relationship info-item with said first concept represented by a first cnxpt;

whereby the imprecise definitions of concepts represented by cnxpts can be indicated as incomplete needing definition improvement, subdivided by creation of two more precisely identified cnxpts that become children of the original cnxpt, combined with another cnxpts, deleted, or refined by the user or others who may be inexpert and thus require veracity weighting; and

whereby categorizations can be developed from an imprecise to a fuzzy to a harmonized state in a personal data arguing process over time to obtain, in the face of change or indecision, automated resolution assistance that is tunable, measurable, and repeatable; and

whereby use of identity indicator rankings leads to a higher degree of clarity by ranking, the use of fxxts reduces conflicts between meanings caused by similarity of terms across different categorization bases, use cases; and

whereby use of votes and consensus structures provides for reapplying corrections where new data is ingested that contains the same error; and

whereby these operations can be performed rapidly, aided by automation, checked for quality and prioritized acceptance in a workflowed and prioritized review by the user, and redone under improved approaches; and

whereby said commonplace becomes a resource with a purpose suitable to said user 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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by others and acquiring new knowledge, and aided by accepted assistance of many participants correcting and integrating previous knowledge and applying machine algorithms to continually evolve understanding of the phenomena, based on the best available data at a time point, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of hundreds of thousands ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data of attributes and records with efficient use of human guidance weighted by expertise;

whereby fxxts provide provenance and use case applicability, cnxpt typing, and relationship info-item typing, cnxpt and relationship info-item aging, cnxpt and relationship info-item applicability by age, process phasing identification, user process temporaries identification, interim search result identification, and other differentiations and each user can have their own personal curation process and result, each user session can be differentiated, interim and temporary results are uniquely identifiable, data sets and DataSets are identifiable, data may be consigned for sale, fxxt structures and cause structures may be to identified and combined, operations may be performed based on different relationship info-item or cnxpt types, models may be applied to the same categorization forest but based upon different relationship info-item weights, cnxpt importances, relationship info-item or cnxpt type interpretation, or based upon the position of the relationship info-item or cnxpt within a categorization forest, different model formulas or default or initial values by fxxt, access control, as well as other differentiations by fxxt.

117. The method of claim 16, to manage a stigmergic commonplace of database authority information to improve database quality, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace;

c. providing application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

d. providing application software map generation means for performing categorization and generating maps;

e. providing one or more computers hosting functions for users to interface with said commonplace;

f. providing application software local or distributed processes means for managing user interface functions and performing automated tasks resulting from user actions;

g. providing application software display and delivery means for controlling presentations of results to users and accepting navigation and other user commands to interface with said commonplace;

h. initiating execution of software for managing and delivering on said one or more computers with functions for managing and delivering said commonplace;

i. initiating execution of software for users to interface on said one or more computers hosting functions for users to interface with said commonplace;

j. initiating execution of communications between said computers with functions for managing and delivering said commonplace and said one or more computers hosting functions for users to interface with said commonplace;

k. establishing a commonplace into said computer storage;

l. providing coordinated access to data extraction analytics for carrying out computer database searching, data extraction, transformation, translation, and loading;

m. providing coordinated access to document management analytics for controlling, storing, accessing, and displaying electronically stored information resource documents;

n. loading of said commonplace with structural information defining a knowledge model;

o. providing task management and document management analytics for controlling workflows, determining scheduling based upon workflow priorities, and suggesting task assignments;

p. initiating execution of continuous processing functions according to continuous processing process means;

q. ingesting a plurality of source objects;

r. 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 consisting 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;

s. 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 consisting 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, such that all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

t. 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;

u. initiating continuous extraction, for each source object that is unstructured data, of all descriptive elements of said source object selected from the group consisting 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, such that 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 unstructured data, a cited information resource irxt info-item for any information resource not existing in said commonplace of information;

w. initiating continuous extraction of topical elements from said source object, said topical element selected from the group consisting 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, such that a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, such that 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;

x. 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;

y. 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;

z. 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;

aa. 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;

bb. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process 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;

cc. 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;

dd. configuring workstation computers to communicate with server computers for transferring information and commands;

ee. granting access to said commonplace;

ff. initiating execution of the means for managing user interface functions and performing automated tasks resulting from user actions;

gg. initiating execution of application software on one or more of said one or more computers to present a version of said results through a user interface to a user and to accept user commands;

hh. initiating execution of the means for display and delivery such that a portion of said commonplace is displayed to said user;

ii. initiating requests for action, with attached description of action, to a user according to methodology workflow specification step;

jj. initiating alerts, with attached description, to a user according to an alert specification generation rule;

kk. initiating methodologies according to said methodology templates;

ll. initiating workflows according to said workflow templates;

mm. providing search query procedure templates for searching for source objects to determine relevance;

nn. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

oo. providing methodology and workflow templates for project management of searching for and reviewing source objects to determine relevance to a stated meaning or issue;

pp. providing prediction analytics establishing commonalty and similarity scores for source objects;

qq. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group consisting 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;

rr. computing a predicted weighted ranking of the likely relevance of said source object to a coding key cnxpt as specified;

ss. computing a predicted weighted rejection ranking of said source object according to rules for rejection for security rules;

tt. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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 visualization 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 view point, such that data arguing is resolved to a consensus, such that said categorization is appropriate to a domain of wisdom for a use case, such that use of different maps provides correlated categorization structuring of the same raw data, such that raw data is converted to consensus structured clean data and useful decision structures, such that various view points 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 view point;

whereby a guide to what data an organization actually has access to in the present or at any other point in time, and how to find and interpret it within context and with bias correction is produced;

whereby data obtained from multiple sources can be integrated and provenance regarding all sources retained; and

whereby data that should be identical regardless of source is different for certain sources can be utilized as an indicator of untrustworthiness;

whereby overlapping data sets with differentiated provenance may be adjusted for biases, time effects, or other consistent differentials;

whereby duplication of data is reduced and curation, data arguing, and integration results are traceable, sharable, and reusable; and

whereby data may be charged for on a disaggregated basis, data of benefit is readily accessible for a shared cost, deprecated data is identifiable for destruction and protected against inappropriate destruction;

whereby authority control of data and data identification are applied to the data curation process to obtain and review source objects according to methodologies and methodology templates, algorithms in predictive coding, meta-data regarding source objects such as originator and owner, where it was found, when it was found, its origination date, subject coding, and responsible party sufficient to manage data extraction, transformation, translation, loading, document management and control, computer search, data curation, and sampling technique analytics and managing the project for searching for or review, prioritization for review accuracy in a priority review and data arguing process that is tunable, measurable, and repeatable so that objective opinions regarding conceptual meanings of entities are derived from default values, to automatically predicted pertinence and similarity values, to subjective opinion votes to a consensus, starting with a small set of similarity bases that grows as by training to settle on a proper set of entities and cleaner data, adjusting to changes over time by associating the context at a time period against the entity existing at that time for entity applicability as entities evolve and adjust to subtle differences of entities that are internal to an organization to keep up with what the entity is called or understood to mean outside, and to allow an organization to obtain and distill a huge amount of information from outside but categorize it according to internal entities or from a specific viewpoint.

118. The adding and refining said commonplace of claim 2 to 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;

e. summarizing fxxt weightings for fxxt instance into summary by fxxt where possible;

whereby a managed process for continuous curation is formed.

119. The method of claim 2 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;

whereby user changes regarding a ttx cause said repositioning of it in said visualization, as calculated based upon user categorization votes.

120. The method of claim 2 to also accept user training, further including:

a. accepting an initial exemplar visualization map;

b. accepting repositioning of zero or more exemplar positions in a exemplar visualization map by a user;

c. accepting repositioning of zero or more cnxpts in a visualization by a user;

d. accepting re-categorization of zero or more cnxpts in a visualization by a user;

e. accepting manual resolution of zero or more positioning defects in a visualization;

f. recalculating display object positions based upon user changes in a visualization; and

g. predetermining improved fxxt coefficients based upon quality error metric value calculations, fxxt extractions, forest extractions, roll-ups, and positionings;

h. accepting manual changes of fxxt coefficients of zero or more fxxts from which visualization was derived;

i. predetermining fxxt extraction, forest extraction, and roll-ups based upon quality determinations and user changes affecting structure; and

j. recalculating quality error metric values based upon changes;

whereby user changes regarding an exemplar and repositioning in said visualization as calculated based upon user categorization votes, provide a training pattern for categorizations.

121. The method of claim 117, to utilize assistance of others or experts when necessary in adaptive resource allocation, further including:

a. registering data to be curated;

b. registering one or more curating sponsors for data curation and the compensation they offer for curation of the data they are seeking curation of, tasking definition for stating role of curator to fulfill, and domain knowledge and other requirements of curators;

c. invoking analytics applying knowledge bases (reference to create initial opinions regarding necessity of specific repairs of apparently erroneous data sets;

d. incenting the right human;

the data creator or owner (a business not the data wrangler (a programmer);

e. incenting data producing human to curate and integrate data into said commonplace at the source;

f. 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 may cause sufficient frustration to cause responsive actions by knowledgeable users;

g. incenting openly rather than hiding the operations to generate sense of participation and openness;

h. 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;

i. scheduling adaptively so that incremental changes are anticipated but human resources are scheduled by the human to avoid overloading;

j. project oriented phasing of incremental identification, metadata adjustment, integration, reviewing iterations;

k. engaging humans in specific roles of in the data curation loop wherein data scientists aware of the final questions that need to be answered from the input data are engaged in selecting analytics to apply for automated error detection;

l. engaging humans in specific roles of in the data curation loop wherein sponsoring business articulate the value of the analytics are engaged in selecting analytics to apply;

m. engaging humans in specific roles of in the data curation loop wherein qualified domain experts are engaged to answer data-centric questions regarding input data;

n. tracking rough cut review to detailed review iteration;

o. recording opinions based upon trustworthiness of opinion in view of sponsor;

p. applying changes to data owned by sponsor to fix errors based upon opinions exceeding a predetermined level of trustworthiness of opinion;

q. incentivizing business experts to assist in making curation decisions with hierarchy of experts inside an enterprise as well as various kinds of expertise externally;

r. a mechanism for identifying data resources that they wish to have curated;

s. incremental identification of provenance veracity;

t. entering provenance information regarding the data source and identity information into said commonplace catalog;

u. 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 retrieve than other such data;

v. crawling to search a corporate internet to locate relevant data sources;

w. finding enterprise data sources;

x. tiering curation by accepting initial opinions from a machine learning approach involving one or more algorithms that will do the necessary curation, and accepting a opinions by one or more humans wherein human opinions are weighted higher than machine learning opinions and are weighted according to the expertise of the user to improve quality by using those best qualified;

Y. calculating quality corrections according to prediction correction mechanism;

z. crowdsourcing to enlist labor;

whereby different roles of humans in the data curation loop are structured to provide an adaptive and efficient business expert driven curation process bridging the gap between the machine learning/automated data improvement and the curator to tradeoff between accuracy and the amount of human involvement attracting those greater in expertise than available staff and of an appropriate cost, if any, to outsource the curation by distributing tasks to data producers and consumers to ask their opinions and draw on their expertise and institutional memory to raise the confidence in the predictions based upon the data in said commonplace, and only trusted fixes are made to data errors as fixes are applied only where sufficiently trusted opinions were expressed regarding the invalidity of data, the high cost involved in engaging data experts is reduced, and experts and analytics applying algorithms and reference source knowledge bases to repair erroneous data sets are judiciously involved.

122. The method for curation of claim 90, to calculate quality corrections according to prediction correction mechanism, wherein:

a. determining an error metric based upon distances of cntexxt centers from exemplar cnxpt placements for similar concept;

b. adjusting coefficients for fxxts in a plurality of attempts at generating of a map until a recalculation of distance based error metric yields an improvement in the calculated error metric;

c. stopping the recalculation process when the error metric shows little improvement after a predefined number of recalculations, or the error metric reaches an acceptable value;

whereby use of votes and consensus structures provides for reapplying corrections where new data is ingested that contains the same error; and

whereby these operations can be performed rapidly, aided by automation, checked for quality and prioritized acceptance in a workflowed and prioritized review by the user, and redone under improved approaches;

123. The quality corrections of claim 90 for positioning error determination, further including:

a. initializing fxxt specific ttx map data set of cnxpt centroid points by the initiation step;

b. updating that data set;

124. The quality corrections of claim 90 for searching error determination, 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 process 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 process means, such that 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, such that 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, such that 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 such that 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. 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;

vi. summing, with predetermined coefficient values for each error metric, 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;

125. The method of claim 90 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.

138. The method of claim 16, to visualize data of a commonplace of information, comprising:

a. extracting a fxxt of info-items from the commonplace of information;

b. extracting a forest of cnxpts in a categorization of cnxpts;

c. displaying a visualization of the cnxpts are shown;

whereby users obtain 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 categorization shows a visualization;

142. The method of claim 16, for delivering frameworks for reuse of results of prior efforts, comprising:

a. reducing search result sets to only entries non-common with the context a concept is a member of in an organization of knowledge;

b. retaining differentials between actuals, corrected beliefs, and beliefs for inclusion in weighted moving averages of viewpoint metrics;

143. The method of claim 16, for organizing and displaying a plurality of contexts represented by cntexxts themselves represented by cnxpts as categories of information on a display screen, the method comprising:

a. organizing the plurality of contexts represented by cnxpts according to at least one relatedness measure between respective pairs of the plurality of contexts;

b. constructing tensors from the relationships relating cntexxts among the plurality of contexts;

c. creating a positioning matrix from the tensors according to positioning function means such that similar objects are in closer proximity than dissimilar objects;

d. positioning the cntexxts according to the positioning matrix;

e. displaying on a first portion of the display screen, the plurality of cntexxts as a network display, the network display including avatars corresponding to the plurality of contexts;

f. displaying simultaneously, avatars representing sub-contexts of at least one context in the subset of the plurality of contexts as avatars internal to said cntexxt;

g. displaying on the first portion of the display screen a properties and information panel pertaining to a selected cntexxt on demand in response to indicating a corresponding avatar;

h. hiding presently less important contexts to reduce the complexity of the display;

i. hiding information regarding presently less important contexts to reduce the complexity of the display;

j. forming a cnxpt when a new idea is identified;

k. staking a claim;

l. responding to a first selection indication by highlighting a subset of the plurality of contexts in response to a first selection of an avatar representing at least one of the plurality of contexts;

m. responding to a second selection indication by highlighting and displaying a second subset of the plurality of contexts in response to a second selection of an avatar representing a different one of the plurality of contexts;

n. responding to a re-categorization command as performed by a user by cutting and pasting, dragging, or other moving of one subset of avatars onto another single avatar to inform the system that said user believes that the correct categorization would have said moved avatars as being within the category cnxpt as shown by the context avatar upon which the moved avatars are dropped;

o. wherein the plurality of contexts are visible at any level of detail and at any scale; and

wherein detail refers to the information within internal contexts of a given context of said plurality of contexts and scale refers to the size of any displayed context;

whereby ideas are treated as narrowing the scope of the enclosing idea, but not stating that it is the last possible idea so the identified idea is itself a context ready for population by yet newer ideas. responding to navigation commands to traverse the display of contexts and information.

144. The method of claim 16, for categorization harmonization using networked computer processors, comprising:

a. providing curating application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

b. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

c. providing initial commonplace of information;

d. collecting information into a data set to be compared against or added to said commonplace;

e. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

f. 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;

g. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

h. replacing any considered relationship info-item of endpoint count greater than two by an equivalent set of relationships having an endpoint count of two;

i. collecting all relationships of the type within the set of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and either already exists or is to be added between said entity types to be considered as instances of said cnxpt type;

considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization to be between said instances of said cnxpt type;

k. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

l. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

m. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

n. 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 function means;

o. reporting the structure of said spanning forest of cnxpts and interrelationships;

p. distributing information content extracted from said commonplace;

q. managing said user interface functions at said workstations and performing said automated tasks resulting from user actions—

according to local or distributed processes means;

r. presenting a local version of a portion of said commonplace content and said maps through a user interface to said user and to accept said user'"'"'s commands;

s. controlling presentations of results to users and accepting navigation and other user commands for use of said maps, to at least one of registering said votes for weighting or direction of relationships between cnxpts to said commonplace content to call for commonplace of information changes—

according to display and delivery functions means;

174. The method of claim 16, for determining initial relevance of a plurality of documents by weighted distribution to categories, comprising:

a. retrieving, by a processor, the plurality of documents;

b. loading, by the processor, a commonplace having a plurality of commonalities, concepts, and at least one organization of knowledge having at least one concept;

c. dissecting by token extraction parsing a first retrieved document into a plurality of phrases as parsed parts;

d. ingesting a parsed part into the commonplace, creating a first cnxpt termed a dissection cnxpt;

e. registering text of the parsed part into the commonalities of said commonplace as a comparator token with a reference connection to the first document and to the first cnxpt, said reference connection given a predetermined weight;

f. imputing relationship info-items from commonalities;

g. generating a structuring of the at least one organization of knowledge based on a consensus of said commonplace as augmented by the info-items imputed from said plurality of documents and the cnxpts according to collective consensus through vote tallying and map generation, each specific member of the at least one organization of knowledge including the augmented info-items termed a comparison map;

h. determining a combined aggregated normalized relevance score for each new or previously added document in said commonplace for each basis cnxpt based upon the distance in said comparison map from the center of a dissection cnxpt to the center of said basis cnxpt, creating or updating a result set item in a result set attached to said basis cnxpt referencing said added document and having a relevance score equal to said combined aggregated normalized relevance score involving said added document and said basis cnxpt;

i. reordering said result set items of said result set attached to said second basis cnxpt according to said result set item relevance scores;

whereby each document of a plurality of documents is ranked against a cntexxt in said commonplace according to its relevance to said cntexxt and sets of documents are rapidly categorized into said commonplace;

whereby due to the ability of the method in combination with commonality, imputing, fxxt extraction, consensus, and mapping means a series of different categorizations with a resulting combined relevance calculated will reflect a dispersal of documents or ingested information across the set of cnxpts with relevance rankings consistent with the pertinence of said document or ingested information to a specific cnxpt.

175. The method for determining initial relevance of claim 174, to determine relevance of documents by culling, further including:

a. showing a new cnxpt internally to the older cnxpt as smaller, so the older idea is actually a context or category, and as the new offshoot idea does not occupy all of the older idea'"'"'s area, voids are left in the context where other new ideas might be entered or in other words still allowing for more children to be spawned from the older idea. that new idea may some day have new offshoot ideas of its own, so it is drawn as a context as well, all empty, and it is considered a leaf only until new ideas come up. so, every non-leaf idea is both an idea of itself, as well as a context for offshoot ideas;

176. The method of determining initial relevance of claim 174, 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;

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;

177. The method for determining initial relevance of claim 174, to score relevance of a plurality of documents by weighted distribution to categories, wherein:

a. loading a commonplace having a plurality of commonalities, concepts, and 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;

b. accepting a request to load said plurality of documents;

c. ingesting each first object document of said plurality of documents into said commonplace if not already present by forming at least one binding point for said first object document in the commonplace, each said binding point created as a first cnxpt termed a dissection cnxpt;

d. dissecting, or accepting a dissection of, said first object document into a plurality of first parsed parts resulting from one or more analytics, ingesting each first parsed part into said commonplace if not already present by forming at least one binding point for said first parsed part in the commonplace, each said binding point created as a first cnxpt termed a dissection cnxpt;

e. updating the consensus of said commonplace augmented by all info-items generated from said plurality of documents and all dissection cnxpts according to utilize collective consensus through vote tallying process means;

i. determining a normalized relevance score between minus one and plus one for relevance of each loaded document to each second said basis cnxpt, including all documents from prior loadings if any, by;

01. determining a disaggregated normalized relevance score between zero and plus one 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, normalizing across all such disaggregated normalized relevance scores for relevance of a differentiated concept, each such score termed a new load disaggregated scoring;

02. determining a disaggregated normalized relevance score between minus one and plus one 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;

03. determining a combined disaggregated normalized relevance score between zero and plus one 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;

04. determining a combined aggregated normalized relevance score between minus one and plus one 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;

05. creating, if the normalized document relevance for a document-cnxpt pair involving said first document and said second basis cnxpt is greater than zero 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;

f. configuring the processor to set a context represented by a cnxpt of a user'"'"'s choice within a categorization of cnxpts as a navigation starting point;

g. 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;

h. 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;

i. 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, such that 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, such that 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;

j. accepting a command from said user stating that the search goal has resolved and one of that a proper cntexxt has been found satisfying the search goal criteria actually intended by said user, that said cntexxt sought was not found but its appropriate parent category was found, or that the goal was not located;

whereby each document of a plurality of documents is ranked against a cntexxt in said commonplace according to its relevance to said cntexxt and sets of documents are rapidly categorized into said commonplace;

whereby due to the ability of the method in combination with commonality, imputing, fxxt extraction, consensus, and mapping means a series of different categorizations with a resulting combined relevance calculated will reflect a dispersal of document or ingested information across the set of cnxpts with relevance rankings consistent with the pertinence of said document or ingested information to a specific cnxpt.

178. The adding and refining said commonplace 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 a result set based upon a search for user culling;

b. determining which set of at least one cnxpt have sets of occurrences most similar to the items in the result set;

c. moving the user'"'"'s focal point in the visualization to a point nearer to the cnxpt of the set having the closest set of occurrences;

d. accepting a user culling of the result set;

e. determining again which set of at least one cnxpt have sets of occurrences most similar to the items in the result set;

f. moving the user'"'"'s focal point in the visualization to the cnxpt of the set having the closest set of occurrences;

whereby a user search goal is pushed to a different location in a visualization;

179. The adding and refining said commonplace 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 an area of consideration based upon a search for user culling;

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;

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;

180. The adding and refining said commonplace 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 a result set of at least one property selected from the group;

features, purlieu, attribute values, and property values;

for user culling based upon a search;

b. generating an area of consideration based upon the cnxpts having features, purlieu, attribute values, or property values in the result set;

c. determining which set of at least one cnxpt in the area of consideration have sets of features, purlieu, attribute values, or property values most similar to the items in the result set of features, purlieu, attribute values, or property values, 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 the result set of features, purlieu, attribute values, or property values;

f. generating an area of consideration based upon the cnxpts having features, purlieu, attribute values, or property values in the result set as culled;

g. determining which set of at least one cnxpt in the area of consideration have sets of features, purlieu, attribute values, and property values most similar to the items in the result set of features, purlieu, attribute values, or property values, 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;

whereby a user search goal is pushed to a different location in a visualization;

181. The method of claim 88 to perform modeling on the basis of a single forest of trees categorization, further including:

a. executing one cnxpt sub-setting operation selected from the group consisting 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 said sub-setting operation;

b. forming an area of consideration from said set of cnxpts defining a forest of trees and the relationships extracted by fxxt extraction process means based upon zero or more fxxt markings for said set of cnxpts;

c. extracting a descendent tree forest from said area of consideration according to tree extraction process means where said modeling rule formulas depend upon results of positioning process means;

d. interpreting said modeling rule formulas associated with the cnxpts in 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. executing positioning process means to determine positioning of cnxpts in said area of consideration on a predetermined visualization where results of said positioning results are to be considered in said modeling rule formulas;

f. interpreting said modeling rule formulas associated with said cnxpts in 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 the cnxpts remaining in the area of consideration associating results with said cnxpts;

whereby a forest based upon a filtered categorization of cnxpts provides structure for modeling based upon structural modeling rule functions such as sum characteristic of children, sum characteristic of children that are leafs;

adopt value of characteristic of child having greatest importance or fulfilling other criterion, adopt value of child having highest connection relationship info-item weight or fulfilling other criterion, normalize characteristic value considering siblings, inherit characteristic from parent, inherit value of sum of characteristic of all parents as specified for cnxpts of said result set as specified for cnxpts of said result set are interpreted to produce a modeling result for that segment of said commonplace found from said search operation; and

whereby modeling what if based upon search results, fxxt extraction, and filtering is provided.

182. The method of claim 88 to perform multi-forest modeling on the basis of single forests of categorization trees, further including:

a. setting up a first categorization forest for a first cnxpt type;

b. setting up a second categorization forest for a second cnxpt type;

c. imputing, from relationships between cnxpts of said first categorization forest and cnxpts of second categorization forest, values of an attribute of a cnxpt in one forest into a calculation for a cnxpt in the other;

183. The method of claim 88 to perform multi-forest modeling on the basis of single forests of categorization trees, further including:

a. executing one or more cnxpt sub-setting operations selected from the group consisting 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 by fxxt extraction process 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 tree extraction process means where results of modeling rule formulas are dependent upon tree structure or 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. executing positioning process means to determine 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;

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 by fxxt extraction process 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. generate a plurality of model result tuples each associated with one said intersection identifying tuple and consisting 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;

m. generating a model results data package consisting of;

the set of said plurality of intersection identifying tuples each with associated model result tuple;

whereby a set of forests based upon a filtered categorization of cnxpts provides structure for multi-forest modeling based upon structural modeling rule functions such as impute characteristic from intersected cnxpt in different forest, impute sum of characteristic from all intersected cnxpts in different forest, sum characteristic of children, sum characteristic of children that are leafs;

adopt value of characteristic of child having greatest importance or fulfilling other criterion, adopt value of child having highest connection relationship info-item weight or fulfilling other criterion, normalize characteristic value considering siblings, inherit characteristic from parent, inherit value of sum of characteristic of all parents as specified for cnxpts of said result set are interpreted to produce a modeling result for that segment of said commonplace found from said search operation; and

whereby modeling what if based upon search results, fxxt extraction, and filtering is provided.

184. The method of claim 16, to add available data sets to a commonplace of information of improving scope and quality to integrate entities, comprising:

a. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

b. providing initial commonplace of information;

c. collecting information into a data set to be compared against or added to said commonplace;

d. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

e. 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;

f. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

g. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and said relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

h. accepting a choice of one or more relationship info-item types to be used as positioning relationships for determining the positioning of cntexxts representing cnxpts in a visualization based upon concept similarity from the relationship info-item types indicating cnxpt similarity to prepare for categorizing and visualizing appropriate to said use case;

i. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity wherein the relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

j. linking cnxpts data integration is the mapping of entities, in order to be able to differentiate one piece of data from another. for a particular use case;

k. integrating cnxpts data integration is the mapping of entities, in order to be able to differentiate one piece of data from another. for a particular use case;

l. 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 relationship 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;

m. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity wherein the relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

n. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity to be between said instances of said cnxpt type;

o. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between cnxpts to have said single default fxxt during processing;

p. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

q. determining effective weights for summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

r. replacing any considered relationship info-item of endpoint count greater than two to an equivalent set of considered relationships having an endpoint count of two;

s. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and said relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

t. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization to be between said instances of said cnxpt type;

u. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

v. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

w. combining the endpoint cnxpts of said summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types 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 relationship 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 relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that an endpoint of any said relationships having is a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

x. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all said revised collection of relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

y. 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 function means;

z. reporting the structure of said spanning forest of cnxpts and interrelationships;

whereby cnxpts are arranged into a harmonized categorization for representing the non-duplicated entities of specified types and based upon the original relationships of specified types to provide automatic data arguing resolutions and curation by entity rationalization for synchronizing data sets into a commonplace of information having improving depth and quality and reaching agreement within an organization on how to define and use key data elements while also highlighting uncommon information where the entity information definitions that suit the purposes of a particular group or individual can also be useful to a second particular business function, unit, or work group to understand diverse perspectives or to discover cases not considered.

185. The method of claim 16, to extract concepts of imprecise identity with similar meanings into sets based upon categorization fuzziness from a stigmergic commonplace of information, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. providing software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

f. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

g. 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;

h. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

i. replacing any considered relationship info-item of endpoint count greater than two by an equivalent set of relationships having an endpoint count of two;

j. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and said relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

k. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization to be between said instances of said cnxpt type;

l. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

m. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

n. replacing any considered relationship info-item of endpoint count greater than two to an equivalent set of considered relationships having an endpoint count of two;

o. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

p. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

q. combining the endpoint cnxpts of said summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types 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 relationship 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 relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that an endpoint of any said relationships having is a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

r. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all said revised collection of relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

s. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

t. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

u. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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;

v. comparing exported data sets to ensure the consistency of reloaded data, for the elimination of re-classified records;

w. creating a cnxpt for the ttx which is at the top of the taxonomy;

x. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group consisting 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;

y. calculating quality corrections according to a prediction correction mechanism selected from the group consisting 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 relationship info-item 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 view point, such that data arguing is resolved to a consensus, such that said categorization is appropriate to a domain of wisdom for a use case, such that use of different maps provides correlated categorization structuring of the same raw data, such that raw data is converted to consensus structured clean data and useful decision structures, such that various view points form of correlative analysis base; and

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 view point;

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 view point, such that data arguing is resolved to a consensus, such that said categorization is appropriate to a domain of wisdom for a use case, such that use of different maps provides correlated categorization structuring of the same raw data, such that raw data is converted to consensus structured clean data and useful decision structures, such that various view points form of correlative analysis base; and

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 view point;

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 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 view point, such that data arguing is resolved to a consensus, such that said categorization is appropriate to a domain of wisdom for a use case, such that use of different maps provides correlated categorization structuring of the same raw data, such that raw data is converted to consensus structured clean data and useful decision structures, such that various view points form of correlative analysis base; and

z. removing commonplace info-items;

i. 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;

ii. removing permanently, by application of one or more cleanup and summarization analytics, zero or more redundant relationships 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, 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 relationships found redundant;

iii. 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, such that 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;

iv. 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 by;

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 relationships and term ttx meaning hierarchy relationships 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 relationships and term ttx meaning hierarchy relationships 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 relationship info-item distance by including into said fxxt additional instances of similarity relationships and term ttx meaning hierarchy relationships having one or more of said marked term cnxpts as endpoints and marking said instances of similarity relationships and term ttx meaning hierarchy relationships as having said fxxt for the purpose of the instant similarity illustration, and then marking all cnxpts serving as endpoints of said newly marked relationships as also having said fxxt for the purpose of the instant similarity illustration; and

07. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of differentiation between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

v. 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 consisting of;

01. ttx match indication to a user viewing said co-location map such that 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 such that user has registered to receive ttx match alerts, if said user has not yet been alerted or has requested all alerts;

whereby said commonplace becomes a resource with a purpose suitable to said user based on the best available data at a time point as; and

whereby categorizations can be developed from an imprecise to a fuzzy to a harmonized state in a personal data arguing process over time to obtain, in the face of change or indecision, automated resolution assistance that is tunable, measurable, and repeatable; and

whereby use of identity indicator rankings leads to a higher degree of clarity by ranking, the use of fxxts reduces conflicts between meanings caused by similarity of terms across different categorization bases, use cases; and

whereby use of votes and consensus structures provides for reapplying corrections where new data is ingested that contains the same error; and

whereby these operations can be performed rapidly, aided by automation, checked for quality and prioritized acceptance in a workflowed and prioritized review by the user, and redone under improved approaches; and

whereby said commonplace becomes a resource with a purpose suitable to said user 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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by others and acquiring new knowledge, and aided by accepted assistance of many participants correcting and integrating previous knowledge and applying machine algorithms to continually evolve understanding of the phenomena, based on the best available data at a time point, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of hundreds of thousands ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data of attributes and records with efficient use of human guidance weighted by expertise;

whereby fxxts provide provenance and use case applicability, cnxpt typing, and relationship info-item typing, cnxpt and relationship info-item aging, cnxpt and relationship info-item applicability by age, process phasing identification, user process temporaries identification, interim search result identification, and other differentiations and each user can have their own personal curation process and result, each user session can be differentiated, interim and temporary results are uniquely identifiable, data sets and DataSets are identifiable, data may be consigned for sale, fxxt structures and cause structures may be to identified and combined, operations may be performed based on different relationship info-item or cnxpt types, models may be applied to the same categorization forest but based upon different relationship info-item weights, cnxpt importances, relationship info-item or cnxpt type interpretation, or based upon the position of the relationship info-item or cnxpt within a categorization forest, different model formulas or default or initial values by fxxt, access control, as well as other differentiations by fxxt.

186. The adding and refining said commonplace of claim 185 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;

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;

whereby apparently duplicated concepts that are in all ways similar are nominated for removal from the commonplace.

187. The adding and refining said commonplace of claim 1 to refine a structure for the participant'"'"'s meanings of related ideas, 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;

c. processing said command to reparent a cnxpt as authoritatively reparented for the participant;

whereby votes by a user are considered differently when seen by themselves versus when seen by others.

188. 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. mark all instances of similarity relationships and term ttx meaning hierarchy relationships having one or more of said chosen term ttx instances as endpoints as having said fxxt for the purpose of the instant similarity illustration;

d. mark all cnxpts serving as endpoints of similarity relationships and term ttx meaning hierarchy relationships 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 relationship info-item distance by including into said fxxt additional instances of similarity relationships and term ttx meaning hierarchy relationships having one or more of said marked term cnxpts as endpoints and marking said instances of similarity relationships and term ttx meaning hierarchy relationships as having said fxxt for the purpose of the instant similarity illustration, and then marking all cnxpts serving as endpoints of said newly marked relationships as also having said fxxt for the purpose of the instant similarity illustration;

f. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

g. illustrating effective term similarity by positioning of terms;

whereby effective term similarity is shown.

191. The method of claim 16, to provide discussion specific to a narrow context within a stigmergic commonplace of information, comprising:

a. providing a computer storage to store said commonplace;

b. providing an interface for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. preparing, by at least one processor, 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;

e. configuring workstation computers to communicate with server computers for transferring information and commands such that improperly configured workstations will fail to communicate when requesting particular access of a pre-defined nature;

f. granting or rejecting access to said commonplace for a given type of interaction;

g. displaying to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

h. receiving a user command to request a connection with a person recently showing knowledge of concepts within a context represented by a cnxpt;

i. 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 consisting 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;

j. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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 where an authorized user is able to provide services, obtain information, negotiate agreements, and report completion of deliverables, all related to a specific topic or context of information in said commonplace and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development, coordinate product development, assess potentials, transfer technology, advertise technology, perform patent clearance operations; and

whereby students, professors, and technologists may communicate regarding narrow issues;

whereby associations may better reach constituencies;

whereby consultants providing may improve their results;

whereby market studies may be augmented by surveys and interviews;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost by communication;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of communication options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared space for detailed discussion;

whereby donative grantors may obtain information while seeking appropriate formative technologies to fund;

whereby individuals, lawyers, agents, researchers, and lawyers and their clients may better communicate regarding specific topics;

whereby individuals, agents, and lawyers and their clients may better communicate for a fee regarding specific topics;

whereby intelligence areas concerned may better communicate regarding specific topics; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and communicating.

193. The method of claim 16, to perform fuzzy logic modeling on the basis of categorization, further including:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. 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 comprising a set of at least one info-item with similarities to other un-extracted info-items of the fxxt according to the fxxt but extracted on the basis of fuzziness to offer categorization fuzziness, from said commonplace according to utilize collective consensus through vote tallying process means, wherein the marking criterion for fuzziness is selected from the group consisting of;

i. 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;

ii. a marking wherein the fxxt has a defined threshold function yielding a 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 value obtained from the threshold function for that info-item;

f. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

g. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

h. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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 categorization and modeling conforms to the way that people think which is inherently fuzzy, where perceptions are that the world is continually changing and cannot always be defined in true or false statements.

194. The adding and refining said commonplace of claim 1 to extract info-items for an operation based upon fuzzy logic set determination, wherein the operation involves at least one criterion selected from the group consisting of:

a. determining a consensus organization of knowledge of at least one domain of wisdom comprising at least in part a fxxt with a fuzzy marking criterion comprising a set of at least one info-item with similarities to other un-extracted info-items of the fxxt according to the fxxt but extracted on the basis of fuzziness to offer categorization fuzziness, from said commonplace according to utilize collective consensus through vote tallying process means, wherein the marking criterion for fuzziness is selected from the group consisting of;

i. 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;

ii. a marking wherein the fxxt has a defined threshold function yielding a 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 value obtained from the threshold function for that info-item;

b. imputing a relationship info-item from a specified commonality based upon whether the calculated strength of the commonality has a value greater than a specified threshold;

c. including an info-item of a specified fxxt as a member of an extracted set of info-items based upon whether a conditional'"'"'s value is greater than a specified threshold for said info-item'"'"'s type;

d. including a relationship info-item of a specified fxxt as a member of an extracted set of relationships based upon whether the calculated strength value of said relationship info-item is greater than a specified threshold;

e. choosing the best parent for a first cnxpt not yet having an assigned parent in a categorization based upon whether a strongest visualization structuring propositional hierarchical relationship info-item between said first cnxpt as child and any second cnxpt as parent in said relationship info-item has a strength greater than a specified threshold;

f. imputing a relationship info-item from a specified subject indicator comparison based upon whether the calculated similarity value is greater than a specified threshold; and

g. using an occurrence relationship info-item of a specified fxxt as a member a set of subject indicators to be included in a subject indicator comparison based upon whether the calculated strength value of said occurrence relationship info-item is greater than a specified threshold;

whereby a fuzzy set of cnxpts having potentially varying degrees of membership may be formed;

whereby a categorization of cnxpts may provide at any branch point a grouping of cnxpts of imprecise meanings that as fuzzily determined should be considered within the grouping providing the representation of subsumption situations where one concept could be considered entirely different from another but still within another concept'"'"'s meaning as with an apple core being different but also still the same as an apple;

whereby as a calculation specifying membership in a set is altered a cnxpt may become, for instance, a sibling of what was formerly its parent-branch point holding the cnxpt; and

whereby a visualization based upon rules to relate different fuzzy sets and numbers to depict and provide a modeling base for calculations and applications of rules of inference based upon sets formed according to membership functions with fuzzy logical decision rules of definition and then to apply rule of substitutions such as generalized modus ponens, modus ponendo ponens, implication elimination to obtain solutions involving inferentially based calculation results as well as forward chaining, Mamdani, Larsen, Takagi-Sugeno-Kang, and Tsukamoto inference and aggregation methods; and

whereby a collocation structure with arrangement of general and specific concepts where a general concept is a categorization including more specific concepts may be offered for associative searching.

195. The method of claim 1 to perform modeling on the basis of a structuring of info-items, wherein the structuring involves at least one criterion selected from the group consisting of:

modeling is on the basis of a single forest of trees categorization;

modeling is based upon multiple sub-categorizations with roots where at least one of the categorization cnxpts are of a different type or nature;

modeling is based upon multiple sub-categorizations with roots where at least one inter-category relationships is of a different type in each said sub-categorizations sub-tree;

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 relationships is of a different type in each said forest;

modeling is based upon dependency, precedence, causality, or surrogate causality;

modeling is based upon probability density functions for outcomes of a dependency, a precedence, a causality, or a surrogate causality;

modeling is based upon categorization to determine result and result is determined based upon causality or surrogate causality such that a causal relationship info-item exists between a parent to child category and a set, voted, probabilistically expected strength of relationships between children and their possible parents is determinant;

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;

modeling is based upon a categorization where organizations are shown as groupings of individuals or functions, each being represented by a category;

modeling is based upon a categorization where outcomes are prioritized, tasks are prioritized;

tasks are assigned or work completed by category;

modeling is based upon a categorization where prioritization or decisions are made by category;

modeling is based upon a categorization where strategies are subdivided into plan phases or results each being represented by a category;

modeling is based upon a matching of categories between a plurality of single forest of trees categorizations; and

modeling is based upon a relationship 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;

further comprising;

a. structuring an organization of knowledge from an extraction of info-items from the commonplace of information;

b. determining a modeling result by interpreting the model;

whereby a model based upon a plurality of categorization of cnxpts may be used in a determination.

196. The method of claim 195 to perform modeling wherein the method further comprises:

a. combining at least one form of data selected from the group consisting of;

structured entities with attributes values, relationships, parsings of text into parts of speech, parsings of text into relative positions, parsings of text into semantic roles, structured text, numerical, unstructured textual, probability density function definitions, statistical samplings, functions, and probably distributions into a predictive models;

b. applying interpretations of mathematical model functional specifications to predict results;

whereby a model based upon a plurality of inputs and relationships may be used in a determination.

198. The adding and refining said commonplace of claim 1 to refine a concept sought by sorting of results of a query by appropriateness to said concept sought and retaining said results with said concept sought, further including:

199. The method of claim 16, to extract a predetermined set of characteristics of cnxpts into a data package, comprising:

a. executing one cnxpt sub-setting operation selected from the group consisting 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 said sub-setting operation;

b. forming an area of consideration from said set of cnxpts defining a dimension and the relationships extracted by fxxt extraction process means based upon zero or more fxxt markings for said set of cnxpts defining a dimension;

c. extracting a descendent tree forest from the area of consideration according to tree extraction process means where said modeling rule formulas depend upon results of positioning process means or where results of modeling rule formulas or positioning process means are included in said predetermined set of characteristics of cnxpts to be extracted into said data package;

d. interpreting said modeling rule formulas associated with said cnxpts in said area of consideration where results of said modeling rule formulas are included in said predetermined set of characteristics of cnxpts to be extracted into said data package and said modeling rule formulas do not depend upon positioning of cnxpts;

e. executing positioning process means to determine positioning of cnxpts in said area of consideration on a predetermined visualization where results of said positioning are included in said predetermined set of characteristics of cnxpts to be extracted into said data package;

f. interpreting said modeling rule formulas associated with said cnxpts in said area of consideration where results of said modeling rule formulas depend upon positioning of cnxpts or where results of said modeling rule formulas are included in said predetermined set of characteristics of cnxpts to be extracted into said data package and 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. extracting a plurality of value tuples each consisting of;

values of predetermined characteristics of said cnxpts in said set of cnxpts defining a dimension;

i. generating said data package consisting of the set of said plurality of value tuples;

whereby a data package based upon a filtered categorization of cnxpts is efficiently extracted for use.

205. The method of claim 1 to provide for accepting expansions of the knowledge models of said commonplace, further including:

a. accepting zero or more info-item definitions to broaden the scope of said commonplace by adding objects;

b. accepting zero or more fxxt specifications each having zero or more ordered fxxt specification steps to establish repeatable procedures for extracting relevant sets of cnxpts from said commonplace for set purposes according to said fxxt specification;

c. accepting zero or more visualization definitions for a fxxt specifications to establish repeatable procedures generating a visualization showing a categorization of said cnxpts from said commonplace found to be members of said fxxt;

d. accepting zero or more map visualization definitions for a fxxt specifications to establish repeatable procedures for generating a map showing a categorization of said cnxpts from said commonplace found to be members of said fxxt;

e. accepting zero or more definitions of flows to show on said map;

f. accepting zero or more definitions of map objects to add to said map;

g. accepting zero or more changes to said specification of a fxxt;

h. accepting zero or more changes to said definition of a fxxt specification procedure step of said specification of said fxxt;

i. accepting zero or more info-item type definitions to broaden said scope of said commonplace by adding object types;

j. accepting zero or more commonality relationship info-item definitions with an enrolling of a heuristic software plug-in to generate said commonality; and

k. accepting zero or more imputation definitions with an enrolling of a heuristic software plug-in to perform said imputing;

l. such that at least one change is made to said knowledge models of said commonplace;

whereby said knowledge models of said commonplace are expanded and refined by creating new fxxt specifications and accepting refinements and accepting registrations of additional means to generate information automatically for better fxxt categorizations.

206. The method of claim 205, further including:

a. accepting zero or more changes to the definition of a methodology or workflow; and

b. accepting zero or more change to the definition of a methodology or workflow procedure step of said methodology;

whereby said knowledge models of said commonplace is expanded and refined by creating new methodologies or workflows and accepting refinements to them.

207. The adding and refining said commonplace 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 may be created and commonality relationships, sub-typing relationships, keyword relationships, phrase commonality thesauri, and other relationships created to improve the commonplace data.

208. The adding and refining said commonplace of claim 207, to also provide information collection and categorization, further including:

a. creating a hierarchical association between a cnxpt becoming a category and another cnxpt becoming a member of the category;

b. providing said hierarchical associations as the structure for a categorization for use such that a cnxpt having said relationship info-item with said information may be located if in a locatable category; and

c. attaching additional information to said cnxpt becoming a member of the category;

d. such that the additional information is available by access through said cnxpt;

whereby a catalog is developed and information found is added such that a user may access said information through a categorized cnxpt providing an index of information.

209. The adding and refining said commonplace of claim 208 to provide for accepting user information, further including:

a. accepting zero or more ideas into said commonplace by incrementally conjuring and concretizing a subjectively differentiated idea;

b. accepting zero or more ideas into said commonplace by concretizing a query goal;

c. accepting zero or more votes regarding presence and strength of an association relationship info-item between commonplace cnxpt info-items by accepting defining of a differentiation of a cnxpt into said original cnxpt and a new cnxpt;

d. accepting zero or more votes regarding presence and strength of an association relationship info-item between commonplace cnxpt info-items by accepting a classifying of said cnxpt into said category cnxpt;

e. accepting zero or more votes regarding presence and strength of an association relationship info-item between commonplace cnxpt info-items by accepting an opinion regarding similarity of said cnxpts;

f. accepting zero or more votes regarding presence or strength of a relationship info-item between commonplace info-items; and

g. accepting zero or more objection votes regarding presence or strength of a relationship;

h. such that an idea or an opinion is stated by a user and;

i. such that differentiated ideas that are improvements to inventions are added as new cnxpts subdividing existing cnxpts so that said existing cnxpts become category cnxpts in the process of manual addition of cnxpts and associations into said commonplace to capture imagination and opinions regarding categorization from a plurality of users of various expertise;

whereby imaginative thoughts of users are captured and organized into a useful structure for tracking improvements to conceptual contributions as separate conceptual additions to provide for security and attribution to foster continuous improvement of said commonplace with an incentive to users to gain value and to satisfy a user'"'"'s need for participation in a coordinated effort to collect information about ideas into said commonplace while considering differentiated user expertise.

210. The adding and refining said commonplace of claim 209 to form a consensus, further including:

a. forming consensus regarding categorizations by association consensus tallying means summarizing strengths of one or more similar relationship info-items to form a single summary relationship info-item replacing said one or more similar relationship info-items; and

b. forming consensus regarding properties by property consensus tallying means summarizing one or more values for a property of an info-item to form a single summary property with one value for said info-item;

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

211. The adding and refining said commonplace of claim 210, to also provide acceptance of occurrences, further including:

a. locating information possibly relevant to a cnxpt and representing it by a txo in said commonplace;

b. relating said information to said cnxpt in said commonplace by generating an occurrence between said txo instance and said cnxpt with a strength stated for the relevance of said information to said cnxpt;

c. accepting votes 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

d. forming a consensus of the strength of said relevance of said information item to said cnxpt;

such that said strength of relevancy is adjusted based upon said opinions entered to form said consensus;

whereby a user'"'"'s need for coordinated storage of relevant information aids in collecting information about ideas in said commonplace as new information is brought into said knowledgebase and stated as relevant to ideas or categories of ideas.

whereby the type of source and, optionally, its usability, quality, expertise, etc. are given by the source object and all ingested information is accessible as a unit;

whereby users participating in the process of curation are informed of needed attention to curate concepts and information in the commonplace.

212. The adding and refining said commonplace of claim 211 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;

whereby a user'"'"'s need for coordinated storage of relevant information resource or internal resource serving as an information resource aids in the collection of information about ideas in said commonplace as new information resources or internal resources serving as information resources are brought into said knowledgebase and stated as relevant to ideas or categories of ideas.

213. The method of claim 1 to accept at least one indication of how said concept being conjured by said user is differentiated from said existing concept, wherein:

a. accepting at least one indication of how said concept being conjured by said user is differentiated from said first concept represented by said cntexxt, the indication selected from the group consisting of;

i. a textual entry;

ii. a selection from a list of differentiation types;

iii. a selection of a list of characteristics of said first concept represented by said cntexxt and also setting a differentiated value for said characteristic;

iv. 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;

v. the stating of one or more words describing a differentiation type not listed;

vi. 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 the characteristic;

vii. 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;

viii. 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;

ix. 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;

x. 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;

xi. 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;

xii. 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;

xiii. citing 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 first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for; and

xiv. citing 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 first concept represented by said cntexxt and not precisely excluded from encompassing the present purlieu of said first concept represented by said cntexxt;

whereby a description explaining differentiation can be provided.

214. The method of claim 213 to control access to said differentiated concept, wherein:

a. 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;

b. accepting a user request to constrain access to information pertaining to said new technology innovation idea;

c. accepting a user request to constrain access to particular portions of information pertaining to said new technology innovation idea;

d. accepting a user request to refrain from publishing a differentiated concept for a specified time to protect said new technology innovation idea;

e. accepting a user request to pursue, with assistance, a government process to protect said new technology innovation idea;

f. updating said data structures for source object access control;

g. updating said data structures for source object cataloging, tracking provenance, by controlling access, by collecting voting on veracity of data;

h. accepting a user request to provide or constrain access to personal information related to said new technology innovation idea'"'"'s originator;

i. offering and accepting a contract to constrain access to and guarantee against publishing a new concept conjured;

j. providing information repository structures for managing and sharing competitive information on an access controlled basis;

k. monitoring information access and usage;

l. granting access to commonplace of information;

i. narrowing results by applying access right restrictions while forming a fxxt from extraction or search result inclusion;

ii. associating fxxt unique to controlled data granted to a user to control original and interim data so that data already screened for access control is encapsulated by newly assigned fxxt and need not be rescreened for additional access granting for the user;

m. associating unique data marking to controlled data of an owner to control original and interim data owned;

n. associating unique data marking to control original and interim data of a communal innovation consortium where others may join to work on ideas in a protected environment on an access controlled basis;

o. 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;

whereby control over added information is accorded to a user for an appropriate time frame;

whereby what people use and try to use is tracked to thwart attempts at unauthorized access as well as to obtain user interest in specific data, learn how people are using the information, and computing of fee data and fee services for billing.

215. The adding and refining said commonplace of claim 1 to curate added information, further including:

216. The method of claim 2 to provide protecting against unapproved or unpaid release of private information intended to be protected while held in said commonplace, comprising:

a. controlling access by said user by identification of user, authentication, granting of access to said commonplace content;

b. performing fee-based usage and usage right granting of for fee functions;

c. controlling said user'"'"'s adding of information to said commonplace;

d. controlling participation by said user in one or more marketplaces for ideas;

e. controlling participation by said user in one or more marketplaces for data related to specific concepts categorized in said commonplace;

f. controlling access by said user to functions for establishing protection for said idea, granting access to said idea, granting access to project teams involved with applying said idea, and, if novel, to legal protection for said idea;

g. controlling access by said user to tools for ideating, searching, organizing, protecting, commercializing, communicating, and extending said ideas in said commonplace;

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 said votes or causing changes to said commonplace content—

according to display and delivery functions means;

whereby concepts assembled into a commonplace of information can be protected from disclosure and from being considered as having been published.

217. The adding and refining said commonplace of claim 211 to also provide multiple categorizations, further including:

a. creating at least one hierarchical association specific to a fxxt between a cnxpt becoming a category and another cnxpt becoming a member of the category;

b. positioning said cnxpt becoming a member of the category in a position depicting the logical relationship info-item between said cnxpts in a visualization of a fxxt according to said application software map generation means;

c. providing said cnxpt becoming a category for use in navigation such that a cnxpt related as a member of the category of said cnxpt becoming a category may be located; and

d. providing said information possibly relevant to a cnxpt related as a member of the category of said cnxpt becoming a category may be accessed through said cnxpt related as a member of the category;

whereby a classification structure catalog is developed and information found is added such that a user may access said information through a specific fxxt categorization providing an index of information.

218. The adding and refining said commonplace of claim 217 to determine a new extracted ontology from a combination of fxxt extraction results, wherein:

a. defining an ontology segmentation from a set of at least one association or cnxpt marked by a fxxt;

whereby a selection of associations and cnxpts is stated by a marking indicating potential membership in a fxxt, the potential resolved when determined by a fxxt extraction.

219. The adding and refining said commonplace of claim 218 to determine a new extracted ontology from a combination of fxxt extraction results, wherein:

a. determining a derived ontology from a fxxt extraction by evaluation of an equation having a fxxt as an operand;

b. naming the derived ontology with a temporary fxxt name;

whereby a selection of associations and cnxpts is stated by a membership function;

whereby an info-item included in said derived ontology is termed an included info-item, or more specifically an included association or included cnxpt.

220. The adding and refining said commonplace of claim 218, wherein:

a. determining membership of an info-item in the commonplace of information as a member in a set named by a fxxt;

b. naming the derived ontology with a temporary fxxt name;

whereby a set of general and specific cnxpts, relationships between cnxpts, and info-items is named and its elements indicated as members.

221. The adding and refining said commonplace of claim 218, wherein:

a. marking an info-item in the commonplace of information as a member in a set named by a fxxt defined by a resulting derived ontology;

b. naming the derived ontology with a temporary fxxt name;

whereby an arrangement of general and specific cnxpts is implemented where a general cnxpt is a categorization of more specific cnxpts, the user is given an ability to see ‘

nearly identical’

concepts in the arrangement as close together and dissimilar concepts distant from one another according to an extraction calculation to achieve a collocation objective;

whereby interest collection, audience segmentation, data arguing, and cleanup in curation are more efficient; and

whereby subtle differentials in meaning become obvious; and

whereby associative searching can be offered.

222. The interpreting said fxxt specification for said fxxt of claim 218, further including:

a. determining membership of an info-item in the commonplace of information in a set named by a fxxt;

b. determining membership of an info-item in the commonplace of information in a set named by an equation having a fxxt as an operand;

c. determining weighting for an info-item in the commonplace of information in a set derived from a fxxt;

d. summarizing info-items whereby weighted average summaries of info-item strengths are produced;

e. controlling fxxt specification interpretation, wherein said specification comprises step specifications selected from the group consisting of;

i. summarization steps,

ii. standard fxxt heuristic steps,

iii. base fxxt heuristic steps,

iv. base association fxxt heuristic steps,

v. simple fxxt extension steps,

vi. complex fxxt extension steps,

vii. fxxt generation steps, and

viii. interpreting metadata altering steps; and

f. re-summarizing info-items by weighted average summarization;

whereby basic fxxts are created or altered by marking cnxpts and associations to carry out said steps of a fxxt specification for map generation and derived ontologies are created and made ready for utilization.

223. The adding and refining said commonplace of claim 218 to also extract data sets, further including the following steps in the order named:

a. detailing a fxxt specification defining at least one said extraction to perform for said fxxt;

b. structuring said commonplace to extract content;

c. interpreting said fxxt specification for said fxxt to extract said fxxt from said commonplace by marking cnxpts and associations as members of said fxxt; and

d. packaging an extract data set;

whereby users may obtain subject matter data sets for specific purposes from said commonplace, a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification, and said contents of said extracted data set from said commonplace embodies a shareable information collection and a shareable analysis for data extraction toward a purpose.

224. The categorization of claim 217 to also form a visualization data set, further including the following steps in the order named:

a. detailing a fxxt specification defining said categorization to perform for said fxxt;

b. structuring said commonplace to extract content by marking relationships and cnxpts of said commonplace with fxxt identities;

c. interpreting said fxxt specification for said fxxt to extract said fxxt from said commonplace by including cnxpts and relationships found marked with said fxxt wherein if said fxxt specification includes steps said relationships or said cnxpts also pass the tests specified by said steps according to fxxt extraction means;

d. choosing visualization structuring propositional hierarchical associations from said marked associations of said fxxt to form spanning trees by generating hierarchical tensors that point specifically to at most one parent cnxpt in said fxxt to generate descendant tree forest according to fxxt descendant tree extraction means for tree extraction;

e. generating fxxt specific visualization positions for cnxpts for said fxxt by depth first ordering;

f. generating a visualization for display for said fxxt; and

g. utilizing said visualization;

such that classifications are derived from a relevant portion of said commonplace data, cnxpts and association relationships are marked as members of said fxxt, a forest of trees is formed and said cnxpts are positioned onto a visualization according to said structure provided by said descendant tree forest;

whereby users may obtain subject matter displays for specific purposes from said commonplace to more efficiently understand the contents of said commonplace, a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification and an extracted set of cnxpts are positioned in said visualization of said fxxt, said visualization produced has cnxpt members of said fxxt positioned in a taxonometric categorization of said fxxt with positioning based upon said associations involving said cnxpts and said strengths of said associations thus forming a classification harmonization from multiple classifications, said categorization visualization being navigable by said user for associative searching and serendipitous discovery, and said contents of said commonplace as shown in said visualization embody a shared information collection and a shared analysis for categorization.

225. The interpreting said fxxt specification for said fxxt of claim 223, further including:

a. determining if said fxxt specification is easily determined or not easily determined by checking each fxxt calculation step in said fxxt specification to determine if it is easily determined and if not, marking said fxxt specification as not easily determined;

b. interpreting, according to the process selected from the group consisting of;

i. if said fxxt specification is easily determined, developing said fxxt result interpreting said fxxt specification steps; and

extracting a fxxt descendant tree by generating hierarchical tensors based upon the effective weights of candidate relationships to form spanning trees; and

ii. if said fxxt specification is not easily determined, developing said fxxt result by interpreting base steps in a complex annealing fxxt specification consisting of;

01. triggering, if said fxxt specification is not easily determined, interpretation of a non-base fxxt calculation script step of said fxxt specification where a triggering event occur and a stated condition is met during tree extraction; and

02. extracting, if said fxxt specification is not easily determined, a fxxt descendant tree by generating hierarchical tensors based upon the effective weights of candidate relationships to form spanning trees from said extracted associations of said fxxt;

whereby the ability is provided to find and mark member cnxpts and associations by interpreting a fxxt specification, and to create weighted hierarchical tensors to point specifically to at most one parent cnxpt in said fxxt to provide for map generation.

226. The extracting of data sets of claim 223 to also form categorization data sets, further including the following steps in the order named:

a. detailing a fxxt specification defining at least one said categorization to perform for said fxxt;

b. structuring said commonplace to categorize an extracted data set;

c. interpreting said fxxt specification for said fxxt to mark hierarchical associations from associations in said extracted data set of said fxxt to form spanning trees by generating hierarchical tensors from child cnxpts that point specifically to at most one parent cnxpt in said fxxt to generate descendant tree forest according to fxxt descendant tree extraction means for tree extraction; and

d. packaging an extract data set containing said forest of trees for said fxxt;

whereby users may obtain augmented taxonomies of subject matter data sets for specific purposes from said commonplace, a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification, and said contents of said extracted data set from said commonplace embodies a shared information collection and a shared analysis for categorization.

227. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. generating a new 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 ontology derived from said first fxxt extraction or said second ontology derived from said second fxxt extraction, where a union Boolean set operation on a first ontology derived from a first fxxt extraction and a second ontology derived from a second fxxt extraction;

b. generating a new 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 both of said first ontology derived from said first fxxt extraction or said second ontology derived from said second fxxt extraction, where an intersection Boolean set operation on a first ontology derived from a first fxxt extraction and a second ontology derived from a second fxxt extraction;

c. generating a new 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 ontology derived from said first fxxt extraction or said second ontology derived from said second fxxt extraction, where an exclusive or Boolean set operation on a first ontology derived from a first fxxt extraction and a second ontology derived from a second fxxt extraction;

d. generating a new 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 the first but not in the second of said first ontology derived from said first fxxt extraction and said second ontology derived from said second fxxt extraction, where a set minus operation between a first ontology derived from a first fxxt extraction and a second ontology derived from a second fxxt extraction;

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

228. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if no second association was extracted by a second fxxt extraction between said first cnxpt and said second cnxpt, the new weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

b. setting the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the sum of the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the sum termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

229. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the coefficient of the first fxxt times the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if no second association was extracted by a second fxxt extraction between said first cnxpt and said second cnxpt, the new weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

b. setting the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the sum of the coefficient of the first fxxt times the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, the coefficient of the second fxxt times the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the sum termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

230. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the sum of the coefficient of the first fxxt times the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, the coefficient of the second fxxt times the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the sum then divided by the sum of the coefficient to normalize, the normalized sum termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

231. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting, where a fxxt-minus operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if no second association was extracted by a second fxxt extraction between said first cnxpt and said second cnxpt, the new weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

b. setting, where a fxxt-minus operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the difference between the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, and the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the difference termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

c. setting, where a fxxt-minus operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the negative of the weight of a second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, and no first association was extracted by a first extraction that was between said first cnxpt and said second cnxpt, the weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

232. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting, where a fxxt-times operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if no second association was extracted by a second fxxt extraction between said first cnxpt and said second cnxpt, the new weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

b. setting, where a fxxt-times operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the product between the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, and the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the difference termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

c. setting, where a fxxt-times operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the weight of a second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, and no first association was extracted by a first extraction that was between said first cnxpt and said second cnxpt, the weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

233. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. setting, where a fxxt-divide operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus, if no second association was extracted by a second fxxt extraction between said first cnxpt and said second cnxpt, the new weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

b. setting, where a fxxt-divide operation is evaluated in a fxxt equation and if both a first association was extracted by said first fxxt extraction between said first cnxpt and said second cnxpt and a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, the dividend from dividing the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the product between the weight of a first association extracted by said first fxxt extraction and between said first cnxpt and said second cnxpt plus by the weight of said second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt, the difference termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

c. setting, where a fxxt-divide operation is evaluated in a fxxt equation, the weight of the resultant association between said first cnxpt and said second cnxpt placed into the resultant derived ontology as the inverse of the weight of a second association extracted by said second fxxt extraction and between said first cnxpt and said second cnxpt plus, if a second association was extracted by said second fxxt extraction between said first cnxpt and said second cnxpt, and no first association was extracted by a first extraction that was between said first cnxpt and said second cnxpt, the weight termed the base set combination weight of the resultant association between said first cnxpt and said second cnxpt;

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

234. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. determining membership of a first association of a first fxxt between a first cnxpt and a second cnxpt by a fuzzy membership function, wherein said membership function indicates a 1 where said association is to be in the resulting ontology, or 0 if not;

whereby a set operation generates a new ontology with a temporary fxxt name, from a fuzzy selection.

235. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. determining membership of a first cnxpt of a first fxxt by a fuzzy membership function, wherein said membership function indicates a 1 where said cnxpt, termed an included cnxpt, is to be in the resulting ontology, or 0 if not;

b. determining membership of a first association of a first fxxt between a third cnxpt and a second cnxpt by a fuzzy membership function, wherein said membership function indicates a 1 where said association is to be in the resulting ontology and either said third cnxpt or said second cnxpt was an included cnxpt, or 0 if not;

whereby a set operation generates a new ontology with a temporary fxxt name, from a fuzzy selection of cnxpts and then associations.

236. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. determining membership of a first cnxpt of a first fxxt by a fuzzy membership function, wherein said membership function indicates a numeric value grade between 0 and 1 where said cnxpt, termed an included cnxpt, is to be in the resulting ontology when the grade is greater than a threshold given by a parameter, or 0 if not;

b. determining membership of a first association of a first fxxt between a third cnxpt and a second cnxpt by a fuzzy membership function, wherein said membership function indicates a 1 where said association is to be in the resulting ontology and either said third cnxpt or said second cnxpt was an included cnxpt and wherein said membership function indicates a numeric value grade between 0 and 1 for the association where said association, termed an included association, is to be in the resulting ontology when the grade is greater than a threshold given by a parameter, or 0 if not;

whereby a set operation generates a new ontology with a temporary fxxt name, from a fuzzy selection of cnxpts and then associations.

237. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. determining membership of a first cnxpt of a first fxxt by a fuzzy membership function, wherein said membership function indicates a numeric value grade between 0 and 1 where said cnxpt, termed an included cnxpt, is to be in the resulting ontology when the grade is greater than a threshold given by a parameter, or 0 if not;

b. determining a weight for said included cnxpt by multiplying the weight of the cnxpt included by said cnxpt grade;

c. determining membership of a first association of a first fxxt between a third cnxpt and a second cnxpt by a fuzzy membership function, wherein said membership function indicates a 1 where said association is to be in the resulting ontology and either said third cnxpt or said second cnxpt was an included cnxpt and wherein said membership function indicates a numeric value grade between 0 and 1 for the association where said association, termed an included association, is to be in the resulting ontology when the grade is greater than a threshold given by a parameter, or 0 if not;

d. determining a weight for said included association by multiplying the weight of the association included by said association grade;

whereby a set operation generates a new ontology with a temporary fxxt name, from a fuzzy selection of cnxpts and then associations with weighting, strength, or importance affected by fuzziness grading.

238. The method of claim 219 to determine a new extracted resultant ontology from an equation, wherein:

a. determining a numeric value grade between 0 and 1 for each weighted included info-item;

b. determining a weight for said included info-item by multiplying the weight of the info-item included by said info-item grade;

whereby a set operation generates a new ontology with a temporary fxxt name, from a fuzzy selection of cnxpts and then associations with weighting, strength, or importance affected by fuzziness grading.

239. The interpreting said fxxt specification for said fxxt of claim 222, further including:

a. interpreting access and retention steps;

b. interpreting weighting heuristic steps;

c. interpreting ordering heuristic steps;

d. interpreting ontology combination steps; and

e. interpreting fxxt combination steps;

whereby the ability is provided to mark cnxpts and associations to be in said fxxt by interpreting said fxxt specification script steps and derived ontologies are created and made ready for utilization.

241. The adding and refining said commonplace of claim 1 to act upon the information, further including:

a. accepting and processing zero or more user commands according to low level procedure models for use cases process means, said command selected from the group consisting 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;

b. such that any addition, change, or deletion may affect stigmergy and is an addition of wisdom affecting said consensus;

whereby a user may add and refine the information of said commonplace manually and search to locate collected wisdom.

242. The adding and refining said commonplace of claim 241 to search for wisdom, wherein:

a. searching by a search method to find wisdom to ingest based upon strategy, said search method selected from the group consisting of;

i. searching by continuous background crawling of web pages to obtain high thoroughness results at low cost and low quality of data results;

ii. searching by continuous background crawling of documents to obtain high thoroughness results at low cost of document stores;

iii. searching by background accessing of databases to obtain high thoroughness results at low cost to synchronize with databases for structure and categorization by external marking and to ingest data;

iv. searching continuously by search query specification re-execution to obtain high thoroughness results at low cost and high quality of results;

v. searching by background crawling of any external commonplace of wisdom by search query specification re-execution with reapplication of prior culling to obtain high thoroughness results at low cost and high quality of 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 high thoroughness results at low cost and high quality of 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 can or should be, do, appear, occur, perform, assembled, fit in, or participate, said binding point for attachment of purlieu characterizing the when, ordering, or duration said conceptual meaning can or should be relevant to, said elements selected from the group consisting of;

word, phrase, string, 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 represented by a fxxt and formed due to interpretation of a fxxt specification, to impart from said context of said fxxt and a user'"'"'s acceptance of the relevance of results after culling from within said context of said fxxt to said result of said search the contextualization information from the criteria specifying the fxxt, the context within the organization of knowledge of the visualization tree to improve usability for cataloging by utilizing;

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. updating fxxts 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;

xiv. searching for categorization structure information to improve ability to discriminate between concepts by more specific differentiation by category;

xv. searching within a domain of wisdom already extracted by navigating to find more specific wisdom; and

xvi. 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 based upon strategy, said refinement method selected from the group consisting 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 a visualization 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. 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 consisting of;

i. forming a navigable visualization to ease understanding of contained conceptual structures as a catalog of topical information;

ii. cataloging information resources after culling;

iii. forming a differentiation between two concepts represented by cnxpts by associating different concepts embodied in results referenced;

iv. 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;

v. forming a differentiation between two concepts represented by cnxpts by associating different concepts embodied in results referenced;

vi. 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

vii. 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;

whereby a user may choose a set of sources of conceptual wisdom and an organizational structuring and criteria for concepts to be included and obtain viewable and understandable mapping by concept and, if available and utilized, a further organization by modeling calculation results such as for precedence or Bayesian prediction, and be assured that results found are thorough, include their past refinements, and the wisdom of the crowds.

249. The request a search for wisdom of claim 241, by executing stored instructions that perform operations to cause the computer system to locate wisdom sought, further including:

a. providing a plurality of procedures to locate wisdom;

b. activating at least one procedure to locate wisdom;

c. providing a plurality of procedures to accept search criteria to locate wisdom;

d. activating at least one procedure to accept search criteria to locate wisdom;

e. determining a first domain as a default domain of wisdom by performing at least one action selected from the group consisting of;

i. determining a first domain as including the commonplace without regard to fxxt data or specification interpretation;

ii. determining a first domain as prescribed by a system parameter;

iii. determining a first domain as prescribed by a setting in a user profile;

iv. determining a first domain as prescribed by a search query specification; and

v. determining a first domain as represented by a fxxt that is identified in said commonplace;

f. determining zero or more second domains each represented by a fxxt identified in said commonplace such that said second domain is available for use as a second default domain in searches as a second organization of knowledge where said search requires one or more second domains;

g. accepting zero or more commands to select a first and zero or more second domains of wisdom, such that said first default domain of wisdom is selected as first domain of wisdom if no command of this type is entered before entering a command to select a cntexxt, such that said second default domain of wisdom is selected as a second domain of wisdom if no command of this type is entered before entering a command to select a cntexxt, said zero or more commands to select said first domain of wisdom in a specification form selected from the group consisting of;

i. initiation of user session causing a first display of information based upon said default domain of wisdom;

ii. implicit acceptance of current domain selection;

iii. user entered domain selection command; and

iv. search query specification step specification;

said zero or more commands to select each second domain of wisdom in a specification form selected from the group consisting of;

v. user entered domain selection command; and

vi. search query specification step specification;

said zero or more commands to select said and zero or more second domains of wisdom selected from the group consisting of;

vii. selecting a default domain of wisdom;

viii. accepting a domain of wisdom automatically chosen from a prioritized list of domains of wisdom, a default domain of wisdom, such default domain of wisdom referring to a fxxt used to construct such domain of wisdom;

ix. selecting from a list of domains of wisdom to choose an organization of knowledge or an alternative organization of knowledge, such choice to become the new organization of knowledge, such choice to referring to a fxxt used to construct such domain of wisdom;

x. selecting from a list of domains of wisdom resulting from accepting a text string such that the string is matched against the names of domains of wisdom available to narrow the list of domains to choose from for an alternative organization of knowledge according to term search on info-item names descriptions process means, such choice to become the new organization of knowledge, such choice to referring to a fxxt used to construct such domain of wisdom;

xi. selecting from a list of domains of wisdom resulting from accepting a text string such that the string is matched against the descriptive information available for each domain of wisdom available to narrow the list of domains to choose from for an alternative organization of knowledge according to term search on info-item names descriptions process means, such choice to become the new organization of knowledge, such choice to referring to a fxxt used to construct such domain of wisdom;

xii. accepting, from a list of fxxts, a default fxxt to be used in constructing an organization of knowledge;

xiii. selecting, from a list of fxxts resulting from accepting a text string such that the string is matched against the names of fxxts in the list to narrow the list of fxxts, a fxxt for constructing an organization of knowledge;

xiv. selecting, from a list of fxxts resulting from accepting a text string such that the string is matched against the descriptive information of fxxts in the list to narrow the list of fxxts, a fxxt for constructing an organization of knowledge; and

xv. selecting, from a list of fxxts, said list ordered as a result from scoring a text string accepted from said user said score determined from an analytic plug-in detecting the nature of problem said user is addressing in said text string such that said fxxt list contains a plurality of candidate fxxts whose specification indicates the nature of problem that said candidate fxxt is useful for, a fxxt for constructing an organization of knowledge;

wherein interpretation of said fxxt'"'"'s specification defines a domain of wisdom having a set of cnxpts having at least one cnxpt as a member, such choice to be organized into an organization of knowledge;

h. constructing an organized and presentable display vehicle expose knowledge in an understandable fashion to a user, for each said first or said second domain of knowledge, from an extracted spanning forest of cnxpts and interrelationships where each of said cnxpts are taken as categories and arranged based upon said summary relationships in an organization of knowledge from said first or said second domain of wisdom selected according to visualization processes means and utilize collective consensus through vote tallying and map generation process means, wherein each category of said organization of knowledge relates a context for concepts, wherein the contexts are generally nearer one another where their contents relate to one-another more strongly, wherein the contexts are generally farther apart when their contents do not relate as strongly to one-another, wherein each such context generally regards a concept that is represented by a cnxpt, said context known as a cntexxt defined by said cnxpt, said cntexxt possibly abstract but representable;

i. determining a default first cnxpt such that said default first cnxpt is presented as the cntexxt focused on in said first organization of knowledge;

j. presenting said first organization of knowledge to said user;

k. determining a default second cnxpt such that said default second cnxpt is presented as the cntexxt focused on in said second organization of knowledge whether or not presented;

l. presenting said zero or one second organization of knowledge as needed;

m. accepting zero or more cnxpt locating commands, with any stated additional specification, said additional specification stating zero or more values, weights, parameters, structures, objects, analytics, or degrees of fuzziness, to select a subsequent first cnxpt presented as a subsequent cntexxt of wisdom according to one or more process means selected from the group consisting of;

i. ideation process means;

ii. finding searching query and retrieval process means;

iii. goal based searching process means;

iv. selection set management process means;

v. focus on information process means; and

vi. alter information through visualization process means;

such that said default first cnxpt within said organization of knowledge is to be presented as the subsequent cntexxt if no cnxpt locating command is entered before entering a command to act upon the subsequent cntexxt of wisdom, said zero or more cnxpt locating commands selected from the group consisting of;

vii. selecting by default said default first cnxpt such that the cntexxt represented by said first cnxpt is presented as the subsequent cntexxt;

viii. stating in a search query specification step specification a first cnxpt;

ix. choosing from a list of cnxpts an alternative first cnxpt, said list determined by listing all said cnxpts in said domain of wisdom, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt;

x. choosing from a list of cnxpts an alternative first cnxpt by initiating a finding query, said list determined by accepting a text string such that said string is matched against the names of all said cnxpts in said domain of wisdom to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt;

xi. choosing from a list of cnxpts an alternative first cnxpt, said list determined by accepting a text string such that said string is matched against the descriptive information stored for each cnxpt of all said cnxpts in said domain of wisdom to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt;

xii. choosing from a list of cnxpts an alternative first cnxpt, said list determined by listing all root cnxpts in said domain of wisdom, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt;

xiii. navigating to a cntexxt chosen from all said cntexxts in said domain of wisdom according to visualization navigation process means by navigating around said visualization such that a choice is made of new first cnxpt as that cnxpt presented as the destination cntexxt;

xiv. 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 presented as the subsequent cntexxt if chosen cnxpt is in said first organization of knowledge or a new second cnxpt presented as the subsequent cntexxt in an alternative visualization presenting said second organization of knowledge if chosen cnxpt is not in said first organization of knowledge;

xv. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a search query according to searching process means resulting in a list of cnxpts to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt if chosen cnxpt is in said first organization of knowledge or a new second cnxpt presented as the subsequent cntexxt in an alternative visualization presenting said second organization of knowledge if chosen cnxpt is not in said first organization of knowledge;

xvi. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to querying process means resulting in a list of cnxpts to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt if chosen cnxpt is in said first organization of knowledge or a new second cnxpt presented as the subsequent cntexxt in an alternative visualization presenting said second organization of knowledge if chosen cnxpt is not in said first organization of knowledge;

xvii. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a goal search query according to search with goal process means resulting in a list of cnxpts to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt if chosen cnxpt is in said first organization of knowledge or a new second cnxpt presented as the subsequent cntexxt in an alternative visualization presenting said second organization of knowledge if chosen cnxpt is not in said first organization of knowledge;

xviii. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to querying process means a search query intended to result in a list containing a plurality of cnxpts having an identity indicator, characteristic value, trait, purlieu, or keyword meeting criteria given by said additional specification and resulting in a list of cnxpts to narrow the possibilities to said list of cnxpts, such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt if chosen cnxpt is in said first organization of knowledge or a new second cnxpt presented as the subsequent cntexxt in an alternative visualization presenting said second organization of knowledge if chosen cnxpt is not in said first organization of knowledge; and

xix. choosing from a list of cnxpts an alternative cnxpt, said list determined by accepting and processing a query according to querying process means a search query intended to result in a list containing a plurality of cnxpts having an identity indicator, characteristic value, trait, purlieu, or keyword meeting criteria given by said additional specification and resulting in a list of cnxpts to narrow the possibilities to said list of cnxpts, such choice added to said first organization of knowledge in not already in said first organization of knowledge, and such choice replacing any prior cnxpt as the new first cnxpt presented as the subsequent cntexxt in said first organization of knowledge;

such that said subsequent cntexxt is further defined by the set of cnxpts that are children of said first cnxpt within the structure of said organization of knowledge, such that said set of cnxpts that are children of said first cnxpt within the structure of said organization of knowledge are considered to be in said subsequent cntexxt;

n. repositioning said organization of knowledge to a single concept selected from the group consisting of;

said subsequent cntexxt and said default cntexxt represented by said default cnxpt;

o. 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;

said first form of result selected from the group consisting of;

viii. an empty set;

ix. a default set;

x. an avatar;

xi. a commonality;

xii. a conceptual meaning by a repositioning;

xiii. a deal made;

xiv. a decision made;

xv. a directory listing;

xvi. a fxxt extraction invocation;

xvii. a goal;

xviii. a link;

xix. a methodology action;

xx. a plug-in;

xxi. a portfolio entry;

xxii. a registration made;

xxiii. a relationship info-item;

xxiv. a resolved link;

xxv. a result of a model invocation;

xxvi. a result of a prediction;

xxvii. a result of a workflow invocation;

xxviii. a scalar;

xxix. a single item result;

xxx. a specification;

xxxi. a step in a specification;

xxxii. a taxonomy;

xxxiii. a template;

xxxiv. a transaction;

xxxv. a value of a characteristic of an info-item;

xxxvi. a value of a property of an info-item;

xxxvii. a vote made;

xxxviii. a vote;

xxxix. an alert;

xl. an event;

xli. an identity indicator of an info-item;

xlii. an info-item;

xliii. an information resource;

xliv. an intermediate or final result of processing a specification of an info-item having a specification for processing;

xlv. an invocation of a step of a specification of an info-item having a specification for processing;

xlvi. an item of a result set;

xlvii. an outcome;

xlviii. information;

xlix. a collaboration blog list;

l. a crawl;

li. a data set;

lii. a directed graph;

liii. a directory;

liv. a forest of trees;

lv. a graph;

lvi. a list for picking a selection of a what appears to the user as a good choice according to said user'"'"'s own criteria;

lvii. a list;

lviii. a pair tuple or pairing;

lix. an ordered pair tuple or pairing;

lx. a product catalog;

lxi. a result set map;

lxii. a portfolio map;

lxiii. a portfolio;

lxiv. a result of an analytic invocation;

lxv. a result set list;

lxvi. a result set;

lxvii. a timeline;

lxviii. a timeline ordered area of consideration of cnxpt info-items;

lxix. a timeline ordered area of interest of cnxpt info-items;

lxx. a timeline ordered result set;

lxxi. a timeline ordered list;

lxxii. a timeline ordered graphical composite of durations;

lxxiii. a transaction list;

lxxiv. an area of consideration of cnxpt info-items;

lxxv. an area of interest of cnxpt info-items;

lxxvi. a selection set;

lxxvii. a set;

lxxviii. a sub-tree;

lxxix. a tracking history of an item of a consortium;

lxxx. a tree;

lxxxi. an ordered list;

lxxxii. an ordered result set list;

lxxxiii. a descendant tree formed according to fxxt descendant tree extraction process means;

lxxxiv. a descendant forest formed according to fxxt descendant tree extraction process means;

lxxxv. an ascendant tree formed according to calculate ascendant trees process means;

lxxxvi. an ascendant tree forest formed according to calculate ascendant trees process means;

lxxxvii. a result of a fxxt extraction according to fxxt calculation script interpretation process means;

lxxxviii. 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;

lxxxix. 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;

xc. 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;

xci. a map based upon positioning of cnxpts within an area formed according to set or area map generation process means;

xcii. a map based upon positioning of cnxpts within an area formed according to fxxt specific ttx map generation process means;

xciii. a predictive map formed according to fxxt specific ttx map generation and predictive intelligence process means;

xciv. a workflow task map formed according to fxxt specific ttx map generation process means;

xcv. a process flow map formed according to fxxt specific ttx map generation process means;

xcvi. a methodology step map formed according to fxxt specific ttx map generation process means;

xcvii. a portfolio expected monetary value map formed according to fxxt specific ttx map generation and primary predictions process means;

xcviii. a timeline event formed according to fxxt specific ttx map generation process means;

xcix. a methodology step map formed according to fxxt specific ttx map generation process means;

c. a 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;

ci. 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;

cii. 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;

ciii. 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;

civ. 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;

cv. 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;

cvi. 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;

cvii. 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; and

cviii. a default form of result based upon the type of requested search;

p. 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. a null result;

ii. a result defined by a search analytic;

iii. alert information;

iv. analytic information;

v. associative position information navigation;

vi. conceptual interrelationship info-item information;

vii. entity similarity information;

viii. business decision information;

ix. business growth progress information;

x. business transaction information;

xi. categorization information;

xii. characteristic information;

xiii. commonality information;

xiv. competitive product information;

xv. concept similarity information;

xvi. consortium artifact information;

xvii. consortium information;

xviii. contract transaction information;

xix. crawl result information;

xx. data availability and sales information;

xxi. goal information;

xxii. how-to information about invention;

xxiii. how-to information about invention protection;

xxiv. how-to information about innovative business growth;

xxv. info-item information;

xxvi. information resource information;

xxvii. interest shown by users;

xxviii. satisfaction shown by users;

xxix. information about experts;

xxx. information about participants;

xxxi. investment information;

xxxii. investment opportunity information;

xxxiii. investment pool information;

xxxiv. investment diligence and vetting information;

xxxv. legal case information;

xxxvi. legal case strategy information;

xxxvii. legal discovery status information;

xxxviii. legal discovery relevance information;

xxxix. legal information;

xl. legal precedent information;

xli. methodology information;

xlii. communal mind mapping consensus information;

xliii. model information;

xliv. negotiation process tracking information;

xlv. occurrence information;

xlvi. opinion information;

xlvii. outline construction information;

xlviii. patent clearance process information;

xlix. patent clearance exposure information;

l. plug-in information;

li. portfolio entry information;

lii. portfolio information;

liii. portfolio transaction information;

liv. prediction information;

lv. process analysis information;

lvi. process control information;

lvii. product design information;

lviii. product control information;

lix. product longevity information;

lx. project control information;

lxi. property information;

lxii. purlieu information;

lxiii. registration information;

lxiv. relationship info-item information;

lxv. research study information;

lxvi. result set information;

lxvii. statistical analysis information;

lxviii. subscription and usage information;

lxix. survey information;

lxx. template information;

lxxi. trait information;

lxxii. transaction information;

lxxiii. workflow information;

lxxiv. a cnxpt info-item satisfying criteria;

lxxv. a conceptual meaning;

lxxvi. a consortium info-item;

lxxvii. a crawl result;

lxxviii. a deal made in a consortium transaction;

lxxix. a deal made in a portfolio transaction;

lxxx. a deal made in an investment pool transaction;

lxxxi. a decision made in a consortium business decision;

lxxxii. a decision made in a portfolio business decision;

lxxxiii. a decision made in an investment pool business decision;

lxxxiv. a differentiator;

lxxxv. a discovery objective;

lxxxvi. a fact to rule applicability ordered pair of cnxpt info-items;

lxxxvii. a law info-item;

lxxxviii. a legal charge theory of the case info-item;

lxxxix. a legal doctrine or principle info-item;

xc. a legal fact info-item;

xci. a legal general rule info-item;

xcii. a legal jurisdiction info-item;

xciii. a legal precedent info-item;

xciv. a legal rule element info-item;

xcv. a legal rule info-item;

xcvi. a legal theory of the case info-item;

xcvii. a link cited in an attached occurrence in said organization of knowledge;

xcviii. a methodology info-item;

xcix. a model info-item;

c. a modeling result;

ci. a participant info-item in a consortium;

cii. a precedent successor dependency ordered pair of cnxpt info-items;

ciii. a prediction outcome info-item;

civ. a prediction outcome value;

cv. a prediction;

cvi. a property of a type of interest shown;

cvii. a property of a type of interest shown;

cviii. a property of an info-item;

cix. a purlieu;

cx. a query;

cxi. a registration;

cxii. a relationship info-item meaning;

cxiii. a role of a consortium;

cxiv. a set of matching pairings;

cxv. a set of applicability pairings;

cxvi. a set of dependency pairings;

cxvii. a specific rule;

cxviii. a step in a fxxt specification info-item;

cxix. a step of a specification of an info-item having a specification for processing;

cxx. a study info-item;

cxxi. a study objective;

cxxii. a study result;

cxxiii. a subscription;

cxxiv. a survey result;

cxxv. a task info-item in a timeline of a workflow;

cxxvi. a task info-item of a methodology;

cxxvii. a task info-item of a workflow;

cxxviii. a theory, principle, or law of science info-item;

cxxix. a tracked info-item of a consortium;

cxxx. a trait of an info-item;

cxxxi. a transaction result;

cxxxii. a type of connected relationship;

cxxxiii. a type of interest shown;

cxxxiv. a type of relationship info-item;

cxxxv. a vote result;

cxxxvi.a workflow info-item;

cxxxvii. an information resource reference info-item;

cxxxviii. an investment pool info-item;

cxxxix. an item of a blog;

cxl. an item of a commonality;

cxli. an item of a crawl result;

cxlii. an item of a pool info-item;

cxliii. an item of a portfolio info-item;

cxliv. an item of a subscription;

cxlv. an item of a transaction;

cxlvi. an occurrence info-item;

cxlvii. an opinion info-item;

cxlviii. an event info-item in a timeline of a workflow;

cxlix. an evidence info-item;

cl. an identifiable product of a task of a methodology;

cli. an identity indicator an item of a portfolio;

clii. an identity indicator of a child in said organization of knowledge;

cliii. an identity indicator of a commonality;

cliv. an identity indicator of a consortium info-item;

clv. an identity indicator of a crawl result;

clvi. an identity indicator of a crawl specification info-item;

clvii. an identity indicator of a descendent in said organization of knowledge;

clviii. an identity indicator of a descendent leaf in said organization of knowledge;

clix. an identity indicator of a fxxt info-item;

clx. an identity indicator of a goal info-item;

clxi. an identity indicator of a methodology info-item;

clxii. an identity indicator of a model info-item;

clxiii. an identity indicator of a parent in said organization of knowledge;

clxiv. an identity indicator of a participant info-item in a consortium info-item;

clxv. an identity indicator of a plug-in;

clxvi. an identity indicator of a pool info-item;

clxvii. an identity indicator of a portfolio info-item;

clxviii. an identity indicator of a prediction info-item;

clxix. an identity indicator of a query specification info-item;

clxx. an identity indicator of a registration;

clxxi. an identity indicator of a result set;

clxxii. an identity indicator of a role info-item of a consortium info-item;

clxxiii. an identity indicator of a sibling in said organization of knowledge;

clxxiv. an identity indicator of a step in a fxxt specification;

clxxv. an identity indicator of a step of a methodology info-item;

clxxvi. an identity indicator of a step of a model specification info-item;

clxxvii. an identity indicator of a step of a prediction specification info-item;

clxxviii. an identity indicator of a step of a query specification info-item;

clxxix. an identity indicator of a step of a workflow info-item;

clxxx. an identity indicator of a subscription specification;

clxxxi. an identity indicator of a task info-item in a timeline of a workflow info-item;

clxxxii. an identity indicator of a task info-item of a methodology info-item;

clxxxiii. an identity indicator of a task info-item of a workflow info-item;

clxxxiv. an identity indicator of a tracked item of a consortium info-item;

clxxxv. an identity indicator of a transaction info-item;

clxxxvi. an identity indicator of a type of interest shown;

clxxxvii. an identity indicator of a workflow info-item;

clxxxviii. an identity indicator of an alert info-item;

clxxxix. an identity indicator of an analytic;

cxc. an identity indicator of an ancestor in said organization of knowledge;

cxci. an identity indicator of an ancestor root in said organization of knowledge;

cxcii. an identity indicator of an attached occurrence in said organization of knowledge;

cxciii. an identity indicator of an avatar info-item;

cxciv. an identity indicator of an event info-item in a timeline of a workflow info-item;

cxcv. an identity indicator of an info-item connected by relationship info-item in said organization of knowledge;

cxcvi. an identity indicator of an information resource referenced in an attached occurrence info-item in said organization of knowledge;

cxcvii. an identity indicator of an item of a blog;

cxcviii. an identity indicator of an item of a commonality specification;

cxcix. an identity indicator of an item of a crawl result;

cc. an identity indicator of an item of a pool;

cci. an identity indicator of an item of a result set;

ccii. an identity indicator of an item of a subscription;

cciii. an identity indicator of an item of a transaction;

cciv. an identity indicator value;

ccv. a list of alerts;

ccvi. a list of analytics;

ccvii. a list of avatars;

ccviii. a list of characteristic or property information regarding an info-item;

ccix. a list of characteristics;

ccx. a list of cnxpt info-items;

ccxi. a list of commonalities;

ccxii. a list of conceptual meanings;

ccxiii. a list of consortium info-items;

ccxiv. a list of crawl info-items;

ccxv. a list of crawl results;

ccxvi. a list of decisions made;

ccxvii. a list of decisions needed;

ccxviii. a list of differentiators;

ccxix. a list of fxxt info-items;

ccxx. a list of goal info-items;

ccxxi. a list of identity indicators;

ccxxii. a list of info-items;

ccxxiii. a list of information resource reference info-items;

ccxxiv. a list of information resources;

ccxxv. a list of items of a result set;

ccxxvi. a list of items of a set of crawl results;

ccxxvii. a list of items of a set of pools;

ccxxviii. a list of items of a set of portfolios;

ccxxix. a list of items of a subscription;

ccxxx. a list of items of a transaction;

ccxxxi. a list of items of blogs;

ccxxxii. a list of items of commonalities;

ccxxxiii. a list of links;

ccxxxiv. a list of methodology info-items;

ccxxxv. a list of model info-items;

ccxxxvi. a list of occurrence info-items;

ccxxxvii. a list of outcome info-items;

ccxxxviii. a list of outcomes possible;

ccxxxix. a list of pairs of cnxpt dependencies;

ccxl. a list of pairs of cnxpts matching by applicability;

ccxli. a list of pairs of cnxpts matching by interest;

ccxlii. a list of pairs of cnxpts matching by suitability;

ccxliii. a list of pairs of cnxpts matching by theory, principle, or law of science;

ccxliv. a list of pairs of cnxpts matching by trait;

ccxlv. a list of pairs of cnxpts matching semantically;

ccxlvi. a list of participant info-items in a list of consortium info-items;

ccxlvii. a list of plug-ins;

ccxlviii. a list of pool info-items;

ccxlix. a list of portfolio info-items;

ccl. a list of precedent successor dependency pairs of cnxpts;

ccli. a list of prediction info-items;

cclii. a list of properties of types of interest shown;

ccliii. a list of properties;

ccliv. a list of purlieu;

cclv. a list of queries;

cclvi. a list of registrations;

cclvii. a list of relationships;

cclviii. a list of result sets;

cclix. a list of roles of consortiums;

cclx. a list of steps in fxxts;

cclxi. a list of steps of a specification of an info-item having a specification for processing;

cclxii. 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;

cclxiii. a list of steps of methodologies;

cclxiv. a list of steps of models;

cclxv. a list of steps of predictions;

cclxvi. a list of task info-items of a specification of an info-item having a specification stating actions to be taken by a user;

cclxvii. a list of tasks in timelines of workflows;

cclxviii. a list of tasks of a set of methodologies;

cclxix. a list of tasks of a set of workflows;

cclxx. a list of tracked items of consortiums;

cclxxi. a list of traits;

cclxxii. a list of transactions;

cclxxiii. a list of types of interest shown;

cclxxiv. a list of types of relationships;

cclxxv. a list of workflows;

cclxxvi. a pair of cnxpts matching by interest;

cclxxvii. a pair of cnxpts matching by suitability;

cclxxviii. a pair of cnxpts matching by theory, principle, or law of science;

cclxxix. a pair of cnxpts matching by trait;

cclxxx. a pair of cnxpts matching semantically;

cclxxxi. a metric ordered area of consideration of cnxpts;

cclxxxii. a metric ordered area of interest of cnxpts;

cclxxxiii. a metric ordered result set;

cclxxxiv. an ordered pair of cnxpts matching by suitability of evidence to discovery objective;

cclxxxv. an ordered pair of cnxpts matching by suitability of evidence to fact;

cclxxxvi. an ordered pair of cnxpts matching by suitability of fact to rule element;

cclxxxvii. an ordered pair of cnxpts matching by suitability of function to audience;

cclxxxviii. an ordered pair of cnxpts matching by suitability of function to need;

cclxxxix. an ordered pair of cnxpts matching by suitability rule to jurisdiction;

ccxc. an ordered pair of cnxpts matching semantically;

ccxci. a result of a fxxt specification;

ccxcii. a result of a model specification;

ccxciii. a result of a workflow specification;

ccxciv. a result set of pairs of cnxpts matching by interest;

ccxcv. a result set of pairs of cnxpts matching by suitability;

ccxcvi. a result set of pairs of cnxpts matching by theory, principle, or law of science;

ccxcvii. a result set of pairs of cnxpts matching by trait;

ccxcviii. a result set of pairs of cnxpts matching semantically;

ccxcix. a result set of precedence dependency pairs of cnxpts;

ccc. an action triggered by said search;

ccci. an action defined by a search analytic triggered by said search;

cccii. an event triggered by said search;

ccciii. an event defined by a search analytic triggered by said search;

ccciv. 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;

cccv. 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;

cccvi. 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;

cccvii. 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;

cccviii. 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;

cccix. 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;

cccx. 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;

cccxi. 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;

cccxii. 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;

cccxiii. 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;

cccxiv. 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;

cccxv. 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;

cccxvi. 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;

cccxvii. 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;

cccxviii. 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;

cccxix. a 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 descendant 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;

cccxx. 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 descendant 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;

cccxxi. 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 descendant 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;

cccxxii. 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 descendant 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;

cccxxiii. 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 descendant 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;

cccxxiv. 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 descendant 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;

cccxxv. 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 descendant 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

cccxxvi. a 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 descendant 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;

q. 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;

r. 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 descendant 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 a info-item property;

xxv. a value of the form of a 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 a info-item characteristic identifier;

xxx. a value of the form of a 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;

s. 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 a 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, practice, field, jurisdiction, purlieu, trait, law, author, subject, fact, opinion, doctrine, study, study result, lab test report, evidence item, documentary evidence, theory, 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 theory, principal, law, and practice time frames wherein a theory, principal, law, or practice 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 theory, principal, law, or practice relationships to said first cnxpt and said second cnxpt to be added into the result, a theory, principal, law, or practice 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 theory, principal, law, or practice 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 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 theory, principal, law, and practice time frames, a theory, principal, law, or practice pertinent to both said first and said second cnxpts, 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 said theory, principal, law, or practice relationship info-item timeframes, said theory, principal, law, or practice relationship info-item timeframe 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 said theory, principal, law, or practice relationship info-item timeframe, wherein a weight based upon a specified coefficient times the absolute value of the differential of the pertinence of said theory, principal, law, or practice relationship info-item timeframe in said first cnxpt divided by the signed number of standard deviations from the center of said theory, principal, law, or practice relationship info-item timeframe of said first cnxpt'"'"'s gestation and the pertinence of said theory, principal, law, or practice relationship info-item timeframe in said second cnxpt divided by the number of standard deviations from the center of said theory, principal, law, or practice relationship info-item timeframe 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 theory, principal, law, or practice relationship info-item timeframes in said organization of knowledge;

76. 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 factors selected from the group consisting of;

relationships in common and not in common, characteristics in common and not in common, occurrences in common and not in common, cited occurrences in common, commonalities, traits in common and not in common, theory, principal, law, or practice relationships in common and not in common, and purlieu in common and not in common, said overall score providing a metric for similarity according to a weighted averaging of similarities;

77. wherein said second cnxpt is closer in meaning to the meaning given by a definition of a goal based upon a score value determined by a specified weighted averaging of similarity criteria factors selected from the group consisting of;

relationships in common and not in common, characteristics in common and not in common, occurrences in common and not in common, cited occurrences in common, commonalities, traits in common and not in common, theory, principal, law, or practice relationships in common and not in common, and purlieu in common and not in common, said overall score providing a metric for similarity according to a weighted averaging of similarities, said second cnxpt found, if at all, from the items of said first identified search base if specified or from the organization of knowledge if no first identified search base is specified;

78. 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;

79. wherein said second cnxpt has a relationship info-item with a stated theory, principal, law, or practice, wherein said timeline is formed by ordering conceptual meanings by a time point associated with said theory, principal, law, or practice, said time point selected from the group consisting of;

initial recognition of theory, principal, law, or practice, mid-point, point at which said theory, principal, law, or practice is anticipated to become obsolete, point at which products based upon said theory, principal, law, or practice are anticipated to be altered or replaced to conform to new theory, principal, law, or practice, median of distribution, mean of distribution, and any other specified theory, principal, law, or practice summarizer, wherein said theory, principal, law, or practice is a member of said first identified search base if specified or from the set of all theories, principals, laws, or practices in said organization of knowledge if no first identified search base is specified;

80. 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;

81. wherein said second cnxpt has a relationship info-item with a stated theory, principal, law, or practice, wherein said timeline is formed by ordering conceptual meanings by a time point associated with said theory, principal, law, or practice, said time point selected from the group consisting of;

initial recognition of theory, principal, law, or practice, mid-point, point at which said theory, principal, law, or practice is anticipated to become obsolete, point at which products based upon said theory, principal, law, or practice are anticipated to be altered or replaced to conform to new theory, principal, law, or practice, median of distribution, mean of distribution, and any other specified theory, principal, law, or practice summarizer, wherein said theory, principal, law, or practice is a member of said first identified search base if specified or from the set of all theories, principals, laws, or practices in said organization of knowledge if no first identified search base is specified;

82. wherein said second cnxpt is of a type having a property stating a point value or 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;

83. 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;

84. wherein said second cnxpt is of a type having relationships with info-items having a property stating a point value or 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;

85. wherein said second cnxpt is of a type having relationships with info-items having a property stating a point value or 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 point value or 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;

86. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a point value or 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 point value or 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;

87. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a point value or 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 point value or 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;

88. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a point value or 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 point value or 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;

89. wherein said second cnxpt is of a type having relationships with fourth cnxpts having a property stating a point value or 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 point value or 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;

90. 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;

91. 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;

92. 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;

93. 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;

94. 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;

95. 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;

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 temporal ordering, said relationship info-item of a type 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 temporal ordering, said relationship info-item of a fxxt 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 logically exist, 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 logically exist, 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, 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;

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, 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;

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 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;

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 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;

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 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;

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 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;

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 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;

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 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;

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 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;

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 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;

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 implementation against theory, principle, or law of science 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 to science match relationships 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 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;

112. 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;

113. 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;

114. 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;

115. 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;

116. 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;

117. 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;

118. 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;

119. 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;

120. 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 of evidence items against fact, according to heuristic analytics, 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;

121. 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 of facts against rule element;

122. 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 element to rule dependency relationships based upon an optionally specified doctrine specified in said additional specification, and an optionally specified jurisdiction specified in said additional specification;

123. 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 specific rule to jurisdiction'"'"'s law dependency relationships, and limiting by an optionally specified general rule specified in said additional specification, an optionally specified doctrine specified in said additional specification, and an optionally specified jurisdiction specified in said additional specification;

124. 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 specific rule to general rule dependency relationships based upon an optionally specified doctrine specified in said additional specification, and an optionally specified jurisdiction specified in said additional specification;

125. 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 precedent to rule dependency relationships based upon an optionally specified rule specified in said additional specification, and an optionally specified jurisdiction specified in said additional specification;

126. 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 rule to doctrine dependency relationships based upon an optionally specified doctrine specified in said additional specification, and an optionally specified jurisdiction specified in said additional specification;

127. 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 evidence case issue dependency relationships based upon a specified evidence set specified in said additional specification;

128. 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 rule charge theory dependency relationships based upon a specified rule set specified in said additional specification; and

129. 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 fact theory of the case dependency relationships based upon a specified fact set specified in said additional specification;

liv. requesting methodology, workflow, or task information based upon said first identified search base, such that one or more items in said first identified search base relate to methodology, workflow, or task information;

lv. requesting collaboration task or event information based upon said first identified search base, such that one or more items in said first identified search base relate to collaboration task or event information;

lvi. requesting collaboration ecosystem mechanism information based upon said first identified search base, such that one or more items in said first identified search base relate to collaboration ecosystem information;

lvii. requesting opportunity information based upon said first identified search base, such that one or more items in said first identified search base relate to opportunity information;

lviii. requesting a list of methodologies or workflows relevant to said domain each showing how to think about a problem or circumstance, what is needed to accomplish a task or solve a problem, how to prepare to accomplish a task or solve a problem, or how to accomplish a task or solve a problem, each methodology having acceptance as an encapsulation of said wisdom;

lix. requesting a methodology showing how to accomplish a set of tasks related to circumstances regarding said first identified search base, said methodology having acceptance as an encapsulation of said wisdom;

lx. requesting a methodological step to perform next from a methodology or workflow having acceptance as an encapsulation of said wisdom wherein said methodology or workflow was considered appropriate to an effort and circumstances of the state of said effort matched the described requirements of said methodology or workflow for said step to next be attempted;

lxi. requesting a methodological step to perform next by said user or user'"'"'s collaborators from a methodology or workflow having acceptance as an encapsulation of said wisdom wherein said methodology or workflow was initiated for a collaboration involving user and said collaboration had progressed to state from which said step could next be attempted;

lxii. requesting opinion information based upon said first identified search base, such that one or more items in said first identified search base are info-items for which opinion information was entered or for which interest votes may be entered;

lxiii. requesting a relevance ranking of an opinion stated as relevant to items in said first identified search base, said opinion likely to contain said wisdom, such that one or more items in said first identified search base are info-items for which opinion information was entered;

lxiv. requesting an opinion stated as relevant to items in said first identified search base, said opinion likely to contain said wisdom, such that one or more items in said first identified search base are info-items for which opinion information was entered;

lxv. requesting a list of opinions expressed regarding the definition of items in said first identified search base;

lxvi. requesting a list of opinions expressed regarding the placement of said first identified search base and what categorization it should fall under;

lxvii. requesting information regarding interest shown based upon items in said first identified search base;

lxviii. requesting information regarding interest shown for a relationship info-item traversal based upon relationship info-items in said first identified search base;

lxix. requesting normalized interest shown metrics based upon relationship info-items in said first identified search base;

lxx. requesting normalized interest shown metrics for a relationship info-item traversal based upon relationship info-items in said first identified search base;

lxxi. requesting a contact, participant, collaborator, consortia, organization, or jurisdiction connected with said first identified search base likely to have knowledge and wisdom regarding said first identified search base;

lxxii. requesting knowledge of a type from a group consisting of;

evidence, e-discovery documents, facts, issues, documents, testimony, transcripts, depositions, pleadings, persons, organizations, issues remaining, issues to be decided, theory of the case outline items, presentation pattern outline items, presentation planning outline items, precedents, digests, sources, time-points, purlieu, motivations, known travel points, authorities, laws, jurisdictions, legal elements, legal principles, and places relevant in a case as cnxpts and relationships regarding said cnxpts in said first identified search base;

lxxiii. requesting a set of charge theories from a list of pairs of cnxpts in rule to charge theory applicability pairings in said first identified search base;

lxxiv. requesting a set of evidence items from a list of pairs of cnxpts in evidence to case issue applicability pairings in said first identified search base;

lxxv. requesting a set of evidence items from a list of pairs of cnxpts in evidence items against fact pairings in said first identified search base;

lxxvi. requesting a set of fact items from a list of pairs of cnxpts in fact to theory of the case applicability pairings in said first identified search base;

lxxvii. requesting a set of facts from a list of pairs of cnxpts in evidence items against fact pairings in said first identified search base;

lxxviii. requesting a set of facts from a list of pairs of cnxpts in facts against rule element pairings in said first identified search base;

lxxix. requesting a set of general precedents from a list of pairs of cnxpts in precedent to rule applicability pairings in said first identified search base;

lxxx. requesting a set of general rules from a list of pairs of cnxpts in rule to doctrine applicability pairings in said first identified search base;

lxxxi. requesting a set of general rules from a list of pairs of cnxpts in specific rule to general rule applicability pairings in said first identified search base;

lxxxii. requesting a set of jurisdictions from a list of pairs of cnxpts in specific rule to jurisdiction'"'"'s law applicability pairings in said first identified search base;

lxxxiii. requesting a set of precedents from a list of pairs of cnxpts in precedent to rule applicability pairings in said first identified search base;

lxxxiv. requesting a set of rule items from a list of pairs of cnxpts in rule to charge theory applicability pairings in said first identified search base;

lxxxv. requesting a set of rules from a list of pairs of cnxpts in element to rule applicability pairings in said first identified search base;

lxxxvi. requesting a set of rules from a list of pairs of cnxpts in rule to doctrine applicability pairings in said first identified search base;

lxxxvii. requesting a set of specific rule elements from a list of pairs of cnxpts in element to rule applicability pairings in said first identified search base;

lxxxviii. requesting a set of specific rule elements from a list of pairs of cnxpts in facts against rule element pairings in said first identified search base;

lxxxix. requesting a set of specific rule elements from a list of pairs of cnxpts in specific rule to general rule dependency pairings in said first identified search base;

xc. requesting a set of specific rules from a list of pairs of cnxpts in specific rule to general rule applicability pairings in said first identified search base;

xci. requesting a set of specific rules from a list of pairs of cnxpts in specific rule to jurisdiction'"'"'s law applicability pairings in said first identified search base;

xcii. requesting a set of 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;

xciii. requesting a set of model equations from a list of pairs of cnxpts in model equation dependency pairings in said first identified search base;

xciv. requesting a set of dependent elements from a list of pairs of cnxpts in dependency pairings in said first identified search base; and

xcv. requesting a set of precedent elements from a list of pairs of cnxpts in dependency pairings in said first identified search base;

t. 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;

i. for modeling result, estimation, and prediction forms of result, ordering for each result item in said first form of result is to be applied according to a resolved value of a metric specified in said additional specification;

ii. for timeline forms of result, ordering is by a time, process precedence, event precedence, or other metric, such that ordering for each result item in said first form of result timeline is to be applied according to a resolved value for each result of a metric specified in said additional specification;

iii. for co-location and area map forms of result, ordering for co-location is derived from descendant tree extraction process means based upon results of fxxt extraction process means, and positioning is based upon ordering;

iv. for flow maps forms of result, ordering for flow is by a time, process precedence, event precedence, or other metric, such that ordering for each result item in said first form of result flow map is to be applied according to a resolved value for each result of a metric specified in said additional specification and positioning is based upon ordering;

v. for movement, ordering to determine destination for movement is by calculating, for each result item in said first form of result a resolved value of a metric specified in said additional specification if a non-default metric is specified, or by forming a weighted averaging of algorithm scoring utilizing cnxpt result rank determination if any algorithm for scoring is specified, or otherwise by a default metric, such that said destination is first in said ordering after tie breaking by least distance to move;

vi. for list, portfolio table, report, and result set forms of result containing cnxpts, ordering is by calculating, for each result item in said first form of result a resolved value of a metric specified in said additional specification if a non-default metric is specified, or by forming a weighted averaging of algorithm scoring utilizing cnxpt result rank determination if any algorithm for scoring is specified, or otherwise by a default metric; and

vii. for list, portfolio table, report, and result set forms of result containing information resources or info-items representing information resources, ordering is by calculating, for each result item in said first form of result a resolved value of a metric specified in said additional specification if a non-default metric is specified, or by forming a weighted averaging of algorithm scoring utilizing information resource result rank determination if any algorithm for scoring is specified, or otherwise by a default metric;

u. accepting zero or more additional parts of said first or next wisdom request command optionally providing, in each part, an action to apply to said first form of result after completion of said specification for search, according to the finding, searching, query and retrieval process means, said action to apply selected from the group consisting 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;

v. 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 the finding, searching, query and retrieval process means, such that said action to apply is optionally retained with said search even if it occurs after all other specification of said search, such that said action to apply is optionally repeated automatically if said search is re-executed, such that said action to apply is also retained in the form of relevance votes, such that the automatic re-application of said action to apply may be made ineffective upon request by a user re-invoking said search, said action to apply selected from the group consisting of;

i. request display of a particular type of structural view of info-items based upon an entered type, to show said first form of result;

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 process 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 consisting 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 consisting 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 consisting 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;

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;

w. and

x. 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 consisting 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, but search command may be useful if 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, such that 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 consisting of a concept being conjured by said user while locating a first cntexxt wherein said user signifies that said wisdom should have been, such that 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 consisting 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, such that 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, such that 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, optionally indicating a; 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, optionally indicating a conversion of a goal into a cnxpt, such that at least one indication of how said concept being conjured by said user is differentiable from said search result concept represented by said cntexxt, the indication selected from the group consisting 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 the 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 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 first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for; and

14. citing 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 first concept represented by said cntexxt and not precisely excluded from encompassing the present purlieu of said first concept represented by said cntexxt;

whereby a unified search structure is provided so that a user may obtain wisdom from a crowd and non-users regarding an idea or a category of ideas as indicated by said user, the wisdom if available including how to organize the wisdom of a particular domain to provide an understandable structuring of its information by supplying identifiable contexts for similar ideas, how to obtain the wisdom including where it resides allowing for efficient storage, where any concept can play the role of context or mere concept in a domain, where ideas that are similar or more strongly related are nearer each other than those that are unrelated within a given subject matter domain, where a user can find all the like ideas within a larger context where slightly less similar or slightly older ideas are in its subsuming parent and so on in larger and larger categories or older groups of concepts, each context providing information about a set of ideas so that even if a user does not know what else exists that has nearly the same topic they will be able to find it within a context;

whereby data arguing is managed and effects of terminology due to generalization chauvinism theory and language differences are mitigated;

whereby a categorization serves as an organized set of binding points for wisdom;

whereby users may search for collected and organized knowledge, understand the organization and the concepts in the knowledge found, share and collaborate about the knowledge on the basis of the classifications of the knowledge found, develop scenarios and explanations regarding the knowledge found, and anticipate, prepare for and gain advantage from potential futures based upon the knowledge found;

whereby wisdom regarding where to obtain knowledge is available and analytics provided may be invoked to perform searches across many heterogeneous information retrieval systems and results combined for presentation;

whereby organized knowledge and wisdom rather than data is presented as a result of a search;

whereby a result may provide reverse referencing to show where a concept or context is used or where it is referenced;

whereby a result may show what the concept or context is known by in one or any other domain, its relative veracity, relevance, and importance in its parent context and in the domain, what traits or elements it has in a given domain, what its timeframe is, what descriptions exist for it;

whereby a placement of a concept or context in the organization a particular domain in any domain where it is available lends quick access to wisdom of that domain;

whereby wisdom for a concept or context may state how to think about the concept or context, what problems can be worked through in the domain given a context, what to do next in working through a problem in the domain, what task is remaining for a collaboration to complete for a concept or context in each domain, who may have knowledge regarding a concept in the domain or in any other domain, who may have knowledge regarding a context more generally, what facts, estimations of facts, or predictions regarding facts in the domain or in any other domain are available and how well they are accepted as reliable indicators of the actual fact, where the concept or context fits into an organization of concepts or contexts of various domains, what is related to the concept or context, what ecosystem mechanisms are connected to the concept or context, what users have self-selected to be within the audience interested in the concept or context, what is different about the concept or context in any domain, what has been written about the concept or context in any domain, what has been found out about the concept or context in any domain, what information from other domains can be imputed to a domain and what the result of that imputing is, what other wisdom can be found for a concept or context based upon the contexts it is in or based upon the concepts or contexts it includes in a domain or in any other domain, including external information and enterprise data extracts as information accessible through a concept or context;

whereby users may prepare for and gain advantage from potential futures based upon the wisdom found;

whereby superficial searching provides immediate results but highlights where the superficiality is apparent to anticipate further queries;

where knowledge found as returned results is managed for a user during the query process and catalogued for reference later, and available for reuse by others, and the need to rethink a prior user'"'"'s thoughts or devise searches is often unnecessary because the wisdom provided includes the results of the opinions, experiences, creativity, judgment, and thought processes of others allowing a user to be more productive;

whereby innovative thinking is based upon the prior wisdom in the mind of any of the thousands of potential inventors presently unable to find the appropriate means to get an idea into the reach of those able to make use of it;

whereby information may be controlled and access purchased;

whereby collection and maintenance of rapidly improving knowledge is a shared interest of users in specific audiences requiring an overlapped set of knowledge about a common set of concepts at various levels of contextual detail from which an incentive toward maintenance is available;

whereby serendipitous learning and discovering through browsing is empowered; and

whereby the returned results of searches are actionable.

250. The adding and refining said commonplace of claim 241 to manage the growth of knowledge, wherein:

a. harmonizing categorizations by altering extracted categorization to form an altered organization of knowledge;

whereby authority control to provide quality control over index terms and categories to maintain the consistency in the categorization and quality improvement by consensus-based naming, description, and interconnection among category cnxpts, ttxs, and information resources to improve the value of the combined data, without a requirement for unique names and in the presence of multiple interrelationships varying by scope, providing synonym associations, description variants, and name variants, language differences, translations, historic supersession, deprecated names to make transparent the tracking of the decisions made toward identifying and collocating so that users can assume that a term or phrase will refer to a particular topic, that name variations will be brought together under the one form, and that relationships are proper, and to provide for resolution of data argument by context to handle real world complexity or temporal understanding differences, to determine whether entities, categories, or instances are duplicated or merely similar by accumulating suggestions by votes from users to create, weight, and update authority records to obtain a contextual consensus result, and harmonization is the result of consensus tallying when applied to categorizations, and co-location mapping promotes the ability to see nearly identical concepts to allow crowd sourced cleanup or to highlight interesting differences, and definition improvement by concept subdivision and differentiation or combination with another concept by use of contexts, or deletion to provide for data curation at any scale and a higher degree of clarity to reduce conflicts between meaning confusion caused by similarity of terms across different categorization bases.

251. The adding and refining said commonplace of claim 241 to ingest external wisdom, wherein:

a. providing an initial stigmergic commonplace of information;

b. populating by a user when he indicates an appropriate entity (a list, data as a result;

c. producing a crawl result;

d. processing new crawl result data batches of citation rich documentation to find new categories of ttxs to become represented by new cnxpts;

e. or a query is executed, returning rsxitems;

f. collecting information into a data set to be compared against or added to said commonplace;

g. 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 unit,

h. broadening base of knowledge by ingesting as a source object said data set into said commonplace of knowledge;

i. ingesting a plurality of info-items into said commonplace;

ingesting a plurality of relationship info-items into said commonplace;

k. 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;

l. cataloging batches of external or internally held information resources or internal resources serving as information resources by said fxxt;

m. creating classification relationships between the generated categories represented by the new cnxpts and the cnxpts in the clusters;

n. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

o. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

p. accepting a choice of one or more relationship info-item types to be used as a determinant of meaning categorization 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;

q. generating a fxxt for the purpose of the instant similarity illustration;

r. computing a weighted consensus from opinions according to curating application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

s. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that 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 function means;

t. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

u. 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 function means;

v. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process means wherein said organization of knowledge of at least one domain of wisdom includes said added wisdom and also includes any additional portion of said commonplace against which categorization or comparison or curation is to occur;

w. 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;

x. learning from users the inconsistencies and redundancies in said ingested wisdom where connected to existing knowledge in said commonplace of knowledge;

Y. removing clearly redundant knowledge;

z. accepting culling commands in manual review to categorize said source object according to concepts and contexts as represented by existing cnxpt;

aa. 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

bb. initiating and controlling manual review of ingested information where appropriate;

whereby fxxts provide provenance and use case applicability, cnxpt typing, and relationship info-item typing, cnxpt and relationship info-item aging, cnxpt and relationship info-item applicability by age, process phasing identification, user process temporaries identification, interim search result identification, and other differentiations and each user can have their own personal curation process and result, each user session can be differentiated, interim and temporary results are uniquely identifiable, data sets and DataSets are identifiable, data may be consigned for sale, fxxt structures and cause structures may be to identified and combined, operations may be performed based on different relationship info-item or cnxpt types, models may be applied to the same categorization forest but based upon different relationship info-item weights, cnxpt importances, relationship info-item or cnxpt type interpretation, or based upon the position of the relationship info-item or cnxpt within a categorization forest, different model formulas or default or initial values by fxxt, access control, as well as other differentiations by fxxt;

whereby information is added from data sets of changes, new ttxs, new trxrts, and other txo instances, new dxo instances, catalogs of products, documents, information resources, prior extracts with updates made externally, crawling results, or study project results cohesively;

whereby results of ingesting are retained as a unit control over ingesting is initiated for consistency checking and curation;

whereby many organizations may build internal information systems to permit users to obtain documents and yet allow an aggregation of data sets they publish into a central organization of knowledge in a wisdom of crowds of organizations approach.

252. The adding and refining said commonplace of claim 251, 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;

g. computing a predicted weighted consensus quality metric from opinions stating quantification of quality metrics selected from the group consisting 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 curating application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

h. computing a predicted weighted ranking of the likely relevance of said source object to a coding key cnxpt as specified;

i. computing a predicted weighted rejection ranking of said source object according to rules for rejection for security rules;

accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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 structure 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 view point, such that data arguing is resolved to a consensus, such that said categorization is appropriate to a domain of wisdom for a use case, such that use of different maps provides correlated categorization structuring of the same raw data, such that raw data is converted to consensus structured clean data and useful decision structures, such that various view points 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 view point;

whereby said user is able to improve data encompassed by commonplace of information;

253. The adding and refining said commonplace of claim 241 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 consisting 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 consisting 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 consisting 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 consisting 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

i. a source info-item in said commonplace with attached provenance cataloging descriptive information,

ii. said type of source object selected from the group consisting 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;

iii. said source info-item to be used as the authority control base for said source object,

iv. said provenance cataloging information stating at least one identifying fact selected from the group consisting 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;

v. 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;

i. a first irxt to represent as an information resource said data source object,

ii. said first irxt given an identity indicator value from a predetermined combination of said source info-item properties,

iii. said first irxt given properties filled by said source object'"'"'s authority, usability, quality, and expertise of originator,

iv. said first irxt to reference said source object provenance authority source info-item of said data source object,

v. assigning to said first irxt representing said information resource said source object provenance authority fxxt,

vi. said first irxt termed a source object provenance authority irxt;

h. generating, if a predetermined system parameter is set to a predetermined value;

i. 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, ii. an occurrence attached to said first cnxpt,

iii. a relationship info-item of a predetermined weight based between said occurrence and said source object provenance authority irxt,

iv. 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 object,

v. said first cnxpt given properties filled by a predetermined set of elements selected from the group consisting of;

said source object'"'"'s authority and descriptive information;

vi. said generated occurrence of said first cnxpt related to said first irxt,

vii. said cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said cnxpt,

viii. said first cnxpt termed a source object level cnxpt;

i. converting said source object'"'"'s data format to the format required for ingesting;

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;

i. a second irxt to represent as an information resource said table;

ii. said second irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

a name generated from the descriptive information of said source object, and the descriptive information of said table;

iii. said second irxt given properties filled by a predetermined set of elements selected from the group consisting 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;

iv. 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;

i. a new concept represented by a second cnxpt with attached descriptive information from said table'"'"'s description;

ii. an occurrence attached to said second cnxpt;

iii. a relationship info-item of a predetermined type and of a predetermined weight between said occurrence and said source object provenance authority irxt;

iv. such that;

01. said second cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting 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;

02. said second cnxpt given properties filled by a predetermined set of elements selected from the group consisting of;

the descriptive information of said table and said source object'"'"'s authority and descriptive information;

03. 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,

04. 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, such that 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,

05. said second cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said second cnxpt,

06. said second cnxpt to be used as a curation control base for said table,

07. 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,

i. a fourth cnxpt to represent the attribute of the entity of said data set table,

ii. and an occurrence attached to said fourth cnxpt,

iii. a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt,

iv. said fourth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting 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;

v. said fourth cnxpt given properties filled by a predetermined set of elements selected from the group consisting 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;

vi. 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,

vii. 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, such that 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,

viii. said fourth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fourth cnxpt,

ix. said fourth cnxpt to be used as a curation control base for said attribute of the entity of said data set table,

x. 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,

i. a fifth irxt to represent as an information resource said table row

ii. said fifth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting 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;

iii. said fifth irxt given properties filled by a predetermined set of elements selected from the group consisting 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;

iv. each said fifth irxt to reference said source object provenance authority source info-item,

v. 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,

vi. 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,

vii. each said fifth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fifth irxt,

viii. 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,

i. a fifth cnxpt to represent the instance of the entity of said data set table row,

ii. and an occurrence attached to said fifth cnxpt,

iii. a relationship info-item of a predetermined weight is generated between said occurrence and said source object provenance authority irxt,

iv. said fifth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

said table identity indicator and unique identity indicators of said data set table row;

v. said fifth cnxpt given properties filled by a predetermined set of elements selected from the group consisting 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;

vi. 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,

vii. 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, such that 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,

viii. 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, such that 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,

ix. wherein each attribute of said data set table row is translated into a characteristic of predetermined type for said fifth cnxpt,

01. such that a irxt termed an enclosed information resource irxt is generated for each attribute of said data set table row that is an information resource,

02. 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,

03. 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,

04. 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,

05. 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,

06. such that all info-items generated from said source object are assigned said source object provenance authority fxxt, and,

07. 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,

08. such that 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, such that all info-items generated from said source object are assigned said source object provenance authority fxxt,

09. such that each citation in said data set table row as identified by an attribute containing an identifiable citation selected from the group consisting 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;

such that 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 consisting 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 consisting 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 such that 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, such that all info-items generated from said source object are assigned said source object provenance authority fxxt;

x. said fifth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said fifth cnxpt,

xi. said fifth cnxpt to be used as a curation control base for said table row,

xii. said fifth cnxpt to represent the concept represented by said table row,

xiii. 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

i. a seventh cnxpt to represent said name value pair,

ii. and an occurrence attached to said seventh cnxpt,

iii. a relationship info-item between said occurrence and said source object provenance authority irxt,

iv. said seventh cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting 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;

v. said seventh cnxpt given properties filled by a predetermined set of elements selected from the group consisting of;

the descriptive information of said source object'"'"'s authority and descriptive information and the value of said name value pair;

vi. 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,

vii. 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,

01. such that a irxt termed an enclosed information resource irxt is generated for each value of said name value pair that is an information resource,

02. 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,

03. 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,

04. such that all info-items generated from said source object are assigned said source object provenance authority fxxt, and,

05. 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,

06. such that 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, such that all info-items generated from said source object are assigned said source object provenance authority fxxt;

viii. said seventh cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said seventh cnxpt,

ix. said seventh cnxpt to be used as a curation control base for said name value pair,

x. said seventh cnxpt to represent the concept represented by said name value pair,

xi. 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,

i. 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;

ii. each said eighth irxt to additionally reference said source object provenance authority source info-item,

iii. 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,

iv. each said eighth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth irxt,

v. 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

i. an eighth irxt to represent said information resource

ii. said eighth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

a name generated from the descriptive information of said source object, and the descriptive information of said information resource;

iii. said eighth irxt given properties filled by a predetermined set of elements selected from the group consisting 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;

iv. each said eighth irxt to reference said source object provenance authority source info-item,

v. 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,

vi. each said eighth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth irxt,

vii. 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

i. an occurrence attached to said eighth cnxpt,

ii. a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt,

iii. said eighth cnxpt given additional properties filled by a predetermined set of elements from the descriptive information of said source object'"'"'s authority;

iv. 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,

v. 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,

vi. 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,

vii. said eighth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth cnxpt,

viii. said eighth cnxpt to be used as a curation control base for said enclosed information resource,

ix. said eighth cnxpt to represent the concept represented by said enclosed information resource,

x. 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

i. an eighth cnxpt to represent the concept embodied in said enclosed information resource,

ii. and an occurrence attached to said eighth cnxpt,

iii. a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt,

iv. an additional occurrence attached to said eighth cnxpt,

v. a relationship info-item of a predetermined weight between said additional occurrence and said enclosed information resource irxt,

vi. said eighth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting 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;

vii. said eighth cnxpt given properties filled by a predetermined set of elements selected from the group consisting of;

the descriptive information of said source object'"'"'s authority, a citation, and descriptive information of said enclosed information resource;

viii. 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,

ix. 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,

x. 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,

xi. said eighth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eighth cnxpt,

xii. said eighth cnxpt to be used as a curation control base for said enclosed information resource,

xiii. said eighth cnxpt to represent the concept represented by said enclosed information resource,

xiv. 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

i. a ninth irxt to represent as an information resource said data rule

ii. said ninth irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

a name generated from the descriptive information of said source object, and the descriptive information of said data rule;

iii. said ninth irxt given properties filled by a predetermined set of elements selected from the group consisting 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;

iv. each said ninth irxt to reference said source object provenance authority source info-item,

v. 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,

vi. each said ninth irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said ninth irxt,

vii. 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,

i. a concept represented by a ninth cnxpt to represent said data rule,

ii. and an occurrence attached to said ninth cnxpt,

iii. a relationship info-item of a predetermined weight between said occurrence and said source object provenance authority irxt,

iv. said ninth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

said source object identity indicator and unique identity indicators of said data rule, accommodating multiple instances of data rules having the same name;

v. said ninth cnxpt given properties filled by a predetermined set of elements selected from the group consisting of;

the descriptive information of said source object'"'"'s authority and descriptive information of said data rule;

vi. 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,

vii. 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, such that 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,

viii. wherein each said data rule of said source object data set is translated into a characteristic of predetermined type for said ninth cnxpt,

01. such that 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, such that 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,

02. such that 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, such that 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,

ix. said ninth cnxpt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said ninth cnxpt,

x. said ninth cnxpt to be used as a curation reference base for said data rule,

xi. said ninth cnxpt to represent the concept represented by said data rule,

xii. 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,

i. 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 consisting 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;

01. such that 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,

02. said eleventh irxt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

a name generated from the descriptive information of said source object, and the descriptive information of said information resource in said identifiable citation;

03. said eleventh irxt given properties filled by a predetermined set of elements selected from the group consisting 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;

04. each said eleventh irxt to reference said source object provenance authority source info-item,

05. 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,

06. each said eleventh irxt assigned said source object provenance authority fxxt if said fxxt is not already assigned to said eleventh irxt,

07. said eleventh irxt termed a cited information resource irxt;

08. and 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;

ii. impute a citing relationship info-item of predetermined type, and of a predetermined weight based upon the number of references found of said element in said information resource, and like 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 process means, marking 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;

x. 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,

i. said topical element selected from the group consisting of;

word, phrase, string, 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;

ii. each said topical element to be used as a base for deriving commonalty and similarity scores for said source object,

iii. 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,

iv. said twelfth cnxpt given an identity indicator value resulting from a predetermined formulation of a value from elements selected from the group consisting of;

said element type, said element name, said information resource identity indicator, said source object identity indicator, and said source object descriptive information;

v. said twelfth cnxpt given properties filled by a predetermined set of elements selected from the group consisting 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;

vi. 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,

vii. 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, such that 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;

viii. 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, such that 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;

ix. and, if a predetermined system parameter is set to a predetermined value, generating a thesaurus item for said topical element,

x. 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,

xi. such that all instances of said coding key cnxpt of a type are assigned a single fxxt based upon said source object provenance authority fxxt,

xii. said twelfth cnxpt termed a coding key cnxpt,

y. 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;

z. 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;

aa. 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;

bb. 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;

cc. 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;

dd. 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;

ee. initiating alerts, with attached description, wherein said source object is of a type applicable to said alert specification generation rule;

ff. initiating methodologies according to a methodology template wherein said source object is of a type applicable to said methodologies template;

gg. initiating workflows according to a workflow template wherein said source object is of a type applicable to said workflow template;

hh. 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;

ii. initiating alerts, with attached description, wherein a cnxpt of a type applicable to said alert specification generation rule is generated from said source object;

jj. initiating methodologies according to a methodology template wherein a cnxpt of a type applicable to said methodology template is generated from said source object

kk. initiating workflows according to said workflow template wherein a cnxpt of a type applicable to said workflow template is generated from said source object

ll. 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;

mm. 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;

nn. 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

oo. 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,

pp. 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 consisting of;

i. an attempt to add a source object failed and manual intervention or troubleshooting is necessary such that 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 such that 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 such that 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 such that 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 such that 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;

qq. recalculating workflow task effort, resource requirements, resource allocations, and schedule changes;

whereby the type of source and, optionally, its usability, quality, expertise, etc. are given by the source object and all ingested information is accessible as a unit;

whereby users participating in the process of curation are informed of needed attention to curate concepts and information in the commonplace.

254. The method of claim 253 to apply curation rules while preserving raw, original data, further including:

a. applying data curation rules back to raw data of prior import or to a new import;

whereby said user is able to improve data encompassed by commonplace of information by ability to add votes and retain provenance at raw level to not destroy any audit trail for change control until the audit trail is unnecessary.

255. The method of claim 253 to ingest data, further including:

a. filling one role of said relationship info-item with the info-item identifier of a data set, a result set, a business, a url (base site or some other source represented by a source txo;

b. filling one role of the relationship info-item by the added txo instance (any txo instance, cnxpt, etc.);

c. filling a second role by a data set, a result set, or some other source info-item identifier;

d. marking (by detailed infxtypx or the relationship info-item to indicate the type of source and, optionally, its usability, quality, currency or other factors as a basis for a weight or other attribute value;

whereby a txo may have any number of sources, a relationship info-item may have a source role, or in one embodiment, a relationship info-item item identifier may fill a role in a source relationship.

e. processing ingested data set batches of citation rich documentation to find new categories of ttxs to become represented by new cnxpts;

f. creating an irxt for the information resource or internal resource serving as an information resource;

256. The method of claim 253 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;

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 cmm for any information resource or internal resource serving as an information.

257. The method of claim 253 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 function 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 executing zero or more commonality process and imputation process means analytics, 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;

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;

whereby said user is able to improve data encompassed by commonplace of information.

258. The adding and refining said commonplace of claim 251, 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, cmm 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 and procedure—

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, including such information as repository documents, files from file managers, web based research papers, patents, and scraped information regarding products where the ingested results are indexed into said commonplace, listed in a result set for said crawl result, used to form clusters to become cnxpts, compared with existing cnxpts and merged where possible, and made available for workflow based review and for culling, and said new cnxpts are made ready to be used in categorization if sufficient in quality, and results may be set to be updated and to generate alerts when updates cause a set number of new result set items or useful new.

259. The locating information possibly relevant to a cnxpt of claim 223 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 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;

whereby a classification structure catalog is developed from information in said commonplace where opinions regarding relevance improve the indexing power of said category organization of said commonplace.

260. The accepting culling commands of claim 259, 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;

whereby the opinions of experts and the power of the wisdom of the crowd may be taken into consideration as result sets are reviewed by multiple users and occurrence strengths resulting from result sets are set, with the promise of greater accuracy because of the involvement of experts or said crowd in the setting of relevance causing the creation of an occurrence that then positions said cnxpt.

261. The forming a consensus of the strength of the relevance of an information item to a cnxpt of claim 260, further including:

a. summarizing one or more users'"'"' relevance rankings of rsxitems to form a single summary relevance with one value for said rsxitem; and

b. summarizing one or more users'"'"' adjustments of the position of cnxpts in a visualization of a fxxt to form a single summary position with one value for said cnxpt in said visualization;

whereby said relevance rankings of rsxitems in queries, said positioning of cnxpts on visualization maps of a fxxt, the identity of info-items, the pair-wise similarity or connectedness of info-items are summarized within the contexts of opinion expressed as what if, belief, high assuredness, relevance, certitude, or conviction, and personal opinion reliance.

262. The locating information possibly relevant to a cnxpt of claim 223 to allow searching for an idea, further including:

a. choosing from a list of cntexxts an alternative said cntexxt, said list determined by accepting and processing a search query according to searching process 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;

b. choosing from a list of cntexxts an alternative said cntexxt, said list determined by accepting and processing a search query specification according to searching process means and querying process 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;

c. accepting a command to start a search for an idea in a user'"'"'s mind and creating a uniquely identifiable search goal info-item;

d. performing a non-associative search for said idea and positioning the goal according to the result;

e. providing associative searching using one or more visualizations of one or more fxxts to said user to allow seeking a cntexxt in said fxxt where said idea should fit in according to the goal based searching process means; and

f. finalizing the search by stating that a new ttx was concretized and categorized, or not;

whereby said user categorizes a new idea by either locating on a visualization the ttx a user has in his or her mind, locates a proper cntexxt and concretizes the cnxpt for the ttx in his or her mind, or abandons the search.

263. The performing a non-associative search for said idea of claim 262, further including:

a. choosing from a list of cntexxts an alternative said cntexxt, said list determined by accepting and processing a search query according to searching process 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;

b. choosing from a list of cntexxts an alternative said cntexxt, said list determined by accepting and processing a search query specification according to searching process means and querying process 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;

c. forming a query to attach to said goal to seek a set of information relevant to said idea;

d. accepting a query step specification for said idea with specified search criteria as a part of said query to locate relevant search results according to the finding, searching, query and retrieval process means;

e. adding said query to said goal, forming a goal and adding said query if said query is a first query toward said goal according to procedure—

attach a query to goal means;

f. filling said search goal with an instance query step from said query step according to procedure—

process a query for goal, procedure—

execute query and attach result set to goal means;

g. forming a result set for said query for said goal according to result set processes and procedure—

create result set and procedure—

create result set means for holding search results to retain the basis for said goal for reuse;

h. executing said query step search according to procedure—

process query step specification, generating result set means, collecting the content of said information located in one or more heterogeneous repositories with available meta-data possibly including locators;

i. creating a representative txo info-item for said information into said commonplace for new information and setting its properties to have said metadata of said information as values to indicate the characteristics of said information to obtain an index to said information;

j. forming an rsxitem referencing said representative txo info-items for information in said set resulting from said query for said goal according to result set processes and procedure—

create result set and procedure—

process a result set for goal means;

k. 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;

l. presenting said result set items of said result set to user for culling;

m. accepting culling commands on said result set rsxitems to obtain a relevant set of result set items according to result set processes means;

n. accepting an assessment by user 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;

o. 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

p. determining a plurality of cntexxts in said fxxt that said search goal could be associated with by comparing said search results with relevant information of existing cnxpts in said fxxt to reposition said goal according to said result set into the best cntexxt according to result set evaluation for positioning means;

whereby a query result obtained by said user is retrieved, indexed into said commonplace, listed in a result set for said query, made available for culling, is related to an existing or new goal cnxpt, and zero or more cntexxts are located where said idea would logically fit within a fxxt, said cnxpt is repositioned into said best cntexxt on a visualization of a chosen fxxt where said idea fits in based upon a matching of information found previously for that cntexxt category, and said user is asked to confirm the placement next.

264. The performing a non-associative search of claim 263 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 and procedure—

create result set means; and

d. reapplying result set evaluation and cnxpt positioning;

whereby a query result obtained may be semi-automatically refreshed and the effect of said new result may alter the placement of said target cnxpt in a categorization of a fxxt.

265. The performing a non-associative search of claim 263 to organize a personal task, further including:

a. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

b. providing initial commonplace of information;

c. collecting information into a data set to be compared against or added to said commonplace;

d. accepting a choice of one or more entity types selected from said commonplace or from said data set to be considered as cnxpts;

e. 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;

f. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

g. accepting a choice of zero or more relationship info-item types to be used as a determinant of entity similarity from the relationship info-item types of those relationships relating said entity types to be considered as instances of said cnxpt type either already existing within said commonplace or in said data set;

h. 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 relationship 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;

i. replacing any considered relationship info-item of endpoint count greater than two to an equivalent set of considered relationships having an endpoint count of two;

j. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and said relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

k. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization to be between said instances of said cnxpt type;

l. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

m. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity wherein the relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

n. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity to be between said instances of said cnxpt type;

o. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between cnxpts to have said single default fxxt during processing;

p. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity such that said relationships already existing within said commonplace are retained and weights of said relationships to be added are calculated as a coefficient specified by the user times the value;

q. given in an attribute present for said relationship info-item or a specified default value according to utilize collective consensus through vote tallying function means;

r. determining effective weights for summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

s. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

t. combining the endpoint cnxpts of said summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types 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 relationship 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 relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that an endpoint of any said relationships having is a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

u. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all said revised collection of relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

v. 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 function means; and

w. reporting the structure of said spanning forest of cnxpts and interrelationships;

266. The method of claim 108 to also form a visualization of a domain of knowledge utilizing a determined fxxt specification, further including the following steps in the order named:

a. providing software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

b. configuring said processors to operate according to utilize collective consensus through vote tallying function means;

c. 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;

d. accepting a choice of one or more relationship info-item types to be used as propositional relationships for determining a categorization 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;

e. replacing any considered relationship info-item of endpoint count greater than two by an equivalent set of relationships having an endpoint count of two;

f. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization wherein said relationships have directionality and said relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

g. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization to be between said instances of said cnxpt type;

h. considering said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between cnxpts to have said single default fxxt during processing;

i. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

replacing any considered relationship info-item of endpoint count greater than two to an equivalent set of considered relationships having an endpoint count of two;

k. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

l. determining weights of said all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that said relationships already existing within said commonplace are retained and weights of said relationships to be added 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 function means;

m. combining the endpoint cnxpts of said summary relationships between cnxpts summarizing all relationships of type of said choice of one or more relationship info-item types 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 relationship 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 relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization such that an endpoint of any said relationships having is a cnxpt eliminated as a result of combination is replaced by the resulting cnxpt from the combining;

n. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all said revised collection of relationships of type of said choice of one or more relationship info-item types to be used as a determinant of categorization between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function means;

o. 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 function means;

p. reporting the structure of said spanning forest of cnxpts and interrelationships;

q. accepting a choice of one or more relationship info-item types to be used as positioning relationships for determining the positioning of cntexxts representing cnxpts in a visualization based upon concept similarity from the relationship info-item types indicating cnxpt similarity to prepare for categorizing and visualizing appropriate to said use case;

r. collecting all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of entity similarity wherein the relationship info-item already exists within said commonplace between said entity types to be considered as instances of said cnxpt type or is among said relationships to be added between said entity types to be considered as instances of said cnxpt type;

s. replacing any considered relationship info-item of endpoint count greater than two to an equivalent set of considered relationships having an endpoint count of two;

t. reporting the structure of said spanning forest of cnxpts and interrelationships;

u. detailing a fxxt specification defining said categorization to perform for said fxxt;

v. structuring said commonplace to extract content;

w. interpreting said fxxt specification for said fxxt to extract said fxxt from said commonplace by marking cnxpts and associations as members of said fxxt;

x. choosing hierarchical associations from said marked associations of said fxxt to form spanning trees by generating hierarchical tensors that point specifically to at most one parent cnxpt in said fxxt to generate descendant tree forest according to fxxt descendant tree extraction means for tree extraction;

y. generating fxxt specific visualization positions for cnxpts for said fxxt by depth first ordering;

z. generating a visualization for display for said fxxt;

aa. utilizing said visualization;

bb. such that classifications are derived from a relevant portion of said commonplace data, cnxpts and association relationships are marked as members of said fxxt, a forest of trees is formed and said cnxpts are positioned onto a visualization according to said structure provided by said descendant tree forest;

whereby users may obtain subject matter displays for specific purposes from said commonplace to more efficiently understand the contents of said commonplace, a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification and an extracted set of cnxpts are positioned in said visualization of said fxxt, said visualization produced has cnxpt members of said fxxt positioned in a taxonometric categorization of said fxxt with positioning based upon said associations involving said cnxpts and said strengths of said associations thus forming a classification harmonization from multiple classifications, said categorization visualization being navigable by said user for associative searching and serendipitous discovery, and said contents of said commonplace as shown in said visualization embody a shared information collection and a shared analysis for categorization.

267. The method of claim 266 to also form a value estimate of an appcept, further including the following steps in the order named:

a. calculating total space consumed by the two-dimensional area occupied by a 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;

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;

whereby prediction by space utilizes the calculation of value by space consumed on a map of applications of technology to related to innovation that has taken place in each area of technology, up to the horizon shown, or upon, including but not limited to;

interest shown, known investment made, market size per past product sales, predictions of satisfaction of appcepts, present market size according to current values for sales in a market for the appcepts, future market size by estimates of demand for appcepts by planning horizon;

whereby the proportion of space allotted to an appcept, in specific fxxts serving as the basis, can be calculated from, including but not limited to;

value, interest shown, how well one appcept satisfies an overall requirement relative to other candidates, stage of market or timeframe or other metric; and

whereby the resulting size of an appcept can be used as a basis for predicting, including but not limited to;

future market demand, investment value, specific tcept future value, when a projection will be accurate for the overall demand, funds available for investment, or of a metric such as GDP.

268. The method of claim 267 to also form a value estimate of a tcept, further including the following steps in the order named:

a. calculating, by imputation of value from appcepts related by a satisfaction of need relationship, the total value 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;

269. The method of claim 268 to also form a value estimate of a tcept, further including the following steps in the order named:

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;

270. The method of claim 266 to also form a value estimate of a tcept, further including the following steps in the order named:

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;

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;

whereby prediction by space utilizes the calculation of value by space consumed on a map of technologies up to the horizon shown, or upon, including but not limited to;

interest shown, known investment made, market size per past product sales, predictions of satisfaction of requirements, present market size according to current values for sales in a market;

whereby the proportion of space allotted to an tcept, in specific fxxts serving as the basis, can be calculated from, including but not limited to;

value, interest shown, stage of market or timeframe or other metric; and

whereby the resulting size of an tcept can be used as a basis for predicting, including but not limited to;

future market demand, investment value, specific tcept future value, when a projection will be accurate for the overall demand, or funds available for investment.

271. The method of claim 266 to also form an estimate of a metric of a cnxpt, further including the following steps in the order named:

a. calculating total space consumed by the two-dimensional area occupied by a cnxpt taken over all cnxpts shown on a map of cnxpts at a given depth of said map;

b. calculating by estimate, model, or imputation the total metric for all cnxpts shown on the map of cnxpts at the given depth of said map;

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 map of cnxpts at the depth of the map and multiplying it by the total metric;

whereby prediction by space utilizes the calculation of metrics by space consumed on a 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, can be calculated from the resulting size of the cnxpt.

272. The adding and refining said commonplace of claim 1 to compute a value for a product or technology, wherein:

a. generating a plurality of organizations of knowledge;

b. imputing a metric value from a cnxpt of a first organization of knowledge of a plurality of organizations of knowledge to a related target cnxpt in a target organization of knowledge;

273. The method of claim 265 to also form an estimate of a metric of a cnxpt, further including the following steps in the order named:

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.

274. The curation consensus process of claim 184 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;

275. The method of claim 143, wherein organizing the plurality of contexts comprises:

a. identifying relationships between the cnxpts; and

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

whereby clusters are formed from cntexxts at one or more depths of the visualization map;

whereby neighboring cnxpts are highlighted 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;

276. The method of claim 275, wherein the cntexxts are determined from crowd sourced data wherein crowd sourced data refers to information obtained from individuals to be analyzed for purposes of creating the cntexxts.

277. The preparing a co-location visualization of claim 1 to prepare a co-location visualization, wherein:

a. preparing a co-location visualization wherein similar concepts are placed relatively closer to one another;

b. constructing a visualization wherein similar concepts are placed relatively closer to one another to achieve a collocation objective such that said user may better see ‘

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;

whereby a tool for associative searching can be populated for use with a map.

278. The generating a visualization for display for said fxxt 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 consisting 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 such that 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 may be or has been stated such that the more general context is considered to state 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 such that said more general context provides a smaller occurrence set all of which being related to the concept represented by said more general context and such that 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 such that 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;

such that as each new concept is stated that is an offshoot or child of a currently present concept represented by a cnxpt, said new concept shows up internally to said more general context represented by a cnxpt representing said currently present concept and is shown as smaller upon display, such that the more general concept appears to offer a contextual category holding said new concept and said new concept being smaller does not occupy all of said currently present concept'"'"'s contextual area, voids are left in the context where other new concepts might be entered such that more children to be spawned from said currently present concept;

whereby a user is shown an understandable visualization of a categorization of commonplace information;

whereby a new idea may someday have new offshoot ideas of its own, so it is drawn as a context as well, all empty, and it is considered a leaf only until new ideas come up;

whereby as each new idea is stated is either seen as a new root or it shows up internally to a more general context and is smaller to leave space available for other new ideas spawned from the context; and

whereby every non-leaf idea is both an idea of itself, as well as a context for offshoot ideas.

279. The constructing an organization of knowledge of claim 249 in the technology domain to produce lists of prior art, further including:

a. forming a query for parents of a tcept in an organization of knowledge base upon incremental innovations;

b. listing the results of the query;

whereby a list of prior art can be produced.

280. The performing a non-associative search of claim 263 to also provide assisted information resource or internal resource serving as an information resource collection and categorization, further including:

a. 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 process means and goal based searching process means;

b. forming a query for submission to said search tools;

c. forming a goal if said query is a first query toward said goal;

d. adding said query to said goal if query is a continuation of searching of said goal;

e. 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;

f. obtaining said information resource or internal resource serving as an information resource'"'"'s metadata from a heterogeneous repository location provided by said locator;

g. 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 or internal resource serving as an information resource, enter information resource or internal resource serving as an information resource for a ttx, and procedure—

create irxt means;

h. forming a result set for said query for said goal according to result set processes and procedure—

create result set means;

i. 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 and procedure—

create result set means;

j. 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;

k. 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;

l. presenting said rsxitem'"'"'s said information resource or internal resource serving as an information resource'"'"'s content to user by de-referencing said locator;

m. 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;

n. 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

o. determining a plurality of cntexxts in said fxxt that said search goal could be associated with by comparing said search results with relevant information of existing cnxpts in said fxxt to reposition said goal according to said result set into the best cntexxt according to result set evaluation for positioning means;

whereby a search engine result obtained by said user is retrieved automatically for said user, indexed into said commonplace, listed in a result set for said query, made available for said user for culling, is related to an existing or new goal cnxpt, and zero or more cntexxts are located where said idea would logically fit within a fxxt, said cnxpt is repositioned into said best cntexxt on a visualization of a chosen fxxt where said idea fits in based upon a matching of information found previously for that cntexxt category, and said user is asked to confirm the placement next.

281. The method of claim 263 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 according to ideation process means and finding searching query and retrieval process means and goal based searching process means and selection set management process means and focus on information process means and alter information through visualization process means such that 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 selected from the group consisting of;

282. The performing a non-associative search of claim 280 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 from one or more search tools during a user query according to finding, searching, query and retrieval process means and goal based searching process;

c. for query step invoking a metasearch, obtaining from said user'"'"'s returned result of said query a locator for an information resource or internal resource serving as an information resource;

d. for query step invoking a metasearch, obtaining said information resource or internal resource serving as an information resource'"'"'s metadata from said heterogeneous repository location provided by said locator;

e. for query step invoking a metasearch, 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;

f. forming an rsxitem in said result set for said query according to result set processes and procedure—

create result set means;

g. 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 processes and procedure—

create result set means; and

h. reapplying result set evaluation and cnxpt positioning;

whereby a search engine result obtained may be semi-automatically refreshed and the effect of said new result may alter the placement of said target cnxpt in a categorization of a fxxt.

283. The providing associative searching using one or more visualizations of claim 262, further including:

a. accepting a choice of fxxt and visualization on which to search;

b. moving the goal to an initial position on said visualization 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 fxxt chosen;

d. accepting navigation commands for manually moving said search goal on said visualization of said fxxt to a cntexxt in said visualization more strongly related to the ttx in said user'"'"'s mind according to goal based searching process means and goal positioning process 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 process means, such that that are weakened as new positions are chosen;

whereby zero or more cntexxts in one or more visualizations in one or more fxxts may be located where said idea would logically fit within the visualization'"'"'s fxxt.

284. The finalizing the search of claim 262 to accept a conjuring of an idea, further including the following steps in the order named:

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 the fxxt where said query is performed and is not the same as said cntexxt category itself or the same as any sibling idea ttx as represented by the sibling cnxpts in that cntexxt category in said fxxt;

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 fxxt;

d. generating occurrence relationships, in said fxxt, between said cnxpt and each relevant result set item information txo or irxt found; and

e. informing a user regarding said new cnxpt;

whereby said user'"'"'s need for relevancy and incentives offered toward liquidity aid in the collection of information about ideas, said search goal becomes a new cnxpt and is added to said commonplace in a proper classification without need of any further description, said query and its result set items are connected to said cnxpt by occurrences for reuse and refinement, and said user is provided information and predictions, such as opportunities for protecting and commercializing said cnxpt, predictions regarding the value of said cnxpt.

285. The informing a user regarding said new cnxpt of claim 284 to also initiate activity regarding the added idea, further including:

a. informing said user of information available to those entering new cnxpts;

b. providing selected information regarding said cnxpt;

c. setting access to said new cnxpt according to the access management for ttxs means and managing ideas means;

d. providing a methodology or workflow for establishing cnxpt protection according to the patent application workflow—

apply for patent means;

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 the socialize process 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 and consortium investment means;

whereby connections are achievable between people showing expertise or having investment funds available, from inventors to investors to researchers, including linkedin-like networking, yahoo-like groups, facebook-like blog system limited to commercial users within specific well defined technology areas, creating a market for experts to discuss ideas and a facility to increase generation, sharing, and reuse of information, and where users may confidently communicate with others regarding said cnxpt because of the controlled communications structure to share business plans within a protected mechanism for business plan submission and quiet review by validated investors, with access control to provide capturing of granting'"'"'s of access, actual accesses, other disclosures, and the content of discussion between parties.

286. The adding and refining said commonplace of claim 1 to predict the timing of fruition of a subsumed cntexxt in a categorization, further including:

a. calculating for a target cnxpt as a basis, including but not limited to;

when the most recent productized predecessor of a predecessor cnxpt became real by when a product utilizing that cnxpt was delivered or when that cnxpt was used in production;

what the patent status is for a predecessor or target cnxpt;

what the research status is for a predecessor or target cnxpt;

what the rate of innovation has been for the incremental innovations prior to and in the ancestry of the target cnxpt, and generating a timeline for the timing of gestations of the target and the predecessors between the known productized predecessor and the target cnxpt;

whereby the length of time before or time frame when a technology is reasonably anticipated to exist is estimated.

287. The adding and refining said commonplace 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 best available overall 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 but not limited to;

estimating the depth of the subsuming cnxpt;

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

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.

288. The constructing a visualization map of claim 111 to also construct a flow map, further including:

a. assigning a cnxpt pair to a flow by relating said cnxpt pair with a directed association;

b. detailing a fxxt specification defining a categorization to perform, defining a map detailing one or more foci for said fxxt, defining a representative fraction structure for the elastic surface related to said flow;

c. forming zero or more trait trxrts for one or more of said cnxpts in one or more of said cnxpt pairs related by a flow association such that an analysis of said trxrt can yield the identity of a particular representative fractional segment of said elastic surface where said cnxpt would properly fit on the basis of said trxrt'"'"'s information;

d. forming zero or more purlieu purxpts for one or more of said cnxpts in one or more of said cnxpt pairs related by a flow association such that an analysis of said purxpt can yield the identity of a particular representative fractional segment of said elastic surface where said cnxpt would properly fit on the basis of said purxpt'"'"'s information;

e. forming zero or more property values for one or more of said cnxpts in one or more of said cnxpt pairs related by a flow association such that an analysis of said property value can yield the identity of a particular representative fractional segment of said elastic surface where said cnxpt would properly fit on the basis of said property'"'"'s information;

f. for each cnxpt in one or more of said cnxpt pairs related by a flow association, determine the set of elastic surface representative fractional segments indicated by the trxrts, purxpts, and properties of said cnxpt, if any, and summarize said set to form a flow tensor indicating a proper fit for said cnxpt into a representative fractional segment of said elastic surface related to said flow to yield an approximate anchoring relationship info-item for said cnxpt to be positioned in said representative fractional segment for said flow;

g. generating flow roll-up associations, 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 elastic surface based upon said child'"'"'s anchoring location; and

h. generating positioning for said fxxt member cnxpts according to process trees for visualization generation, position determination and final sizing means for calculation;

i. such that said positioning of said cnxpts of said cnxpt pairs related by a flow association are placed into a representative fractional segment of said elastic surface of said map according to information associated to said cnxpt by trait, purlieu, or property, where one of more of said trait, purlieu, or properties may have been derived from information outside of said cnxpt;

whereby the ability is provided to place objects for a 3d map in a position related to the ordering of said object directly or relative to the positioning of others in a flow.

289. The constructing a visualization map of claim 111 to also construct a forest of enhanced descendant trees, further including the following steps in the order named:

a. forming an enhanced descendant spanning tree forest from said fxxt descendant tree forest according to build enhanced descendant spanning trees means for tree formation, after choosing visualization structuring propositional hierarchical associations from said marked associations of said fxxt to form spanning trees;

b. adding zero or more anchored dxo instances or txo instances of said fxxt to said enhanced descendant spanning tree forest according to build enhanced descendant spanning trees means for tree formation;

c. generating tensors and associations to direct positioning of said added anchored dxo instances or txo instances of said fxxt according to build enhanced descendant spanning trees means for tree formation;

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

e. generating tensors and associations to direct positioning of added alias-hyperlinks of said fxxt according to build enhanced descendant spanning trees means for tree formation;

f. generating importance properties with weights for enforcing relative sizing of objects on said map according to calculate bottom up importance metrics for cnxpt categories means;

g. generating tensors, tensor weights, associations, and association weights by performing roll-up processing on said enhanced descendant spanning tree forest for said fxxt according to calculate roll-up association weights to form affinitive tensors means for generation of tensors for enforcing object spacing and sizing for said map of said fxxt;

h. 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 fxxt complete summary tensor generation means;

i. generating between-category repulsor tensors with weights for enforcing distance between objects during positioning on said map according to fxxt complete summary tensor generation means;

j. generating fxxt specific visualization positions for cnxpts for said fxxt according to the process trees for visualization generation, position determination and final sizing means for positioning;

k. generating a visualization for display of said map for said fxxt; and

l. utilizing said visualized map;

m. such that new positioning of map info-item objects are generated based upon the prior positions of said info-item objects and said tensor weights for a fxxt based map and;

n. so that classifications derived from a relevant portion of said commonplace data serve as the basis for positioning of cnxpts onto a visualization according to the structure provided by said enhanced descendant tree forest;

whereby the ability is provided to place objects for a 3d map in a position related to the closeness of said object to others logically according to a fxxt specification and a categorization derived therefrom and create a map showing said categorization and providing users with subject matter displays for specific purposes from said commonplace to more efficiently understand the contents of said commonplace with the addition of alias-hyperlinks and other objects.

290. The constructing a forest of enhanced descendant trees of claim 289, further including:

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

b. generating a dummy cnxpt as parent for each said added dxo or txo info-item anchored to a cnxpt in said descendant 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 said fxxt 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 said fxxt 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 said fxxt to said enhanced descendant spanning tree forest;

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

d. adding zero or more unanchored dxo instances and txo instances of said fxxt to said enhanced descendant spanning tree 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 said fxxt 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 fxxt specification;

f. such that the performance of roll-up processing on the resulting said forest of enhanced descendant trees will consider said tensors and associations added;

whereby the ability is provided to build a forest of trees from a basic descendant spanning tree forest to contain alias-hyperlinks and other dxo instances and txo instances based upon said fxxt specification, the sizing of said added objects is controllable, and the levels of cnxpts can be adjusted properly to appear reasonably for a user.

291. The constructing a forest of enhanced descendant trees of claim 290, further including:

a. generating a forest of ascendant trees according to the calculate ascendant trees means after the build enhanced descendant spanning trees means completes;

whereby the ability is provided to a user to navigate into said forest and at some cnxpt turn around to look back toward the root and see parents of said cnxpt where he is, if more than one parent existed in said fxxt for said cnxpt and a multi-faceted ontology is reduced to a single faceted structure according to said fxxt specification and an extracted set of cnxpts to be positioned on said map in said visualization of said fxxt.

296. The adding and refining said commonplace of claim 16, for ontology statistical analysis and modeling, further comprising:

a. forming a plurality of set extraction specifications partitioning an ontology'"'"'s contents into either in or not in said set extraction;

b. accepting a structuring of an ontology as a basis for modeling by specifying a weighting coefficient for each said set extractions such that any such said set extraction is included into a model basis if the assigned coefficient is not zero;

c. extracting said set extractions of ontology components with non-zero coefficients into said model basis;

d. developing a structure from said model basis according to the weightings of said set extractions;

e. calculating a model result from said model basis;

f. accepting a normative result anticipated of the modeling;

g. computing an error metric for the differential between the modeling result of the structuring and the normative solution;

h. adjusting the coefficients assigning weighting to said set extractions to reduce said error metric such that a secondary model result is nearer to said normative result;

i. accepting said set of assigned coefficients as an acceptable set for a model to achieve a satisfactory predictive result;

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

a. extracting a plurality of subsets of relationships between cnxpts from a commonplace, each subset described by a fxxt, such that at least one relationship extracted is in a subset defined by a fxxt that, in the user'"'"'s opinion, states that a first cnxpt on a first end of the relationship affects the condition of a second cnxpt on the opposite, second end in the relationship in a proportion determinable by the relationship'"'"'s weight, the presence of the affect of said second cnxpt on said first cnxpt termed a dependency, said affect termed a surrogate causality, said second cnxpt termed an event outcome;

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

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

d. considering only conditionality dependency relationships, form hierarchical surrogate causality chains based upon most heavily weighted summarized dependency relationships according to basic descending tree extraction of map generation process means;

e. considering only conditionality dependency relationships not used already for tree formation, form secondary hierarchical surrogate causality chains based upon these remaining summarized dependency relationships according to enhanced descending tree extraction of map generation process means;

f. calculating likelihood of each dependent event outcome;

298. The method of claim 241 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 collective consensus through vote tallying process means;

b. determining, by at least one processor, at least one chain segment consisting of an a priori justification and an a posteriori justification according to map generation process means from said organization of knowledge of at least one domain of wisdom;

c. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

d. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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;

299. The method of claim 297, further including:

a. multiplying, for each subset obtained from a fxxt, the weight of all relationships in the subset by a coefficient stated for the fxxt, according to fxxt extraction of map generation process means;

whereby quality of a prediction can be altered by adjusting the weight of beliefs input;

300. The method of claim 297 wherein a conditional likelihood is based upon an estimate selected from the group consisting of:

a belief, a causality, a surrogate causality and a logical condition.

301. The method of claim 297 to empower users to reallocate beliefs, comprising:

a. specifying a set of one or more circumstances for which an evaluation of the likelihood of a particular outcome is needed;

b. specifying a space of one or more possibilities as second cnxpts connected to a predecessor first cnxpt by relationships showing causal or surrogate causalities relevant to determining a likely outcome in any one or more of said sets of one or more circumstances;

c. assigning zero or more fxxts for each of said second cnxpts indicating fxxt specifications stating the parameter structures appropriate and procedure steps for determining inclusion of said second cnxpt in said evaluation of said likely outcome in any zero or more of said sets of one or more circumstances;

d. assigning zero or more fxxts for each of said relationships indicating fxxt specifications stating the parameter structures appropriate and procedure steps for determining validity for said relationships for use in said evaluation of said likely outcome in any one or more of said sets of zero or more circumstances;

e. assigning zero or more characteristic values for characteristics of said relationships;

f. assigning zero or more relative weighting characteristic values for each said fxxt assigned for each said relationship;

g. assigning zero or more characteristics, traits, purlieu, or additional relationships for each of said first or second cnxpts;

h. specifying a circumstance for which said evaluation of the likelihood of a particular outcome is to be determined;

i. determining the set of said second cnxpts to include in said evaluation of the likelihood of a particular outcome by fxxt extraction procedure means wherein a cnxpt is included if it is marked with a fxxt having no criteria for determining validity for inclusion, or alternatively if it is marked with a fxxt having fxxt specification steps which when applied find that said cnxpt is valid for inclusion;

j. determining the set of said relationships showing causal or surrogate causalities to include in said evaluation of the likelihood of a particular outcome by fxxt extraction procedure means wherein a cnxpt is included if it is marked with a fxxt having no criteria for determining validity for inclusion, or alternatively if it is marked with a fxxt having fxxt specification steps which when applied find that said cnxpt is valid for inclusion;

k. determining the set of said weightings of said relationships showing causal or surrogate causalities included in said evaluation of the likelihood of a particular outcome by fxxt extraction procedure means followed by the utilize collective consensus through vote tallying means;

l. normalizing the relative weights of said relationships showing causal or surrogate causalities found valid for said circumstance to total to 1;

m. determining a likelihood for each of said one or more possibilities as second cnxpts by Bayesian analysis utilizing an a priori weighting from the predetermined characteristic of said predecessor first cnxpt and said normalized relative weights of said relationships showing causal or surrogate causalities found valid for said circumstance;

whereby the data associated with cnxpts and relationships is used to determine an expected result given the wisdom of the crowd within a circumstance defined by at least one user using Bayesian data analysis on a logical view of data constructed from the present characteristic values, traits, purlieu, and relationships of said set of cnxpts and characteristics of relationships valid during the circumstance using the fxxt structuring prescribed, and a mathematical description of the knowledge of the crowd as collected data wherein a researcher'"'"'s intentions are lowered in effect by the crowd reallocates the beliefs as shown as the posterior belief by Bayes'"'"' rule and the accepted causalities or surrogate causalities used within the logical view extracted in domain-specific models, stitching together a vast pool of bite-sized micro-tasks involving potentially thousands of interacting data systems that are constantly changing, and whose solutions have difficult to understand structures, predictive quality, and unforeseen consequences can be modeled on a best available information basis from crowd-based inputs, where individual contributions can be processed for a flexible collaborative environment to better address the most challenging issues, and where prediction quality levels can be improved by fxxt specification and parameter alteration without altering raw data or collected crowd wisdom as well as by combination of the research of a plurality of users, allowing loose or team collaboration asynchronously over long timeframes with innate reuse modes of interaction for building on other researcher'"'"'s work that crowdsourcing alone cannot achieve to achieve scalable interaction by a diverse crowd.

302. The method of claim 16, for determining decision tree choices, further comprising:

a. extracting a plurality of subsets of relationships between cnxpts from a commonplace, each subset described by a fxxt, such that at least one relationship extracted is in a subset defined by a fxxt that, in the user'"'"'s opinion, defines that a first cnxpt on a first end of the relationship is a decision point for making alternative choices one of which is the choice of the state defined by the second cnxpt on the opposite, second end in the relationship, the relative quality of that choice determinable by the relationship'"'"'s weight, the presence of the selection of said second cnxpt from said first cnxpt termed an choice availability, said second cnxpt termed a choice outcome state, said connection between said first cnxpt and said second cnxpt termed a transition;

b. multiplying, for each subset obtained from a fxxt, the weight of all relationships in the subset by a coefficient stated for the fxxt, according to fxxt extraction of map generation process means;

c. determining a consensus regarding each transition possible by summarizing the weights of all instances of transition relationships between each pair of a first cnxpt and a second cnxpt where said pair exists in the extracted set of relationships, according to collective consensus through vote tallying process means;

d. summarizing the weights of all instances of non-transition relationships between each pair of a first cnxpt and a second cnxpt where said pair exists in the extracted set of relationships, according to collective consensus through vote tallying process means;

e. considering only transition relationships, form hierarchical transition to choice outcome state chains based upon most heavily weighted summarized transition relationships according to basic descending tree extraction of map generation process means;

f. considering only transition relationships not used already for tree formation, form second hierarchical transition to choice outcome state chains based upon these remaining summarized transition relationships according to enhanced descending tree extraction of map generation process means;

g. generating a Bayesian network from a commonplace;

h. generating a decision tree from a commonplace;

303. A computer-implemented method for predicting best decision tree choices from decision tree of claim 302, comprising:

a. generating a Bayesian network from a commonplace;

304. A computer-implemented method for predicting best decision tree choices from decision tree of claim 302, comprising:

a. generating a forest from a commonplace such that each node is of a type selected from the group consisting of;

a question;

a potential completion of a decision regarding a question;

a determination required before a question may be answered;

an a priori event that is also a potential completion of a question; and

an outcome a posteriori event having a calculable expectation value and conditioned on an a priori event;

such that possible transitions and condition are based upon answers to a question and likelihood that an outcome is attained by initiating or answering is based upon a stated probability density or mass function;

b. simulating by a model on the Bayesian network from a commonplace to determine likely expectation values for outcomes;

whereby the best decision according to a commonplace extraction is determined.

305. The method of claim 16, for determining decision tree classifier structures, 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;

d. walking from root to leaf of the structuring, choosing a branch in the classifier based upon choosing the 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.

306. The method of claim 16, for determining decision tree classifier structures, 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;

d. walking from root to leaf of the structuring, choosing a branch in the classifier based upon choosing the best match of child by the one having the closest matching of traits to the goal;

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

308. The adding and refining said commonplace of claim 241 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;

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 consisting 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 relationships 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, 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 relationships 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, such that 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, appropriateness of said notice determined by;

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 relationships and term ttx meaning hierarchy relationships 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 relationships and term ttx meaning hierarchy relationships 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 relationship info-item distance by including into said fxxt additional instances of similarity relationships and term ttx meaning hierarchy relationships having one or more of said marked term cnxpts as endpoints and marking said instances of similarity relationships and term ttx meaning hierarchy relationships as having said fxxt for the purpose of the instant similarity illustration, and then marking all cnxpts serving as endpoints of said newly marked relationships as also having said fxxt for the purpose of the instant similarity illustration; and

07. determining effective weights and directions for summary relationships between said cnxpts of said cnxpt type summarizing all relationships of type of said choice of one or more relationship info-item types to be used as a determinant of differentiation between said cnxpts of said cnxpt type according to utilize collective consensus through vote tallying function 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 consisting of;

01. ttx match indication to a user viewing said co-location map such that 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 such that 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 consisting 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;

03. a command from a user expressing a belief that an info-item has veracity of a low level and generating a vote accordingly;

x. locating, according to continuous processing means and a system preference setting, a first info-item meeting a condition selected from the group consisting of;

01. having a value determined by an analytic executed according to consensus determination process 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 process 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 process 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 by consensus determination process means concerning veracity such that 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 consisting 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 by existence vote summarization process means concerning existence such that 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 consisting 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 by consensus determination process means concerning the belief that said first info-item should be deleted such that 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;

xi. logging, according to continuous processing means and a system preference setting, actions taken meeting a condition selected from the group consisting of;

01. wherein said system preference is false, not set, or is not implemented, deleting of said info-item is not logged; and

02. wherein otherwise, deleting of said info-item is logged for tracking of historic operations;

whereby redundant ttx, cnxpt, and relationship info-item instances are eliminated from said commonplace automatically or upon request or approval by users;

whereby users participating in the process of curation are informed of needed attention to curate concepts in the commonplace;

whereby a consensus is illustrated regarding the meaning of selected terms as the result of data arguing voting and data integration with previous knowledge is achieved based upon machine analysis and human insight to iteratively improve the stored understanding of meanings of terms as being within in contexts within a structured categorization of term meanings and whereby an understanding of a phenomena may be investigated using continually evolving knowledge based upon continually improving of meanings within massive data by relying upon a dynamic combination of automation and crowd wisdom for machine learning;

whereby said user is empowered to suggest inappropriateness of an info-item;

whereby a cleanup according to the wisdom of the crowd may occur considering the voting weights of users and various system analytics and may occur over a period of time with or without a phasing of schedule and through collaboration without a requirement for direct dialog;

whereby the use of identity indicator ranking by weights leads to a higher degree of clarity by ranking, and the use of fxxts reduces conflicts between meaning confusion caused by similarity of terms across different categorization bases is mitigated;

whereby automated combining of sufficiently identical info-items may be performed;

whereby automated aging of info-items may take place;

whereby a history may be kept where a logging of actions is required;

whereby information that makes no sense because of errors by users, typos, or nonsense entries by children or others, as well as duplicates, disconnected or unlinked entries, and old, junk, backed up, off-topic, imprecise, or unnecessary data may be removed in a controlled authority control process automatically utilizing collective consensus; and

whereby consistency in the naming or category naming will serve as a virtual international authority file for info-items exposed to users, or unexposed but collected from search phrases used, synonym associations, description variants, name variants, ‘

superseded’

or deprecated names, thesauri or translations entered;

whereby quality improvement by consensus-based naming, description, and interconnection among category cnxpts and other info-items and information resources will improve the value of the combined data; and

whereby the tracking of the decisions made toward identifying and collocating concepts lets users assume that a term or phrase will refer to a particular concept, that name variations will be brought together under one form, and that relationships are proper.

309. The curation of claim 308 to eliminate redundant information and keep information properly connected, further including:

a. suggesting that a pair of cnxpts consisting 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;

whereby roots are eliminated in favor of additional branching.

310. The accepting commands from user to add or refine said commonplace;

of claim 308 to accept authoritative changes, further including;

a. marking vote as authoritative to retain an error correction vote to apply automatically if a new data set contains the same error;

whereby a correction may be made to improve said commonplace of knowledge.

316. The utilizing said visualization of claim 223 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 it;

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;

whereby a file management system is provided to a set of users with the ability to organize said files as needed without moving files or permanently changing the storage structure and management of information resources or internal resources serving as information resources such as a reference to an electronic file or collection of electronic files, an electronic file, a references to a physical document or collection of physical documents, an image of a physical document, a reference to a web page, or some other object is made possible in a single apparatus and categorized regardless of the type of information resource or internal resource serving as an information resource.

317. The utilizing said visualization of claim 223 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;

whereby the collective understanding of legal issues and preparation for litigation are more efficient because legal theories, precedents, and factual issues and evidence can be used to categorize said documents involved in litigation by use of the multi-classification tools of said system at various stages and said file system indexing tools provide workflow facilities for team operations.

318. The utilizing said visualized map of claim 223 to 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, ontology manipulation for mapping fxxt specific ttx map generation, and forming predictions means;

d. showing state of obsolescence of a cnxpt according to tpl based prediction means; and

e. generating suggestions of differentiations of a cnxpt possibly usable form a new cnxpt according to generate TRIZ based candidate suggestions;

whereby standard and plug-in algorithms provide methodology based suggestions to a user for innovation to break through gaps, find hidden information, efficiently apply ideation, and apply theories, principles, laws of nature, or TRIZ methodologies.

319. The utilizing said visualization of claim 223 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;

d. such that 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;

whereby methodologies or workflows created by experts and delivered at low cost turn the lead qualification process for a funding source into profitable self-help product tool disintermediating off-line service providers, speeding collection of information, directing said user toward better planning, providing investors with better information at earlier stages of commercialization, making liquidity events earlier in the commercialization process for said idea, provide a lead generation facility as well as a customer qualification tool for service providers, and a task management structure.

320. The collecting commercialization status information of claim 319 to also manage investment pools, further including:

a. 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 its graduation guidelines;

b. accepting accounting of funding;

c. providing tools for defining entrant due diligence information requirements as a methodology or workflow;

d. accepting information from entrant candidates for application for entry and for due diligence;

e. preparing notices offering entry to qualified startups;

f. defining progress information requirements as a methodology or workflow;

g. accepting progress reporting information for enrollee startups;

h. providing tools for making a market by negotiating graduations to sell held stakes to another pool or a funding source according to innovation investment pools means;

i. providing tools for evaluating enrollee startups;

j. providing tools for preparing startup progress report;

k. providing tools for suggesting enrollees for termination;

l. providing tools for enforcing rules and confidentiality;

m. providing tools for managing said pool and participants according to innovation investment pools means; and

n. summarizing value of said pool and generating reports;

whereby a structured approach for improving the potential of a startup through fostering commercialization while also reducing risk for investors is offered resulting in development of a record of progress by said startups involved and heightened visibility of said startups without traditional fund raising problems to prepare vetting information for companies seeking investment for crowdfunding, traditional fund raising, intellectual property sales, or other exits.

321. The utilizing said collective consensus of claim 223 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 an estimate 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.

322. The accepting a prediction definition of claim 321 to also provide corrective changes, further including:

a. accepting an observation that a prediction may be incorrect;

b. entering into a workflow a task for said observation for gaining assistance;

c. sharing said observation of an error with others for communal action to solve said observed problem;

d. providing a structured walk-back work tool for drill-back examining the derivation trees for predictions and intermediate results according to the prediction correction mechanism means;

e. presenting fault-isolation questions to a user during use of said structured walk-back work tool;

f. accepting an observation that an intermediate step result value in a prediction calculation is likely wrong and forking said workflow task in two;

g. accepting an estimate for an intermediate step result value in a prediction calculation to provide an assertion base value, default value, or temporary value;

h. accepting an estimate for a prediction result to provide an assertion base value or default value;

i. assisting said user to locate the offending step in a prediction calculation procedure according to said prediction correction mechanism means;

j. assisting said user to determine the source of an error or inappropriate basis for a prediction according to said prediction correction mechanism means;

k. accepting said user'"'"'s vote to correct a base cause for the incorrect prediction;

l. accepting incremental correction of prediction definitions according to said prediction correction mechanism means;

m. recalculating said prediction upon any change;

n. manage the coordination of presentation of the issue in one or more fxxts to assist said user to see meta-predictions; and

o. managing said workflow of said solution effort tasks;

whereby debugging by drill-back is provided to any user who believes that something is wrong with a prediction or a model and intends to examine said issue toward correction.

323. The accepting a model definition of claim 321 to also predict, further including:

a. accepting a prediction definition for a fxxt specification to establish a repeatable procedure for generating a value for said prediction from said commonplace based upon said fxxt;

b. calculating preliminary predictions not depending upon hierarchy according to preliminary prediction calculations means; and

c. calculating prediction for each cnxpt at a level by level of a formed fxxt 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 so that relationship info-item votes for shaping the fxxt based taxonomy, info-item properties, cnxpt attached information, and collected user interest information are used as base information for the prediction so that votes on trait matching, associations, occurrence relevance, other properties, and occurrences to traits, purlieu, or information resources may all be considered in said prediction and said fxxt based organization of said commonplace is analyzed to provide predictions according to said prediction specification to provide a probability of a leaf'"'"'s technology existing at a certain time, the distribution of probability of a leaf'"'"'s value at various times and in sum, the value of a category of technologies for investment, the timing of satisfaction of technological requirements, the strength of competitive technologies and products, the probability of fruition, and the timeframe for a technology or product obsolescence, or some other property.

324. The utilizing said collective consensus of claim 98 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 the key encryption process 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 said key encryption process means;

whereby the organization of said controlled commonplace cannot be fully understood or reassembled by anyone having insufficient access to said controlled commonplace based upon the plurality of said individually identified partial records communicated.

340. The adding and refining said commonplace of claim 1 to provide external marking for organizing data for applications, further including:

a. defining a fxxt;

b. mark an info-item of the commonplace as being a member of the fxxt;

c. granting access to the commonplace and the fxxt marked data to an automated process;

d. optionally creating a reference in a cnxpt to a data item in an automated process;

e. optionally specifying a reference in a linkage mechanism to a cnxpt;

whereby a platform for implementation of knowledge tools for specific application domains such as configuration management, issue management, software design and analysis, enterprise resource planning, process pattern recognition, financial modeling, causality and root-cause analysis, and others;

whereby an external marking structure where nodes of an ontology can be marked as having a position in a taxonomy and the position is conveyed to an application process;

whereby if a cnxpt references a cell of a spreadsheet, then the taxonomies are roll-up specifying mechanisms for the spreadsheet application process;

whereby cell-like calculation equations on the taxonomy cnxpts nodes, such as sum of an attribute of children, average of children'"'"'s attribute, sum of sibling'"'"'s attribute, my index within a ranking by sibling'"'"'s attribute, prime parent'"'"'s attribute, sum of all parent'"'"'s attribute are available for use by external process;

whereby if a set of rows on a sheet where each row is referenced by an ontology cnxpt, and each cnxpt has a set of attributes, can, for instance, immediately adapt to a change of an organizational structure by a manager who rearranges the taxonomy of organization of the company.

341. The method of claim 249 to compute a value for a product or technology, wherein:

a. identifying a relationship info-item between a first cnxpt and a second cnxpt in a commonplace of information wherein said relationship info-item said first cnxpt comprises a property stating a point value or value distribution applicable to said second cnxpt;

b. summing said property of each first cnxpt having a relationship with said second cnxpt to form a value for said second cnxpt according to primary tcept value prediction process 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;

342. The method of claim 341 to compute a value for a product or technology, wherein:

a. form a timeline by ordering conceptual meanings by a time point associated with said theory, principal, law, or practice, said time point selected from the group consisting of;

initial recognition of theory, principal, law, or practice, mid-point, point at which said theory, principal, law, or practice is anticipated to become obsolete, point at which products based upon said theory, principal, law, or practice are anticipated to be altered or replaced to conform to new theory, principal, law, or practice, median of distribution, mean of distribution, and any other specified theory, principal, law, or practice summarizer, wherein the form of said timeline is of the group consisting 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;

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;

364. The method of claim 2, to position cnxpts on a map being generated, further comprising:

a. deriving a position of an initial cnxpt without children in an extracted structuring of cnxpts based on relationships 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 relationships of the parent cnxpt with cnxpts selected from the group consisting 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 map based on the positioning of the cnxpt.

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

365. The method of claim 2, to position cnxpts on a map being generated, 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;

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 consisting of;

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

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

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

366. The method of claim 2, 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 relationships 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 relationships of the precedent cnxpt with cnxpts selected from the group consisting 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 based on the positioning of the cnxpt.

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

367. The method of claim 2, to position cnxpts on a map being generated, 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;

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 consisting 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; and

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

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

368. The interpreting said fxxt specification for said fxxt of claim 223, further including:

a. determining if said fxxt specification is easily determined or not easily determined by checking each fxxt calculation step in said fxxt specification to determine if it is easily determined and if not, marking said fxxt specification as not easily determined; and

b. determining, upon occurrence of an event changing the resulting composition of relationships in the extraction by fxxt or the consensus weighting thereof sufficient to alter the ordering by weight for forest extraction, a revised forest extraction;

whereby the ability is provided to find and mark member cnxpts and associations by interpreting a fxxt specification, and to create weighted hierarchical tensors to point specifically to at most one parent cnxpt in said fxxt to provide for map generation based upon consensus strength.

36. A computer-implemented method for managing an information organization system, comprising:

a. providing a computer storage to store a commonplace of information comprising a plurality of cnxpts and relationships among the plurality of cnxpts;

b. generating a map for a domain of wisdom comprising an organization of knowledge of cnxpts connected with each other via relationships in one of a hierarchical manner, a directed graph manner, or a structure comprising a combination thereof, based on information derived from the plurality of cnxpts and the relationships among the plurality of cnxpts;

c. generating a rights policy for an info-item within the organization of knowledge; and

d. enabling a user to access an info-item within the organization of knowledge based on the rights policy.

whereby innovation inefficiencies are reduced through information reuse, sharing of analysis, and crowdsourcing to collect the wisdom of crowds, financial gain may be obtained from operating said system, the service provider may collect, track, and mine the demographic characteristics of startups to allow reporting on entity progress, reliability, risk, and value.

37. The computer-implemented method of claim 36, wherein the info-item comprises a cnxpt.

38. The computer-implemented method of claim 36, wherein the info-item comprises a relationship.

50. The method of claim 36, to enable verifiable and secure transactions regarding ideas, comprising:

a. providing a computer storage to store a commonplace of information comprising a plurality of cnxpts and relationships among the plurality of cnxpts;

b. generating a cmmv for a domain of wisdom comprising an organization of knowledge of cnxpts connected with each other via edges in one of a hierarchical manner, a directed graph manner, an undirected graph manner, or a structure comprising a combination thereof, based on information derived from the plurality of cnxpts and the relationships among the plurality of cnxpts;

c. providing a value creation structure comprises a group of related cnxpts by;

i. generating ownership rights for a set of cnxpts;

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;

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 according to the ownership right.

whereby peer signatories to service agreement create and share in the collective wealth and value held by agreement and participation in exchange market and transactions managed with others;

whereby, optionally, the service manager is uninvolved in ownership of assets on which stakes are claimed or for which a conceptual identification of a physical record is held in the collected immutable record ledgers of the system;

whereby the rights of owners are established on conceptual assets, possibly linked to physical assets, by staking a claim to the conceptual space possibly indicating a physical asset;

whereby management and record keeping is provided by authorized agent upon service agreement;

whereby the management ensures the uniqueness of the asset claimed;

whereby inventorship may be traced and shared inventorship managed to ensure fairness by traceable negotiation and traceable performance of creativity and pursuit of concept;

whereby fairness of compensation to claimant is a function only of the market and traceable negotiation for rights, as well as franchise exclusivity if agreed upon or government provided;

whereby an agreement for use of the management systems'"'"' services forms an umbrella agreement for acceptance of terms of authenticity of records and transaction validity;

whereby rights of owners are protected by the use of rights agreements and deed-like devices stored as immutable records;

whereby access to records showing ownership is restricted and requires authentication of access requester to management system;

whereby the management process is efficient, involving an owner of rights selling, a buyer of rights, and a trusted electronic transactions management system acting within the scope of a service agreement to record and to protect the authenticity of the transaction only;

whereby transaction clearance is performed, where activity is required outside of the transaction recordation, by the service manager or their agent or by other by contract between parties;

whereby assistance in obtaining government grants of franchise is offered, efficiently, by the service provider if appropriate and requested by an ostensible owner of a qualifying claimed stake;

whereby monetization is possible according to established agreements between parties involved, and the service agreement for record management, by transfer of ownership rights;

whereby said immutable records represent agreements regarding ownership of claimed stakes in concepts defined by one or more differentiations from one or more contexts of concepts;

whereby the rights of ownership may be sub-divided by established procedures of high integrity, the rights specifically stated by written agreement stored upon completion with backup documents regarding negotiation to establish the record of intent, all in immutable records;

whereby aggregation of agreements regarding ownership may be pooled to provide collective ownership to the owners of the pool;

whereby pool ownership may be shared;

where agreements regarding ownership in pools may be transferred between pools based upon graduation transactions;

whereby immutable records are held to form a ledger of transaction history regarding ownership of all claimed assets;

whereby the identity information of each immutable record is obscured to eliminate usefulness outside of the context of the proper collection of records in a stored location for replication;

whereby management over immutable records is provided by a distributable computer structure to ensure existence;

whereby management system ensures the integrity of the retention of the immutable records securely in a plurality of data stores;

whereby owners are provided an identity and access for that identity to a virtual portfolio and management commands;

whereby owners may control assets through portfolio management commands, applying changes to a virtual wallet of assets owned, and supporting the use of the portfolio contents as an index to related information of value to owner;

whereby managing service may collect, track, or mine the characteristics of participants to allow reporting of asset reliability, risk, and value only within the scope and to the degree provided in the service agreement of a signatory to the service, except as needed to protect immutability and prevent fraud or system-wide risk;

whereby share of value represented by agreement is immutable except by valid authority and rules as established by agreement;

whereby information of ownership record is immutable except by transfer, voluntary or forced by valid authority upon validated justification;

51. The method of claim 50, further comprising encapsulating origination data related to the ownership right and the corresponding cnxpt within a transactional data structure that is temper-proof;

52. The method of claim 50, further comprising encrypting data within the transaction data structure before distributing the transactional data structure.

54. The method of claim 50, further comprising deriving a chain of ownership changes based on the transaction data structure.

55. The method of claim 50, wherein the first transaction involves a first entity acquiring from a second entity at least one item selected from the group consisting of:

the cnxpt, and the set of objects represented by the cnxpt.

63. The method of claim 50, wherein each cnxpt within the commonplace of information comprises a first identifier that indicates an existence of the cnxpt as differentiated from the other cnxpts within the commonplace of information.

72. The method of claim 50, wherein the ownership right comprises at least one of a creation right, a use right, and a commercial right.

74. The method of claim 50, wherein the first transaction is an auction sale.

139. The method of claim 36, to empower creativity, comprising:

a. organizing for creativity and innovation;

b. incentivizing creativity and innovation;

c. collecting and categorizing a new idea;

d. extending creativity new idea collection and categorizing;

e. technology innovation and entrepreneurship;

f. incentivizing technical people to work on clearing the roadblocks to use of technologies;

g. improving the capturing and use of creativity;

h. improving the reusability of innovation workers'"'"' results;

i. improving use of the information collected for more efficient and effective innovation;

j. providing an iterative process to yield a continuous flow of new ideas;

k. providing an iterative process to yield a continuous flow of improvements to predictions;

l. empowering the reuse of the efforts of others over time;

m. incorporating and improving other'"'"'s understanding of relationships among technological concepts represented by tcepts, their timeframes stated by purlieu and their contexts represented by cntexxts, and the concept traits of technical concepts represented by cncpttrrts;

n. creating reusable understanding of the relationships between technology application domains and players to allow competitive strategists to summarize their research;

o. empowering progressive understanding of knowledge;

p. reducing the amount of work required of each individual user to assemble and categorize knowledge;

q. fostering innovation within society and within companies;

r. empowering effective collective and collaborative development of innovations;

s. empowering the sharing of innovation;

t. reducing the delay between innovations;

u. protecting collective development;

v. incentivizing entrepreneurs to start businesses based upon needed technologies;

140. The method of claim 139, further including:

a. accepting the addition of a new technology innovation idea as a cnxpt typed as such based upon user'"'"'s determining by navigation or because of a failed search goal that in said user'"'"'s belief the idea was an incremental innovation that could be added as incremental from an existing prior technology innovation idea represented by a cnxpt presented as a cntexxt by adding a new derivative cnxpt within the context of said existing prior technology innovation idea;

b. forming when a new idea is identified because we treat the idea as narrowing the scope of the enclosing idea, but not stating that it is the last possible idea so the identified idea is itself a cntexxt ready for population by yet newer ideas. making a void;

c. accepting user'"'"'s staking of a claim on said new technology innovation idea by stating ownership;

d. entering provenance information on said derivative cnxpt;

e. accepting user request to withhold release of said derivative cnxpt existence information;

f. accepting user request to withhold release of said derivative cnxpt descriptive information;

g. accepting further description of said new technology innovation idea represented by said derivative cnxpt;

h. publishing said new technology innovation idea such that other users may retrieve information about said new technology innovation idea or view it in context;

i. accepting a user request to offer said new technology innovation idea for sale;

j. accepting a user request to offer said new technology innovation idea for collaborative development;

k. accepting a user request to offer said new technology innovation idea for investment;

l. accepting a user request to seek intellectual property protection on said new technology innovation idea;

m. accepting a user request to retain negotiation information and status regarding any offer pertaining to said new technology innovation idea;

n. accepting a user request to retain development plans and status information regarding any efforts pertaining to said new technology innovation idea;

o. accepting a user request to constrain access to information pertaining to said new technology innovation idea;

p. accepting a user request to constrain access to particular portions of information pertaining to said new technology innovation idea;

q. tracking user interest as shown by retrieving information pertaining to said new technology innovation idea;

r. accepting votes regarding characterization of said new technology innovation idea;

s. accepting offers regarding said new technology innovation idea;

t. accepting information regarding said new technology innovation idea and adding said information to said derivative cnxpt as a vote regarding said derivative cnxpt or associated relationships, information resources or internal resources serving as information resources, or traits;

u. accepting modeling equations regarding said derivative cnxpt;

v. accepting a user request to provide or constrain access to personal information related to said new technology innovation idea'"'"'s originator;

w. accepting categorization requests from a second user situating said derivative cnxpt as pertinent to a category of said second user'"'"'s choice as represented by a cnxpt;

x. accepting categorization requests from a second user situating said derivative cnxpt as pertinent to a category of said second user'"'"'s choice;

whereby a new idea is prepared for publishing and reuse, included into competitive analysis, treated as a prospectus or as a research topic, treated as a meetup or open source project, limited for release to specific audiences, countries, experts, or investors with certain status, open a topic for questions from groups such as the product research group at a company or grad students available for projects, defining suitability as a solution to a requirement, defining it as a product ability to be made a part of a product, and other details.

141. The method of claim 36, to determine sharing of creative results, comprising:

a. uncovering the available technologies isolated in the mind of potential inventors now unable to find the appropriate means to get an idea into the reach of those able to use it;

b. determining currently existing and future demand for technology;

c. improving the current burdensome common ground for inventors, technology seekers and technology holders by creating incentives for each and cross incentives by providing a common search tool of broad scope that collects information valuable to each, serves as an organizing tool for other daily tasks, and is most effective if applied to areas that must be deeply indexed so that detail is available without confusion by an overabundance of less detailed information to allow sharing of knowledge and understanding of need and function at great specificity;

d. providing a knowledge sharing platform where technical problems and potential solutions are available to reduce the chaos created due to disorganization and to avoid replication of effort in information organization;

e. providing a knowledge sharing platform where technical problems and potential solutions may be discussed while allowing users to variously balance or reconcile the sharing of knowledge and the cost of exposing valuable intellectual property;

f. providing a structure to capture for intellectual property owners what is known by others about said intellectual property;

g. providing a structure to access technologies that surpass a user'"'"'s invention in solving a larger application of technology requirement represented by an appcept;

h. incentivizing technology developers and awarding creativity to shape concepts represented by cnxpts into marketable products and services;

i. providing a structure to form teams for implementing technologies;

j. providing a structure to manage the rapid communication in an investment market within the parameters of invention protection;

k. moving ideas from those who have them to those who can generate higher value from them while protecting the inventor;

l. providing an anchoring point to which new material can be related in a cognitive structure;

145. The method of claim 36, for defining a matching economy marketplace by structuring collaborative decision making regarding specific instances of types of concepts collected into a commonplace, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. preparing, by at least one processor, 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 process means;

f. configuring workstation computers to communicate with server computers for transferring information and commands;

g. granting access to said commonplace;

h. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

i. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

j. accepting a specification of a methodology defining a workflow of steps, actions, and events in a matching transaction, said steps, actions, and events from the group consisting of;

preparation, offering, negotiation of terms, acceptance, fulfillment of obligations, obligation precedence determination, status tracking of transaction, transaction record information retention, and transaction record access control;

k. recognizing a concept represented by a cnxpt as a type subject to a methodology;

l. building infrastructure for easing the collaboration involved in realizing said matching opportunity;

m. providing said infrastructure to a plurality of users of said commonplace;

n. providing notification to said plurality of users that said concept instance of said concept type has been created;

o. providing narrow chatting between said first user and said second user to negotiate collaboration terms;

P. tracking the negotiation and retaining a record of said negotiation;

q. tracking the transmission of deliverables;

r. tracking said performance regarding promises made;

s. providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas; and

t. defining a matching opportunity regarding said concept type;

u. accepting a definition of a concept instance of said concept type into said commonplace;

v. accepting interest shown regarding said concept instance and collecting user interest information;

w. accepting a request for involvement into said matching opportunity by a second user;

x. granting access to commonplace of information contents regarding said concept instance having said matching opportunity to said second user;

Y. setting default parameters for conducting negotiation of collaboration terms;

z. accepting a command from said first user to alter a deadline for negotiating collaboration terms;

aa. accepting a command from said first user to grant additional access to commonplace of information contents regarding said concept instance having said matching opportunity to said second user;

bb. accepting a command from said first user to register agreement or disagreement on, or termination of talks regarding said negotiated collaboration terms;

cc. accepting a command from said second user to register agreement or disagreement on, or termination of talks regarding said negotiated collaboration terms;

dd. registering a successful or failed negotiation;

ee. registering a failed negotiation upon passing of time beyond said deadline;

ff. removing from said second user all grants beyond a specified set to access commonplace of information contents regarding said concept instance having said matching opportunity;

gg. initiating a methodology or workflow for managing the carrying out of said collaboration according to said negotiated collaboration terms;

hh. accepting commands from said first user or said second user to accept and transmit deliverables required by said collaboration according to said negotiated collaboration terms;

ii. accepting commands from said first user or said second user stating an acceptance of performance regarding promises made as required by said collaboration according to said negotiated collaboration terms; and

jj. confirming completion of said agreement based upon said negotiated collaboration terms;

kk. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting of;

i. to view content of said commonplace;

ii. to add or refine content of said commonplace utilizing said collective consensus and effect change;

iii. to navigate around a visualization of said commonplace; and

iv. to request a search for wisdom;

whereby innovation development and other projects may be specified into defined collaboration tasks, collaboration paradigms may be chosen for how collaboration is to be accomplished and intrinsic or extrinsic motivations for participants agreed to, collaborators may be organized to accomplish tasks toward said project, resources may be organized to accomplish tasks toward said project, said project information may be protected, negotiations, commitments and completions may be tracked, and progress may be reported;

whereby inefficiencies are reduced through information reuse, sharing of analysis, and crowdsourcing to collect the wisdom of crowds, and collaboration based upon agreed terms may be obtained from operating said system, the service provider may collect, track, and mine the demographic characteristics of startups to allow reporting on entity progress, reliability, risk, and value; and

marketplace efficiency is greatly increased for carrying out transactions of any complexity so long as the terms and acceptances can be stated specifically.

146. The method for defining a matching economy marketplace of claim 145 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;

whereby innovation inefficiencies are reduced through information reuse, sharing of analysis, and crowdsourcing to collect the wisdom of crowds, financial gain may be obtained from operating said system, the service provider may collect, track, and mine the demographic characteristics of startups to allow reporting on entity progress, reliability, risk, and value.

147. The computer-implemented method of claim 36, wherein the info-item comprises a fxxt.

148. The computer-implemented method of claim 36, wherein the info-item comprises a irxt.

149. The computer-implemented method of claim 36, further comprising determining a rights policy of an info-item as a function of being marked by a fxxt.

150. The computer-implemented method of claim 36, further comprising determining a rights policy of that represented by a cnxpt as a function of a rights policy of a cnxpt info-item.

151. The computer-implemented method of claim 36, further comprising determining a rights policy of that represented by a irxt as a function of a rights policy of a irxt info-item.

152. The computer-implemented method of claim 36, further comprising

a. automated and manual cataloging of information prior to study and incenting users to add and refine said information

b. modeling based upon the organization of cataloged information

c. modeling based upon the dynamic organization by consensus or non-consensus of cataloged wisdom of crowd information

d. empowering dynamical competitive intelligence study updating by automated and manual addition, refinement, cataloging, and mapping of information regarding the study topic and incenting users to add and refine said information by providing usefulness of their efforts for other purposes

e. empowering users to obtain profit by the sale or leasing of information of specific details needed for decision making or modeling;

f. providing a dynamic technology road mapping framework

g. providing a dynamic report regeneration framework

h. retaining the infrastructure for studies for reuse with new information

i. indexing by meaning as clarified and refined over time to shape dynamic cataloging with forward and reverse traversal;

j. providing the ability to conduct prior art searching for ideas of the future where even the prior art will not be in existence

153. The method of claim 50, wherein the ownership right comprises at least one of a wholly owned right, a partial owned right, and a transiently owned right.

155. The method of claim 50, wherein each first relationship within the commonplace comprises one first relationship endpoint cnxpt identifier that indicates an association of a first cnxpt with a second cnxpt.

158. The method of claim 50, further comprising providing multiple computer storages that store received subsets extracted from the commonplace of information.

159. The method of claim 158, 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 may be preserved by timeframe.

160. The method of claim 50, wherein each first cnxpt within the cmmv participates in zero or more first relationships that indicate an association of the cnxpt with another cnxpt determinative of a location of the first cnxpt with respect to the other cnxpt within the cmmv, wherein said first relationship comprises a relationship identifier.

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 makes difficult the recombination of exported data sets into a re-creation of the central commonplace of information.

165. The method of claim 50, further comprising:

a. providing a value creation structure comprises a rights to a cnxpt created by;

i. generating ownership rights for the cnxpt;

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;

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 according to the ownership right;

whereby ownership for specific use or application may be delineated.

166. The method of claim 50, further comprising:

a. providing a value creation structure comprises a rights 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 according to the ownership right with respect to cntexxt;

whereby ownership for specific use or application may be delineated according to a cntexxt of a structuring of knowledge.

169. The method of claim 50, 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;

whereby an entity may be involved in modeling; and

whereby an entity may be utilized in categorization.

171. The method of claim 50, further comprising defining a transaction to be represented by a cnxpt

whereby a transaction is made available as a binding point;

whereby a transaction may be involved in modeling; and

whereby a transaction may be utilized in categorization.

172. The method of claim 50, 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;

c. registering a right to a portion of a cntexxt occupied by the cnxpt;

whereby ownership for specific differentiated asset may be claimed by staking a claim to the differentiated asset;

whereby a space claiming operation wherein control over a space defined by a staking of claim is granted to the user staking the claim;

whereby ownership information regarding the space defined by the staking of claim is collected;

whereby an initial transaction to initiate an immutable transaction data structure is generated.

173. The method of claim 36, for providing categorization services to customers, comprising:

a. providing a computer storage to store a stigmergic commonplace;

b. providing a plurality of computers with server functions for managing said commonplace;

c. providing a plurality of computers hosting workbench functions for workbench users to interface with said commonplace;

d. managing the organization of said commonplace,

e. managing said commonplace for distributing information content extracted from, and by collecting information to be added to said commonplace to and from said at least one of a plurality of computers hosting workbench functions;

f. initiating execution of communications management software executing on said at least one of a plurality of computers hosting workbench functions to control those computer'"'"'s communication connection, synchronization, and transfer of information with said at least one of said computers with server functions for managing said commonplace;

g. 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;

h. ingesting a source object of said plurality of source objects into said commonplace;

i. defining at least one source object provenance authority fxxt to identify in the catalog of said commonplace said source object;

j. ingesting a plurality of info-items into said commonplace from said source object;

k. ingesting a plurality of relationships into said commonplace from said source object;

l. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process 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;

m. updating said data structures for source object access control;

n. updating said data structures for source object cataloging, tracking provenance, by controlling access, by collecting voting on veracity of data;

o. 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;

p. presenting extracted data sets as subject matter for other application software local or distributed processes; and

q. processing application software local or distributed processes commands for controlling user interface functions and performing automated tasks resulting from user actions;

whereby resulting data confederation of said commonplace is achieved, instilling iterative, incremental, traceable quality improvement of diverse and continually evolving knowledge obtained, quality rules, and schema over time by empowering humans to utilize flexibly tailored extractions structured by use case context selection, business and quality rule application, provenance, and access right, to add knowledge, change previous beliefs, obtain automatic algorithmic assistance, to form consensus mode quality decisions, to set metrics for quality issues by causality, provenance, and responsibility, to correct prior actions, to assess quality to achieve a best available basis for understanding that is current, accepted, repeatable, and reusable by appropriate users, reducing inefficiencies through information reuse and effective curation;

whereby the categorization schemes of an organization are made dynamic and harmonized in a traceable meaning change manner;

whereby a reclassification of items having a certain classification is controlled and any calculation performed does not count raw data of said items doubly or not at all;

whereby classifications by old and new versions of schemes may be seen side by side to show similarity as a whole and by similar ttxs;

whereby products offering these classification indices are improved to become more dynamically organized to improve efficiency;

whereby products or items indexed by a classification indices of one jurisdiction may be classified in a similar indexing scheme in another jurisdiction by harmonization.

189. The method of claim 36, to make available investment opportunities for organizations developing technologies related to concepts within a stigmergic commonplace of information, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. preparing, by at least one processor, 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 process means;

f. configuring workstation computers to communicate with server computers for transferring information and commands such that improperly configured workstations will fail to communicate when requesting particular access of a pre-defined nature;

g. granting or rejecting access to said commonplace for a given type of interaction;

h. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

i. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

j. 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 consisting 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;

k. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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 a business entity can be formed around the idea and the value of the entity can be determined in an options market;

whereby investment pools are capable of being milestone specific;

whereby as a graduation occurs a negotiation may take place to set a value for the entity at that point in time;

whereby negotiations are less structured at the lowest investment pool level and tighter in higher levels of investment pools;

whereby the results from these predictions are combined with the results of prior predictions for the higher level categories around the technology and with predictions about what applications of the technology would have to then form an improving prediction of value and time of fruition;

whereby investment pools help to determine the prediction of values;

whereby the prediction of the higher levels of a categorization of entities and ideas are inherited to also help to form a basis for values of the new ideas and the investment pools based upon them;

whereby new interest is formed because of the excitement in specific markets;

whereby the predictions of the past give presumptions to the predictions of the future and also the value of an investment pool in conjunction with other factors considered;

whereby predictions can be made even if a pool is charitable, is a virtual game, or is a test markets as they are comparable in value to market based entities;

whereby an entity seeking crowd funding can be rated for progress made, for value, for status by their documentation, for quality by their level of communication to allow for the ‘

vetting’ and

qualification required by the law;

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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

192. The method of claim 36, for collaboratively developing technologies related to concepts within a stigmergic commonplace of information, comprising:

a. providing a computer storage to store said commonplace;

b. providing an interface for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. preparing, by at least one processor, 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;

e. configuring workstation computers to communicate with server computers for transferring information and commands such that improperly configured workstations will fail to communicate when requesting particular access of a pre-defined nature;

f. granting or rejecting access to said commonplace for a given type of interaction;

g. displaying to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

h. 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 consisting 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. assignee) can be formed around the idea and the value of this can be determined in an options market. the investment pools are milestone specific. when the graduation occurs, a negotiation takes place, giving us a value for that entity at that point in time. these negotiations are extremely loosey-goosey at the lowest level, and much tighter in higher levels of investment pools. the results from these predictions are combined with the results of prior predictions for the higher level categories around the technology, and with predictions about what applications of the technology would have, and a better prediction of value and time of fruition are formed.

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;

i. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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; and

whereby said user may investigate phenomena by reusing knowledge coalesced and curated by them or others, and acquiring new knowledge, correcting and integrating it with previous knowledge with the assistance of others and applying machine algorithms to continually evolve understanding of the phenomena, all at massive scale, so that knowledge may be used and extracted; and

whereby data confederated by natural unification is provided for search and connection of a massive number of ingested or constructed data sources using both machine learning and advanced collaboration capabilities while resolving duplications, errors, and inconsistencies among source data with efficient authority control over attributes and records by use of human guidance weighted by expertise with continual quality improvement and whereby entrepreneurs may readily find teams for a project and may readily learn of new ideas for development;

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby universities may better manage technology transfer by advertising technology and patent clearance operations by detecting potential loss of intellectual property by improper exposure;

whereby students, professors, and technologists may stay current with technology;

whereby associations studying technology or industries may better reach constituencies and consign data for sale;

whereby consultants providing competitive intelligence may improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby market study companies providing product area analyses may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby crowd funding sites may readily obtain needed information for vetting companies raising funds;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby futurists and science fiction writers interested in potential futures have a shared base of analysis tools;

whereby donative grantors may find appropriate formative technologies to fund;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific topics without burdensome organizing because others have developed useable categorizations and will have available a very modern basis for thinking and an organized history available, according to ideation, finding searching query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

197. The adding and refining said commonplace of claim 139 to locate a concept more similar to that thought of by a user comprising sorting of results by appropriateness to the concept sought.

200. The method of claim 36, further including:

a. providing a product planning process and methodology or workflow utilizing the categorization of the applications software map generation means and said commonplace data;

b. providing modeling tools for product what if value analysis tuned to operate on said commonplace and said categorizations produced by said applications software map generation means;

c. providing product management methodologies or workflows tuned to operate on said commonplace; and

d. providing product planning information repository structures for managing and sharing product planning information on an access controlled basis;

whereby company profiles, requirements of technology, application requirements, and product lines are maintained, and product lines and products are planned and managed using data of said commonplace obtained from the crowd and categorized with the assistance of said crowd, but also with data maintained privately and linked to said commonplace categorizations, providing a blend of protected private, open source and for fee data all categorized uniformly.

201. The method of claim 36, 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. 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;

c. 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;

d. 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;

e. 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;

f. providing application software tools for indicating commonalities and variabilities between concepts represented by cnxpts;

g. providing application software tools for indicating commonalities and variabilities between products represented by cnxpts;

h. providing application software tools for indicating commonalities and variabilities between technologies represented by cnxpts;

i. providing application software tools 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;

j. providing definitional tools for describing multilevel application domain models to hold, organize, communicate, and track relevant requirement and timing information;

k. providing a requirements engineering mechanism by which the complete set of requirements for a product line or for a particular product can be produced;

l. providing a structure for differentiation between applications of technologies represented by appcepts based upon requirement criteria;

m. providing a structure for differentiation between products represented by cnxpts, each such product to address an applications 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.

n. determining market segments by requirements;

o. determining inter company and intra product line comparators;

p. determining market segment requirements;

q. providing analysis tools for product area domain analysis from the group consisting of;

entity and competitor strengths weaknesses and assets, product objectives scenario description tool, brainstorming methodology, brainstorming workflow, product objectives tracking tool, use case description tool, change cases description tool, product application description tool, product application requirement description tool, product line description tool, product version description tool, product trait description tool, product commonality analysis tool, mapping tool to connect product version to application area, mapping tool to connect product trait responsive to application requirement, methodology tool to provide analysis framework and study management, feature-oriented domain analysis workflow, requirements verification workflow, product capabilities description tool;

ticket or issue tracking tool, time planning tool for strategy execution by product version, complimentary product family analysis, product roadmap generation tool, product planning lifecycle methodology, product planning lifecycle workflow tool, alternative scenario what-if tool, product line and version profitability analysis tool, and product version and release configuration management tool;

r. accepting product road map;

s. accepting votes stating changes to organization of tcepts by managing component;

t. accepting votes stating changes to organization of product strategy element by managing component;

u. accepting votes stating changes to development phasing of products;

v. accepting votes regarding modeling information of a type selected from a group consisting of;

development stage of product, completion status, value of market, size of market, investment availability, opportunity window, critical technology drivers as theories principles or laws of nature involved, 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;

w. accepting ideation;

x. accepting votes 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;

y. accepting refinement, by votes, of modeling information and relationships regarding product roadmaps;

z. accepting product production plans;

aa. accept product issue modeling information for internal and competitor development and marketing efforts;

bb. accept descriptive information about product and market issues and solution strategies;

cc. 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;

dd. performing modeling calculations to report product, company, and competitor posture against evaluation criteria for competitive strength and weakness determination;

ee. comparing product features across products, product lines, time frames, strategies, divisions, and competitive entities;

ff. 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;

gg. 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;

hh. calculating value changes and impact for what-if analysis of product candidates;

ii. providing data sets for analytic use and reporting regarding products;

jj. generating comparative reports based upon methodologies to assist product line managers, competitive analysts, management, and investors;

kk. generating surveys for obtaining specific information for analyzing product feature acceptance and user requirements;

ll. specifying a set of complementary products that provide a complete, workable solution to specific appcepts by matching features to requirements;

whereby said commonplace becomes a resource for companies offering products to assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, model product feature assignment, compare technologies, compare product features, determine fitness of product to application by feature, find descriptions for characteristics of a tcept or product based upon a tcept, and assess product potentials, better manage technology transfer by advertising technology, studying technology or industries for competitive intelligence, performing product line analysis, performing feature reuse analysis, performing use case modeling and change-case modeling, plan product changes;

anticipate and detect competitive product changes;

improve their results by better modeling, better knowledge organization, more particular feature comparisons and demand analysis;

whereby studies of markets and product areas may be more precise about futures analysis for specific product directions and better detect technology gaps;

whereby engineering companies searching for devices to solve problems may improve timeliness at lower cost;

whereby patent agents and patent searchers may much more easily obtain results far superior to current prior art searching facilities;

whereby people in distant areas searching for solutions to tough local technology problems may obtain a wealth of options rapidly and at low cost;

whereby intelligence areas concerned may determine levels of knowledge of others or concepts being stolen; and

whereby users in general will more quickly focus on specific product topics without burdensome organizing because others have developed useable categorizations, according to finding, searching, query and retrieval, goal based searching, selection set management, focus on information, and alter information through visualization process means.

202. The method of claim 36, to structure competitive intelligence use of concepts collected into a commonplace, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. preparing, by at least one processor, 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 process means;

f. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

g. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

h. estimating timings for states of product obsolescence in competitive areas;

i. providing modeling tools for competitive analysis what if value analysis;

j. providing information repository structures for managing and sharing competitive information on an access controlled basis;

k. processing zero or more environmental scanning process methodologies;

l. managing the collection of competitive data;

m. accepting and processing a command and effecting changes therefrom, said command selected from the group consisting 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;

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 functions;

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 applications software 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 that will pull-in a market lock, and clarifying feature change and need satisfaction scenarios to deploy potential product line core assets that can be mined and used competitively; and

whereby a crowd-sourced, fine-grained basis for market analysis, predictions of product demand and value and a disaggregated, quantitative basis for forecasting market demand and market share by feature to project sales and customer analysis based upon their products, technologies, and market positioning, customer technology needs based upon their requests or upon their product or production inefficiencies and weaknesses should provide more efficient advertising and selling of products, efficient locating and purchasing of products, a well categorized online product catalog system for analysis, and a well categorized online product catalog system for e-commerce sales; and

whereby companies offering products may assess competition, manage formation of product lines from product strategies, manage product feature sets, find technologies to solve product gaps, coordinate product development, and assess product potentials;

whereby dynamic crowd sourced competitive intelligence directed toward specific technical or application features is collected and made available;

203. The method of claim 36, further including:

a. providing an environmental scanning process and methodology or workflow for managing the collection of competitive data utilizing the categorization of the applications software map generation means and said commonplace data;

b. providing competitive analysis methodologies or workflows tuned to operate on said commonplace;

c. providing modeling tools for competitive analysis what if value analysis tuned to operate on said commonplace and said categorizations produced by said applications software map generation means; and

d. providing competitive product analysis information repository structures for managing and sharing competitive information on an access controlled basis;

whereby competitive analysis research tools provide structure and analytical results for methodology and workflow based environmental scanning, competitor profiling, methodology and workflow based surveying, data analysis and calculating competitive posture using data of said commonplace obtained from the crowd and categorized with the assistance of said crowd, but also with data maintained privately and linked to said commonplace categorizations, providing a blend of protected private, open source and for fee data all categorized uniformly.

204. The method for defining a matching economy marketplace of claim 145 for obtaining transactions fees on the basis of collecting new concepts into a commonplace, 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; and

h. providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas;

i. accepting a request to search for wisdom;

whereby innovation inefficiencies are reduced through information reuse, sharing of analysis, and crowdsourcing to collect the wisdom of crowds, financial gain may be obtained from operating said system, the service provider may collect, track, and mine the demographic characteristics of startups to allow reporting on entity progress, reliability, risk, and value.

292. The method of claim 36, for using associative search and interest shown to steer a user to a cntexxt closer to a recommendation the user is more likely to accept, comprising:

a. providing computer storage to contain said commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace;

c. providing application software utilize collective consensus through vote tallying means for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

d. providing application software map generation means for performing categorization and generating maps;

e. providing one or more computers hosting functions for users to interface with said commonplace;

f. providing application software local or distributed processes means for managing user interface functions and performing automated tasks resulting from user actions;

g. providing application software display and delivery means for controlling presentations of results to users and accepting navigation and other user commands to interface with said commonplace;

h. initiating execution of software for managing and delivering on said one or more computers with functions for managing and delivering said commonplace;

i. initiating execution of software for users to interface on said one or more computers hosting functions for users to interface with said commonplace;

j. initiating execution of communications between said computers with functions for managing and delivering said commonplace and said one or more computers hosting functions for users to interface with said commonplace;

k. establishing a commonplace into said computer storage;

l. providing an organization of knowledge regarding possible choices for action;

m. loading of said commonplace with structural information defining a knowledge model;

n. initiating execution of continuous processing functions according to continuous processing process means;

o. ingesting a plurality of source objects;

p. initiating continuous extraction of topical elements from said source object, said topical elements from features, characteristics, and descriptive information;

each said topical element to be used as a base for deriving commonalty and similarity scores for said source object, such that a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, such that 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;

q. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process 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, such that prior interest shown by user regarding any key concept is weighted much higher than the consensus for information regarding interest shown;

r. 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;

s. configuring workstation computers to communicate with server computers for transferring information and commands;

t. granting access to said commonplace;

u. initiating execution of the means for managing user interface functions and performing automated tasks resulting from user actions;

v. initiating execution of application software on one or more of said one or more computers to present a version of said results through a user interface to a user and to accept user commands;

w. initiating execution of the means for display and delivery such that a portion of said commonplace is displayed to said user;

x. accepting and processing a user command and effecting changes therefrom while also collecting interest information without a reliance on explicit interest statements by said user, said user command selected from the group consisting of;

i. to view content of said commonplace;

ii. to navigate around a visualization of said commonplace; and

iii. to request a search for wisdom;

whereby a co-location visualization based upon a structuring built previously containing concepts or items and augmented by interest shown by a user is used as a profile to indicate the type of concepts or items said user may also have an interest in as an improved, adaptive multi-criteria recommender system not reliant on keywords to describe concepts or items but offering contextually structured viewing for easy navigation and understanding of similarities between concepts or items;

whereby recommend concepts or items that are similar to those that a user showed interest in the past without the need to obtain user ratings or explicit statements of interest;

whereby sources of user interest differentiation other than recommender concepts or items are easily used to augment directly shown user interest;

whereby the approach surpasses collaborative, content-based, knowledge-based, and demographic techniques by incorporating collective wisdom beyond each such as information, if available, regarding topical searches by said user or said similar users on topics entirely outside of the recommender content area and in entirely different domains of wisdom, and by providing a multitude of organizations of knowledge wherein interest may be collected;

whereby the co-location visualization is an improvement on vector space representation for recommending;

whereby the use of user based weighting of specific item features to denote the importance of each feature to the user is surpassed while the use of additional techniques such as incorporation of explicit user interest statements, Bayesian decision trees, and cluster analysis analytics may easily augment the consensus information collected and interest shown to estimate the probability of user action;

whereby the use of consensus based upon multiple factors and conceptual descriptors yields a predictive accuracy substantially improved over any single technique and provides an ensemble model for recommendation.

293. The method of claim 292, to recommend to a viewing user on the basis of a similar user or user group having shown interest, further including:

a. determining user similarity by comparing patterns of interest shown by a viewing user and said similar user or user group;

b. weighting, during consensus determination, the interest of said similar user or users in said user group higher than all users other than said viewing user;

whereby the interest shown by others will likely cause a different structure for the co-location map viewed by a user, and cause a smaller sizing or a hiding of concepts of less interest to said viewing user if the interest shown by said viewing user or other similar users is lower than shown by the general set of users.

294. The method of claim 292, to hide information of low interest to user, further including:

a. applying information hiding in a co-location visualization to provide content-based filtering where content of lower interest is not shown;

whereby recommended concepts are removed by content-based filtering based on item concept as described and on interest shown in concepts of the subtree of a co-location based forest map of concepts.

295. The method for using associative search and interest shown of claim 292, to provide action workflows to user, further including:

a. providing task management and document management analytics for controlling workflows, and suggesting actions;

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;

e. initiating workflows according to said workflow templates;

whereby users may take action when reaching a decision regarding a concept.

307. The method for using associative search and interest shown of claim 293, to determine whether improvement of recommendation scoring is efficient based upon the measurement of quality of recommended choices against actual choices by codeword comparison, further including:

a. preserving a pre-viewing structure of a recommender scoring of an organization of knowledge;

b. accepting a plurality of uses of said recommender scoring of an organization of knowledge by a user viewing of said recommender scoring of an organization of knowledge;

c. comparing by codeword comparison said organization of knowledge as structured before said user viewing of said recommender scoring of an organization of knowledge to the structure after said user viewing by forming predictions and prediction correction mechanism process means;

d. determining the lack of quality of a positioning of cnxpts by the lack of quality of a positioning, taken over all cnxpts, all cnxpts at a level, or all cnxpts within a category, to determine an estimate of the amount of correct structure present in the post viewing actual but lost in the pre-viewing estimation codebook data set;

e. determining the lack of quality of a positioning of non-cnxpts such as people, location, or language by the lack of quality of a positioning, taken over all non-cnxpts, all non-cnxpts at a level, or all non-cnxpts within a category to determine an estimate of the amount of correct structure present in the post viewing actual but lost in the pre-viewing estimation codebook data set;

f. altering the basis of recommender scoring calculation by a change of a metric, said metric chosen from the list consisting of;

a coefficient applied in the calculation of a 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 alter the differential between said organization of knowledge as structured before said viewing to the structure after said viewing;

whereby quality improvement methods, post tree clustering, and metrics are applied to determine if the method used to form likelihood estimates of actions possible to be taken by a user against the cnxpt the actions are associated with in the organization of knowledge are sufficiently effective in determining the probability of action for a specific user or a set of users by codeword and error analysis techniques for statistical improvement in the metrics after the map is built by comparing what should be against what is.

325. The collecting user interest information of claim 146, further including:

a. collecting counts of unique and secondary views of ideas and categories of ideas 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;

such that predictions of future value are based in part on said statistics taken regarding interest shown;

such that data collected regarding what a user views during querying or navigation of said commonplace is made a business resource; and

so that tracking a user'"'"'s interest regarding areas of said commonplace categorization index cnxpts assists in addressing market needs;

whereby a user may obtain information describing the value of an idea or a category of ideas as indicated by said interest in said idea as shown by statistics on unique and secondary views of said idea or said category of ideas by said user; and

whereby revenue is based upon specific types of information from said commonplace to provide inexpensive access by narrowing the resource purchased.

326. The providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas of claim 146, further including:

a. providing a controlled communications information repository; and

b. providing tools for communicating regarding a cnxpt 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 cnxpt category with those of similar level of expertise;

whereby a user may confidently communicate with others regarding said cnxpt because of said controlled communications structure to share business plans within a protected mechanism for business plan submission and quiet review by validated investors, with access control to provide capturing of grantings of access, actual accesses, other disclosures, and the content of discussion between parties; and

whereby revenue is based upon specific types of information from said commonplace to provide inexpensive access by narrowing the resource purchased.

327. The providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas of claim 146, 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;

whereby said novel new idea may be protected rapidly to preserve the rights of the inventor and revenue is derived from granting access to said commonplace and said tools.

328. The providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas of claim 146, 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;

whereby business plans, consortium or company formation documents, founder profiles, consortium management information, negotiation documents, competitive company profiles, requirements of technology, application requirements, and consortium product line plans are maintained, and product lines and products are planned and managed using data of said commonplace obtained from the crowd and categorized with the assistance of said crowd, but also with data maintained privately and linked to said commonplace categorizations for rapid use by investment analysts, providing a blend of protected private, open source and for fee data all categorized uniformly so that all necessary information is made available at a reasonable cost to said owner so that said owner may obtain funding from crowdfunding portals or other funding sources without difficult data assembly and maintenance practices.

329. The providing tools for accessing, ideating, searching, organizing, protecting, commercializing, communicating, and extending ideas of claim 146, 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 where others may join to work on ideas in a protected environment on an access controlled basis;

whereby innovation systems are set up and operated, system functions augment manual efforts, creativity is assisted, a commonplace is established to accept additions and refinements of ideas, ideation is captured, ideas are categorized, and searching and retrieval of ideas, data mining, prediction, and forecasting from said commonplace is provided in a sharing and communing in innovation in a marketplace for ideas, information, jobs, technologies, services, and licenses.

333. The providing a marketplace for data related to specific concepts of claim 146, to export extracted data sets, further including:

a. presenting extracted data sets as subject matter for other application software according to local or distributed processes means;

whereby data may be packaged for use outside.

335. The providing a marketplace for data related to specific concepts of claim 146, to outsource the task of ideation, further including:

a. accepting a request for assistance;

b. informing a user of the request for assistance;

c. accepting an agreement to participate in creativity;

d. accepting a conjuring;

e. submitting the conjuring to the requestor;

f. accepting from the requestor a statement of fulfillment of the promise to deliver a conjuring;

g. processing a compensation package and delivering the compensation to the conjurer;

whereby requests for assistance are dynamically targeted to partners, affiliates, collaborators, and users for each type or phase of their involvement, e-commerce is effected, progress statuses are tracked, and use data is collected;

whereby the unrestrained model of granting access to all of the ideas coming in from crowd sourcing is altered so that an individual'"'"'s ideas are hidden until released, but the individual'"'"'s contributions still affect the collective intelligence in other important ways, including but not limited to classification of ideas. crowd source results speed deeper insight into what individuals need for innovation, and yet the structure present is more narrow then open innovation;

whereby creativity by crowd sourcing involves a form of crowdfunding, and a form of mass collaboration.

h. providing a learner the ability to connect the new information with relevant preexisting topics or propositions in the learner'"'"'s own cognitive structure provided by a map;

i. the assimilation of new topics represented by ttxs and propositions implemented as relationship info-items into existing cognitive structures held in a commonplace but readily accessible as an adjunct to the memory of a user but constantly refreshed by a collective learning process;

j. 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;

k. providing the mental excitement as would occur in game program to keep the speed of learning high;

l. 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;

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126. A computer-implemented method of producing a map from a commonplace of information demarcing what is known from that which is unknown at any point in time, comprising:

a. extracting a forest of cnxpts in a three dimension categorization of cnxpts where depth presents a time aspect where deepest depth is most into the future;

b. slicing the forest across to prepare a two-dimension flattened visualization where the cnxpts deeper than the slice are not shown;

whereby users obtain 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 a two-dimension map;

113. The method of claim 126, for machine learning of a new concept from a user conjuring with minimal description using a stigmergic commonplace, comprising:

a. providing computer storage to contain a commonplace;

b. providing one or more computers with functions for managing and delivering said commonplace for users to view, navigate and enter commands to interface with said commonplace;

c. establishing a commonplace and loading structural information defining a knowledge model for a domain of wisdom into computer storage;

d. initiating execution of software functions;

e. preparing, by at least one processor, 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 process means;

f. determining, by at least one processor, at least one user display visualization according to map generation process means for display to a user from said organization of knowledge of at least one domain of wisdom for initial viewing;

g. initiating execution of the means for display and delivery such that a portion of said organization of knowledge of at least one domain of wisdom is displayed to said user;

h. accepting a request to add or refine said commonplace and effecting change therefrom;

i. 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 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 such that 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;

j. 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 should have located the information in the empty space, the stating termed staking a claim to said space to encompass that wisdom;

k. and

l. 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;

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, and add to said commonplace new ideas, correcting and integrating it with previous knowledge with the assistance of others and whereby a minimum of entry by a user yields an addition of a new idea into said commonplace.

114. The method of claim 113 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 consisting 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 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 first concept represented by said cntexxt or no other said first concept represented by said cntexxt was valid for;

14. citing 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 first concept represented by said cntexxt and not precisely excluded from encompassing the present purlieu of said first concept represented by said cntexxt;

whereby the learning of a machine by failed searches is improved.

127. The method of claim 126, to produce a map from a commonplace of information demarcing what is completed of a process from what is not completed at any point in time, comprising:

a. extracting a structuring of cnxpts where a dimension presents a time aspect;

b. slicing the structuring by a timeline to prepare a two-dimension flattened visualization where the cnxpts incomplete at the time of the timeline fall to the future side of the timeline and are optionally not shown;

whereby users obtain 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 a two-dimension map showing completion;

128. The method of claim 126, to produce a map from a commonplace of information demarcing what outcomes are anticipated from what outcomes are no longer anticipated at any point in time, comprising:

a. 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;

b. slicing the structuring by a timeline to prepare a flattened aspect of a visualization 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;

whereby users obtain 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 a two-dimension map showing completion;

129. The method of claim 126, to produce a map from a commonplace of information demarcing the collective consensus of a crowd from what has not reached consensus to a predetermined level, comprising:

a. extracting a structuring of cnxpts by fxxt extraction based upon consensus voting where association choice is based upon consensus weighting;

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

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;

130. The computer-implemented method of claim 129 to produce a map from a commonplace of information demarcing the collective belief of a crowd, 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 remaining cnxpts where association choice is based upon consensus weighting;

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;

131. The method of claim 126, to produce a map from a commonplace of information demarcing the collective belief of a crowd regarding what outcomes are anticipated at any point in time, 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 visualization 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;

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

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;

132. The computer-implemented method of claim 131 to produce a map from a commonplace of information demarcing 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.

133. The computer-implemented method of claim 132 to produce a map from a commonplace of information demarcing the collective rationale of a crowd, further comprising:

a. extracting at least one cnxpt representing a state from which a decision determinative of an a priori event outcome, at least one cnxpt representing an a priori event, at least one cnxpt representing an a posteriori event outcome, and at least one association connecting said cnxpt representing a state from which a decision determinative of an a priori event outcome to said cnxpt representing said a priori event outcome, and at least one association connecting said cnxpt representing said a priori event outcome to said cnxpt representing said a posteriori event outcome indicative of the conditional likelihood of the a posteriori event, by fxxt extraction based upon consensus voting;

b. depicting at least one a priori event as a cnxpt in a tree such that said cnxpt is an event determinative of an outcome cnxpt and said cnxpt is structured to be more distant from the root of the tree than said outcome 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.

134. The computer-implemented method of claim 133 to produce a map from a commonplace of information demarcing 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 tree such that 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.

135. The computer-implemented method of claim 134 to produce a map from a commonplace of information demarcing the collective rationale of a crowd in a folded deep map, further comprising:

a. depicting said at least one a priori event as a cnxpt in a tree such that said cnxpt is a root in the tree and is shown on a flattened map depicting a directed graph of Bayesian network, wherein said cnxpt is at an edge of the flattened map 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 map;

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 in a manner where old decisions and outcomes are shown in an information hiding display.

136. The computer-implemented method of claim 131 to produce a map from a commonplace of information demarcing the collective rationale of a crowd in a task map, 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;

b. depicting at least one predecessor task as a cnxpt in a tree such that said cnxpt is determinative of the completion of a successor task and said predecessor task cnxpt is structured to be earlier in the time aspect of the map than said successor task 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 a task plan.

137. The computer-implemented method of claim 134 to disclose the basis of calculations used for at least one of structuring of a map, positioning of a map, modeling, or prediction from a commonplace of information regarding rationale, further comprising:

a. marking a fxxt by a type of rationale associated with its information source; and

b. calculating the proportion of a weighting in a summarization calculation by retaining information about the nature of the information of a fxxt and its proportional application to determine a summary weight of an info-item and a summary weight by rationale type;

whereby users obtain consensus based knowledge from beliefs, science, experts, causalities, or other forms of rationale basis and are informed regarding the mixture of rationales used in structuring or placing a cnxpt in a visualization, or in modeling.

337. The method of claim 126, for determining name and relationship of concepts by visual position, comprising:

a. enabling deep classification structures;

b. eliminating superficial descriptions of ttxs to ensure that experts are not held back

c. empowering novices to start at a general level of description and progress toward detail only to the degree they must based upon their task

d. empowering experts a clear path to the greater detail needed to discuss the future of a field

e. empowering investors to understand the timing of invention into the future;

f. empowering inventors to understand the details of prior art for their inventions even though their inventions will have prior art not yet disclosed or possibly not yet invented;

g. empowering competitive analysts to understand detailed information about very specific topics regarding technologies, products, product strategies, innovative individuals and groups;

h. empowering novices to understand whether an idea they have considered may have already been invented;

i. mitigating the differentials in understanding levels between experts and novices;

managing the authority issues related to dynamic classification based upon provenance;

k. managing the quality of dynamic, complex classification according to prediction correction mechanism;

l. empowering personal command and control over a dynamic, complex classification;

m. empowering personal command and control by a dashboard over a dynamic, complex classification;

n. empowering personal command and control over modeling within dynamic, complex classification management system;

o. empowering personal command and control over predictions generated by a dynamic, complex classification management system;

p. connecting display of point solution results to a user'"'"'s view of the commonplace to achieve consistent command and control;

q. harmonizing classifications;

r. empowering traceability of modeling performed by said computer-implemented method;

s. empowering traceability of decisions recommended by said computer-implemented method;

t. reducing redundancy in the presence of a plurality of manifestations of a topic identical in meaning to combine information related to each manifestation for said topic to a single manifestation;

u. providing authority control in the presence of a plurality of manifestations of a topic intended to be identical in meaning to achieve integration of topics by intended meaning without loss of the use of any different identity indicator for said topic;

v. providing authority control in the presence of a plurality of manifestations of a topic intended to be identical in meaning while said meaning is expressed in a second language to achieve integration of topics by intended meaning without loss of the use of any different identity indicator for said topic regardless of said identity indicator for said topic being in said second language;

w. providing authority control in the presence of a plurality of manifestations of a topic intended to be identical in meaning while said topic has an identity indicator in a second language to achieve integration of topics by intended meaning without loss of the use of any different identity indicator for said topic regardless of said identity indicator for said topic being in said second language;

x. providing authority control in the presence of a plurality of manifestations of a topic identical in meaning while said topic has an identity indicator found to contain a linguistic error to achieve integration of topics by meaning without loss of the use of any different identity indicator for said topic regardless of the need to correct said linguistic error by retaining said identity indicator found to contain a linguistic error as being corrected and retaining a corrected identity indicator;

y. providing authority control in the presence of a plurality of manifestations of a topic intended to be identical in meaning while said topic has an identity indicator found to be misleading to achieve integration of topics by intended meaning without loss of the use of any different identity indicator for said topic regardless of the need to correct said identity indicator found to be misleading by retaining said identity indicator found to be misleading as being corrected and retaining a corrected identity indicator;

z. providing authority control in the presence of a plurality of manifestations of a topic intended to be identical in meaning while said topic has an additional identity indicator stating an equivalent description for intended said meaning to achieve integration of topics by intended meaning without loss of the use of any different identity indicator identity indicator stating an equivalent description for said topic by retaining said identity indicator stating an equivalent description;

aa. generating a unique identity indicator for a ttx automatically when said ttx is entered into the commonplace;

bb. generating, if a predetermined system parameter has a predetermined value, a name for a ttx automatically;

cc. generating, if a predetermined system parameter has a predetermined value, a name for a ttx automatically when said ttx has no name and said ttx will be presented in a visualization;

dd. generating, if a predetermined system parameter has a predetermined value, a corrected name for a ttx automatically from a string entered when said string entered fails to comply with the syntax stated in a predetermined system parameter for names of ttx'"'"'s of the type of said ttx;

ee. generating, if a predetermined system parameter has a predetermined value, a corrected name for a ttx automatically from a string entered when said string entered duplicates a name of a second ttx for names of ttx'"'"'s of the type of said ttx;

ff. generating, if a predetermined system parameter has a predetermined value, a corrected name for a ttx automatically from a string entered when said string entered duplicates a name of any second ttx;

gg. providing the ability to edit an ontology visually;

hh. providing the ability to view a visualization utilizing information hiding;

ii. providing the ability to specify estimated result values for equations for use where said equations cannot be calculated for any reason but a result has been referenced;

jj. providing the ability to specify a default value for any characteristic or property of a ttx;

kk. providing the ability to specify a default value for any variable of any equation for use where said variable has no defined value and a defined value is required or said equation will result in an error condition;

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311. A computer-implemented method for managing legal research, comprising:

a. forming a commonplace of legal information comprising at least one legal principle;

b. defining at least one fxxt;

c. defining at least one structuring of knowledge;

d. generating at least one organization of knowledge structure based upon legal subject matter;

whereby the purpose and methodology of legal research is improved;

whereby dramatic improvements over existing legal research tools are achieved;

whereby specific improvements include increased speed, efficiency, and a greater conceptual view of the relationships between cases and the legal theories contained therein by the combined use of 3-d ontological mapping and crowd sourcing;

whereby applying a visual reference overlay that catalogs the various relationships shared by each individual conceptual point on the map to all of the other conceptual point on the map, a user will be able to quickly find that while no case on point exists in their particular jurisdiction for their specific issue or sub-issue or legal theory, there is such a case on point in another jurisdiction, either at the state or federal level, supporting their specific issue or sub-issue or legal theory as applied to their specific facts;

whereby visually depicting the ontology of the legal system as a whole, an attorney might be able to apply in a novel fashion the legal principles, concepts, and theories previously relegated to specialized fields, such as maritime law, for instance, to a tort entirely based on land. as the body of law has increased exponentially over the years with ever more lawyers, laws, rules, and litigation, specialization has become the norm. while specialization clearly has its advantages, an attorney specializing in toxic tort litigation, for example, is likely ignorant of key holdings and concepts as applied in transactional law involving securities. generally speaking, this really does not matter, as the two fields are significantly separate and distinct enough so that there is no overlap and no need for an attorney in one field to be cognizant of the legal doctrines embraced by the courts in another field. but because the practice of law is not necessarily always based on what the law is, but rather is sometimes focused on what the law should be, the attorney who can readily visualize and apply disparate legal concepts to the case at bar will be at an advantage;

whereby in the american model, the simplest layer of visualization would be based on the jurisdictional divisions within the court system itself. the simplest division divides the system into two, one section belonging to federal courts and another section belonging to that of the states;

whereby starting at the top of the federal level, a hierarchical view of the map would include all of the decisions of the U.S. Supreme Court in chronological order. under that node, the map would expand to include the all of the decisions from the U.S. Court of Appeals for each of the 11 regional circuits, the District of Columbia circuit, and the federal circuit. under those appellate court nodes, with the exception of the District of Columbia circuit and the federal circuit, decisions from each of the eleven regional circuit courts follow. beneath that node, decisions from each of the various u.s. district courts within each circuit follow;

whereby going deeper into the map, the cases may be divided into further classifications, such as civil or criminal. the civil section can be broken down into more sections, such as contract, tort, administrative, probate, domestic relations, intellectual property, and so on. each of those sections can be further divided into a smaller and more specialized body of the law. at the micro level of the tree, a user might be able to find the case on point for an extremely specific legal theory as applied to a narrow set of facts, e.g. non-mutual offensive collateral estoppel in a breach of contract case involving sophisticated real estate investors. or conversely, a user might be able to quickly determine that there is no case on point for their particular specific legal theory as applied to their facts in their particular jurisdiction.

190. The method of claim 311, for managing a stigmergic commonplace of legal information for research and legal discovery, comprising:

a. utilizing collective consensus through vote tallying for controlling continuous processing and managing add-in function modules to calculate consensus and impute associations;

b. performing categorization and generating maps;

c. providing a user interface for users to interface with said commonplace;

d. providing coordinated access to data extraction analytics for carrying out computer database searching, data extraction, transformation, translation, and loading;

e. providing coordinated access to document management analytics for controlling, storing, accessing, and displaying electronically stored information resource documents;

f. 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;

g. 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;

h. 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;

i. 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;

j. 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;

k. loading of said commonplace with structural information defining a knowledge model;

l. providing task management and document management analytics for controlling workflows, determining scheduling based upon workflow priorities, and suggesting task assignments;

m. initiating execution of continuous processing functions according to continuous processing process means;

n. ingesting a plurality of source objects;

o. 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 consisting 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;

p. 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 consisting 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, such that all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

q. 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 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;

r. initiating continuous extraction, for each source object that is unstructured data, of all descriptive elements of said source object selected from the group consisting 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, such that all instances of said source data description authority cnxpts are assigned a single fxxt related to said source object provenance authority fxxt;

s. 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;

t. initiating continuous extraction of topical elements from said source object, said topical element selected from the group consisting 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, such that a cnxpt is created for each unique element extracted, said cnxpt termed a coding key cnxpt, such that 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;

u. 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;

v. 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;

w. 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;

x. 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;

y. initiating execution of the means for categorizing said commonplace by performing map generation, such that 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 process 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;

z. 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;

aa. configuring workstation computers to communicate with server computers for transferring information and commands;

bb. granting access to said commonplace;

cc. initiating execution of the means for managing user interface functions and performing automated tasks resulting from user actions;

dd. initiating execution of application software on one or more of said one or more computers to present a version of said results through a user interface to a user and to accept user commands;

ee. initiating execution of the means for display and delivery such that a portion of said commonplace is displayed to said user;

ff. initiating requests for action, with attached description of action, to a user according to methodology workflow specification step;

gg. initiating alerts, with attached description, to a user according to an alert specification generation rule;

hh. initiating methodologies according to said methodology templates;

ii. initiating workflows according to said workflow templates;

providing search query procedure templates for searching for source objects to determine relevance;

kk. providing concept and source object information templates for searching for and reviewing source objects to determine relevance;

ll. providing methodology and workflow templates for project management of searching for and reviewing source objects to determine relevance to a stated meaning or issue;

mm. providing prediction analytics establishing commonalty and similarity scores for source objects;

nn. computing a predicted weighted ranking of a source object likely relevance to a coding key cnxpt as specified;

oo. computing a predicted weighted rejection ranking of a source objects according to rules for rejection as irrelevant or privileged;

pp. 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;

qq. accepting culling commands in manual review to categorize source objects according to said concepts and contexts as represented by cnxpts;

rr. 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

ss. accepting and processing a user command and effecting changes therefrom, said user command selected from the group consisting 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; and

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;

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;

whereby parties may negotiate toward even a complex formula to obtain and review documents that are being produced, because keyword searches on a list of keyword search terms is critical to initial definition of the agreed-upon scope of discoverable evidence;

the complex linguistic algorithms in predictive coding are replacing simple keyword lists but are also insufficient;

meta-data regarding documents such as originator and addressee, where it was found, when it was found, its origination date, subject coding, and timing in a chain may not contain keywords but are nevertheless crucial in discovery and yet all are insufficient to manage data extraction analytics carrying out computer search, scanning, transformation, translation, document control, data curation, and sampling techniques or the project management requirements for searching for, including into production or review, prioritization for and reviewing potentially responsive documents, or managing legal hold requirements, especially where business continues during the pendency of a matter;

whereby neither party has a goal of simply realizing higher production quantity but rather accurate recall of responsive documents in a priority for review for either concern or benefit;

whereby discovery in litigation is costly and often involves immense amounts of data such that viewing any low value document or data extract is especially burdensome, the limiting of search results to documents that may meet a fair but more narrow definition of pertinence even at the time when a document is catalogued into a company'"'"'s or defendant'"'"'s record-keeping and subjected to a responsible data retention policy greatly impacts cost; and

whereby the process is tunable, measurable, and repeatable so that starting with a small set of search parameters that generate too many documents with a low quality of pertinence can be improved by training and search query alterations to find more relevant documents while justifying burden and satisfying obligations in good faith.

312. The method of claim 311 for finding the case on point in legal research by weighted categorization, further comprising:

a. finding similarities between a first fact from a first case and a second fact from a second case such that 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;

b. finding similarities between a first element or sub-element of a first law and a second element or sub-element from a second law such that 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;

c. finding similarities between a first element or sub-element of a first law and a second fact from a second case such that 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;

d. finding similarities between 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 such that 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;

whereby the purpose and methodology of legal research is improved;

whereby dramatic improvements over existing legal research tools are achieved;

whereby specific improvements include increased speed, efficiency, and a greater conceptual view of the relationships between cases and the legal theories contained therein by the combined use of 3-d ontological mapping and crowd sourcing.

whereby the finding of the case on point legal opinion written on a previously decided case in the same jurisdiction in which the facts, circumstances, and the legal issues or sub-issues of the previously decided case most closely resemble and match those of the case currently being litigated becomes much easier because of the categorization as shown in the associative search co-location visualization, so that an attorney is able to more rapidly apply the law as provided by the “

case on point”

to his particular set of facts and make a legal argument or to improve a theory of the case, and finding authorities on point of related jurisdictions of the same sort is efficient;

whereby the work done by others in such a case or its relatives is reusable and readily applied.

313. The method of claim 311 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;

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 such that said one or more citations to opinions of said second jurisdiction describe the reasoning specifically regarding said first jurisdiction'"'"'s opinion;

314. The method of claim 311 characterization of a law by jurisdiction in legal research by weighted categorization, further comprising:

a. accepting a characterization of 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 such that 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;

b. accepting a characterization of a case as a cnxpt representing said case as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

c. accepting a characterization of a secondary source as an occurrence of a cnxpt representing the issue or sub-issue for which the source is relevant;

d. accepting a characterization of 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;

e. accepting a characterization of 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;

f. accepting a characterization of 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;

g. accepting a characterization of 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;

h. accepting a characterization of a party as a cnxpt representing said party, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

i. accepting a characterization of an involved other person as a cnxpt representing said other person, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

j. accepting a characterization of 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 consisting 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;

k. accepting a characterization of a case issue as a cnxpt representing said case issue as a cntexxt, said cnxpt having zero or more characteristics, properties, purlieu, and traits;

l. accepting a characterization of 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 consisting 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,

m. indices 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;

n. accepting a characterization of 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 consisting 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;

o. accepting a characterization of 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;

p. accepting a characterization of 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;

q. accepting a characterization of 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;

r. accepting a characterization of 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;

whereby the legal principle of stare decisis for legal authority and the doctrine of precedent is considered by a first user such that the information is available in said first user'"'"'s case theory development but is also available to the same or subsequent users for their needs when conducting legal research and the same points arise again in litigation; and

over time nearly all opinions that contain citations to other cases, secondary sources, statutes, and regulations will be categorized and linked by crowd sourcing;

whereby the relating of earlier written cases to newer cases where the earlier opinion was overruled or reversed or a statute held unconstitutional provides dynamic categorizing of legal principles that is appropriately in constant flux and is sufficiently timely to assist every user while for a first user on a first study of a principle additional work will be necessary that will help all subsequent users when completed so that with no more than occasional effort each user will quickly understand what a case'"'"'s value is in relation to their or other cases, and whether a case is “

good law”

or has been overruled or otherwise affected by another ruling;

this citator catalogs cases, secondary sources, theories of a researcher'"'"'s case, facts applied to elements or sub-elements of law, evidence available for proving facts, parties and involved others, case status, dockets, case issues, litigant objectives, attorney presentation outlines for a case, the status of statutes and regulations, indicating whether they have been amended or repealed all to help an attorney to prepare a position based upon any legal issue or sub-issue being researched.

315. The method of claim 311 searching by search terms in legal research by weighted categorization, further comprising:

a. accepting, if needed for organization, a selection of a predefined methodology for conducting legal research;

b. accepting, if using a methodology for legal research, textual answers to questions, mere examples of said questions selected from the group consisting of;

who are the parties, what are the relationship between parties, what are the places involved in the issue, what things are involved in the issue, what are the potential claims made, what are the potential defenses available, when did the incident occur, and what relief is being sought by the complainant.

c. accepting, to initiate a study regarding a legal issue, a set of basic information for legal research issue initiation stating common basic information regarding said legal issue selected from the group consisting of;

who, what, when, why, where, and how;

in the form of a description for a context represented by a cnxpt, said context useful for organizing information regarding said legal issue as a binding point for said study regarding a legal issue;

d. dissecting, or accepting a dissection of, said common basic information regarding said legal issue into a plurality of first parsed parts, and ingesting each said first parsed part into said commonplace as a binding point regarding the concept as stated by said first parsed part if not already present, each said binding point created as a first cnxpt termed a dissection cnxpt;

e. registering text of said common basic information regarding said legal issue first parsed parts into the commonalities of said commonplace as a comparator token with a reference connection to said binding point first cnxpt, said reference connection given a predetermined weight, and imputing relationship info-items from commonalities and any add-in analytics installed;

f. accepting zero or more commands causing the creation of relationship info-items with weights;

g. performing map generation for each said at least one organization of knowledge from the consensus of said commonplace as augmented by all info-items generated from said plurality of documents and all dissection cnxpts according to utilize collective consensus through vote tallying process means and map generation process means, each specific member of the set of said at least one organization of knowledge including said augmented info-items termed a comparison map;

h. determining a combined aggregated normalized relevance score between minus one and plus one for relevance of each new or previously added document in said commonplace for each basis cnxpt based upon the distance in said comparison map from the center of a dissection cnxpt to the center of said basis cnxpt, creating or updating a result set item in a result set attached to said basis cnxpt referencing said added document and having a relevance score equal to said combined aggregated normalized relevance score involving said added document and said basis cnxpt;

i. reordering said result set items of said result set attached to said second basis cnxpt according to said result set item relevance scores;

whereby the common methodology of legal research of generating search terms and then searching legal books or online is considerably simplified to merely using a statement of the case with, with additions as needed over time to build an entire case file on a custom basis or in any one of a series of methodologies;

the legal researcher will be immediately provided with an ample basis of other user'"'"'s work to productively browse through a co-location based map on any dimension of the research rather than a tedious following from a subject index to locate good case law;

whereby use of improving methodologies to provide a searching starting point by reusing notes, a simple description or select search terms to rapidly start legal research is greatly efficient in comparison to other methods;

whereby regardless of the researching attorney'"'"'s level of experience, specialization, and knowledge of the law, the search terms merely begin the organization of information for the attorney but rapidly tie the attorney'"'"'s information proactively into a great web of information provided as a by-product of the work of other attorneys, while protecting client information and attorney work-product confidentiality;

whereby the may vary from the very general and broad to those which are quite specific.

362. The method of claim 311, for evidence discovery and presentation management, 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;

d. categorizing elements of precedent, contract, legal opinion, other elements, or doctrine in one or more hierarchical organizations;

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;

h. accepting associative searching to track issue or sub-issue development;

whereby information requiring continually deeper detail and evolving, detailed categorization;

whereby law is naturally crowd and crowd source oriented;

whereby facts that must be supported by evidence can be obtained and analyzed by many participants according to their own theories and categorization schemes;

whereby a document and information management are made more efficient;

whereby involves the detailing of the specific evidence relevant to the fact to apply evidence to facts;

whereby sharing queries, paths, and results assist secondary users such as clerks and law students;

whereby adjusting queries, paths, and results assists a user to improve a presentation;

whereby the connection of facts to law by association gives refinement tools to an attorney and providing a review mechanism to supervisors, an assembly mechanism for legal teams, and a structuring tool for writing or analysis.

363. The method of claim 362, for case planning, comprising:

a. categorizing cnxpts by element or sub-element to sub-element structuring;

b. reapplying elements or sub-elements across precedent and theory with differentiations;

c. connecting facts to law by association;

whereby information requiring continually deeper detail and evolving, detailed categorization;

whereby law is naturally crowd and crowd source oriented;

whereby facts that must be supported by evidence can be obtained and analyzed by many participants according to their own theories and categorization schemes;

whereby a document and information management are made more efficient;

whereby involves the detailing of the specific evidence relevant to the fact to apply evidence to facts;

whereby sharing queries, paths, and results assist secondary users such as clerks and law students;

whereby adjusting queries, paths, and results assists a user to improve a presentation;

whereby the connection of facts to law by association gives refinement tools to an attorney and providing a review mechanism to supervisors, an assembly mechanism for legal teams, and a structuring tool for writing or analysis.

330. (canceled)

331. (canceled)

332. (canceled)

334. (canceled)

338. (canceled)

339. The method of claim 338, further comprising:

a. enabling participation around a categorization;

b. managing multi-source collaboration by consensus;

c. incentivizing creation of new or refining of knowledge;

343. (canceled)

344. (canceled)

345. (canceled)

346. (canceled)

347. (canceled)

348. (canceled)

349. (canceled)

350. (canceled)

351. (canceled)

352. (canceled)

353. (canceled)

354. (canceled)

355. (canceled)

356. (canceled)

357. (canceled)

358. (canceled)

359. (canceled)

360. (canceled)

361. (canceled)