Spatial intelligence system and method

• US 20030115211A1
• Filed: 12/14/2001
• Published: 06/19/2003
• Est. Priority Date: 12/14/2001
• Status: Abandoned Application

• Current Assignee: Hon Hai Precision Industry Co., Ltd.
• Original Assignee: Metaedge
• Inventors: Luu, Victor, Chen, Li-Wen
• Application Number:
  US10/017,701
• Publication Number:
  US 20030115211A1
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/29 Geographical information databases

Abstract

The present invention provides techniques for analyzing and managing information having a spatial component. Techniques such as virtual schemas can be used to create meta models for analyzing spatial information, in conjunction with information about other centric entities, including business entities, technical entities, and governmental entities. Specific embodiments provide systems, methods, computer programs and apparatus for populating databases in accordance with the defined meta models and analyzing information having spatial components in a variety of business, technical and governmental applications.

Claims

1. A method, comprising:

receiving a first schema database;

forming a virtual schema including at least a portion of a dataset included within the first database;

receiving a first input indicating a criteria;

aggregating data of the database into one or more groupings in accordance with the virtual schema and the first input indicating the criteria; and

displaying one or more indicators associated with the one or more groupings on an n-dimensional presentation.

2. The method of claim 1, further comprising:

receiving a second input indicating one or more regions;

storing the second input as a spatial-object meta data; and

aggregating the groupings based upon the spatial-object meta data.

3. The method of claim 2, further comprising:

displaying one or more indicators associated with the one or more groupings in a region associated therewith on an n-dimensional presentation.

4. The method of claim 2, wherein

the region comprises at least one of:

a polygon,

a circle,

a rectangle,

an ellipse, and

an animal home range.

5. The method of claim 2, wherein:

the second input indicating one or more regions comprises;

at least one of;

an input from a user,

a pre-determined area,

a derivation based upon one or more objects on the n-dimensional presentation, and

a result of a computation.

6. The method of claim 5, wherein:

the pre-determined area comprises at least one of;

a zip code,

an area code,

a census tract,

a Metropolitan Statistical Area (MSA),

a nation state,

a state,

a county,

a municipality,

a latitude, and

a longitude.

7. The method of claim 5, wherein:

the derivation based upon one or more objects on the n-dimensional presentation comprises;

a region within a specified distance of a power line.

8. The method of claim 5, wherein:

the result of a computation comprises;

computing an animal home range, the home range providing a region defined by activities of a target;

defining within the region a first ellipse; and

defining within the region a second ellipse approximately orthogonal to the first ellipse;

wherein

an area defined by intersection of the first ellipse and the second ellipse provides a greatest probability of finding the target.

9. The method of claim 8, wherein:

the target comprises at least one of;

a suspect, who perpetrated criminal acts defined by the data,

a customer, who completed transactions in shops defined by the data,

a source of biological material, which caused infections in persons defined by the data.

10. The method of claim 2, wherein:

aggregating the groupings based upon the spatial-object meta data comprises;

checking whether data points fall within a common region, and

if so, aggregating data represented by the data points.

11. The method of claim 3, wherein:

the n-dimensional presentation comprises a map.

12. The method of claim 11, wherein:

displaying one or more indicators further comprises;

determining an x, y coordinate for each region on the map;

displaying at least one indicator associated with the one or more groupings on the map at the x, y coordinate.

13. The method of claim 2, further comprising:

receiving a third input indicating a one or more redefined regions;

storing the third input as a redefined spatial-object meta data; and

aggregating into new groupings based upon the spatial-object meta data.

14. The method of claim 2, further comprising:

redefining the virtual schema based upon the spatial-object meta data.

15. The method of claim 14, wherein:

redefining the virtual schema based upon the spatial-object meta data comprises;

receiving a third input indicating a criteria;

aggregating data of the database into one or more new groupings in accordance with the redefined virtual schema and the third input indicating the criteria; and

displaying one or more indicators associated with the one or more new groupings on an n-dimensional presentation.

16. The method of claim 2, further comprising:

receiving a third input indicating a relationship between a first data point and a second data point on the n-dimensional presentation;

reflecting the relationship in the virtual schema;

aggregating data of the database into one or more new groupings in accordance with the virtual schema; and

displaying one or more indicators associated with the one or more new groupings on an n-dimensional presentation.

17. The method of claim 1, further comprising:

receiving a second database;

forming a virtual schema including at least a portion of a dataset included within at least one of the first database and the second database;

receiving a first input indicating a criteria;

aggregating data of at least one of the first database and the second database into one or more groupings in accordance with the virtual schema and the first input indicating the criteria; and

displaying one or more indicators associated with the one or more groupings on an n-dimensional presentation.

18. The method of claim 1, further comprising:

generating code in accordance with the virtual schema.

19. The method of claim 1, further comprising:

providing customer centric information to a core of customer data within the database in accordance with the virtual schema.

26. A customer data analysis report produced according to the method of claim 1.

20. A method, comprising:

receiving a first schema database;

forming a virtual schema including at least a portion of a dataset included within the first database;

receiving a first input indicating a criteria;

receiving a second input indicating one or more regions;

aggregating data of the database into one or more groupings in accordance with the virtual schema, the first input indicating the criteria, and the second input indicating the one or more regions of interest; and

displaying one or more indicators associated with the one or more groupings on an n-dimensional presentation.

21. A system, comprising:

a schema builder that generates one or more virtual schemas including at least a portion of data input from a source, and generates mapping rules controlling data movement into a data warehouse;

a metadata repository operative to hold the virtual schemas and mapping rules;

a data warehouse builder;

a spatial-object data repository;

a region checker; and

an n-dimensional presentation;

wherein the data warehouse is defined by at least a portion of the data input, the virtual schemas, the mapping rules, and the analysis functions.

22. The system of claim 21 wherein:

the source comprises at least one of a plurality of on line transaction processing (OLTP) databases.

23. An apparatus, comprising:

means for generating one or more virtual schemas including at least a portion of data input from a source;

means for generating mapping rules controlling data movement into a data warehouse;

means for holding the virtual schemas and mapping rules;

means for generating one or more analysis functions based upon the virtual schemas and data input.

24. A computer program product, comprising:

code for providing a user interface;

code for generating customer data analysis function code;

code for scheduling tasks for managing a data warehouse;

code for pre-processing data for movement into the data warehouse;

code for managing creation of the data warehouse;

code for defining customer data analysis functions;

code for performing data source analysis;

code for planning operations of a customer data analysis environment; and

a computer readable storage medium for holding the codes.

25. A computer program product, comprising:

code for accessing meta data from a repository;

code for translating entities from a meta model into a data schema to form a database;

code for providing customer activity correlation queries with access to a database of a data warehouse;

code for providing customer data analysis functions;

code for providing analysis results to at least one of a plurality of business applications; and

a computer readable storage medium for holding the codes.

27. A method, comprising:

providing a focal group, comprising;

at least one of a plurality of core components; and

at least one of a plurality of classification components providing classifications for information relating to the core components; and

providing at least one customized group, comprising;

at least one of a plurality of customer activity components related to the core component; and

at least one of a plurality of activity lookup components related to at least one of the customer activity components;

wherein the focal group and the customized group comprise a reverse star schema meta model.

28. A computer readable storage medium containing information organized according to the method of claim 27.