Data source interation system and method

• US 20040034651A1
• Filed: 05/12/2003
• Published: 02/19/2004
• Est. Priority Date: 09/08/2000
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Martone, Maryann E, Ludaescher, Bertram, Gupta, Amarnath
• Granted Patent: US 7,533,107 B2
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 16/8358 Query translation
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A method and program product for integrating different data sources has steps of obtaining semantic information from each of the different data sources (200, 202, 210), creating a conceptual model of (218, 220, 22) the data source using the semantic information, and accessing one or more secondary knowledge sources. The secondary information sources contain information regarding the relations of data from different of the databases, so that an integrated semantic model of all of the databases (200, 202, 210) may be created. Queries can then be processed using the integrated semantic model.

Claims

1. A method for integrating a plurality of data sources comprising the steps of:

obtaining semantic information from each of the plurality of data sources;

creating a conceptual model for each of the plurality of data sources using said semantic information;

accessing a secondary knowledge source having information that relates the different data sources;

creating an integrated semantic model of the plurality of data sources using said conceptual models and said secondary knowledge source.

2. A method as in claim 1 wherein each of said conceptual models is in a uniform language.

3. A method as in claim 1 wherein each of the plurality of data sources has a semantic formalism, and wherein the method further comprises providing a plug-in for converting at least one of the plurality of data source'"'"'s semantic formalism to said uniform language of said generic conceptual model.

4. A method as in claim 1 wherein said semantic information obtained from at least one of the plurality of data sources is expressed in one of either a unified modeling language, resource description framework, or an extended entity relationship language.

5. A method as in claim 1 wherein the step of creating a conceptual model for each of the plurality of databases further comprises converting each of said conceptual models into a generic conceptual model, each of said generic conceptual models being in a uniform language.

6. A method as in claim 5 wherein said uniform language represents logic statements.

7. A method as in claim 5 wherein the step of creating said integrated semantic model comprises using said generic conceptual models.

8. A method as in claim 1 wherein each of said conceptual models created from each of the plurality of data sources comprise logic statements, and wherein said integrated semantic model comprises logic statements.

9. A method as in claim 1 wherein said secondary knowledge source comprises logic statements in a frame logic language.

10. A method as in claim 1 wherein said integrated semantic model comprises logic statements, and wherein at least one of said logic statements comprises an instance declaration, at least one of said logic statements comprises a subclass declaration, and at least one of said logic statements comprises a method declaration.

11. A method as in claim 1 wherein said secondary knowledge source comprises a plurality of secondary knowledge sources.

12. A method as in claim 1 wherein each of the conceptual models from each of the plurality of data sources have at least a class, said semantic information comprises as least a class schema, and wherein said integrated semantic model comprises logic statements that define one of at least an instance, subclass, or method relation between at least a first class from one of the plurality of data sources and a second class from a second of the plurality of data sources.

13. A method as in claim 1 wherein each of said conceptual models has at least a class, said semantic information comprises a class schema, and wherein said integrated semantic model comprises logic statements that define an instance, subclass, and a method relation between one or more classes from a first of the plurality of data sources and one or more classes from others of the plurality of data sources.

14. A method as in claim 1 wherein each of said conceptual models has at least a class, and wherein said integrated semantic model comprises at least a logic statement that defines one of an “

is a”

, a “

has a”

, or a “

part of”

relation between at least a first class from one of the plurality of data sources and one or more classes from others of the plurality of data sources.

15. A method as in claim 1 wherein said secondary knowledge source comprises expert knowledge.

16. A method as in claim 1 wherein each of the plurality of data sources define at least a class, and wherein said secondary knowledge source has information comprising rules that relate at least some of the classes from different of the plurality of data sources to one another.

17. A method as in claim 16 wherein said rules relate at least a first class from one of the plurality of data sources to one or more second classes from others of the plurality of data sources in a logical instance, subclass, or method relation.

18. A method as in claim 1 wherein said secondary knowledge source information is not available from any of the plurality of data sources.

19. A method as in claim 1 wherein said method further comprises converting data from each of the plurality of data sources into a uniform language.

20. A method as in claim 19 wherein said uniform language comprises extensible markup language.

21. A method as in claim 1 wherein the method further comprises processing a user-input query against said integrated semantic model to identify data from one or more of the plurality of data sources responsive to said query.

22. A method as in claim 21 wherein each of the plurality of data sources comprises at least a data class, and wherein in responding to said query the method further comprises the steps of:

logically relating one or more classes from different of the plurality of databases to one another; and

presenting said data responsive to the query in context by displaying said logic relations made between said related classes.

23. A method for integrating a plurality of individual data sources to process a query comprising the steps of:

converting data from each of the plurality of data sources to a uniform language;

obtaining semantic information from each of the plurality of data sources, said semantic information comprising at least a class schema;

creating a generic conceptual model in a uniform language for each of the plurality of data sources using said semantic information, said uniform language comprising logic statements;

accessing at least one secondary knowledge source comprising rules relating data classes from different of the data sources to one another;

creating an integrated semantic model using said conceptual models and said secondary knowledge source, said integrated semantic model comprising logic statements expressing at least one of an instance, subclass, or method relation between a first class from one of the plurality of data sources and one or more second classes from another of the plurality of databases;

converting the query to a language consistent with said integrated semantic model; and

using said integrated semantic model to identify data from one or more of the plurality of data sources responsive to the query.

24. A method as in claim 23 wherein each of the plurality of data sources has a semantic formalism, and wherein said data responsive to the query comprises data retrieved from at least two of the plurality of databases, and wherein the method further comprises the steps of:

providing a plug-in for converting between at least one of the plurality of data source formalisms and said generic conceptual model uniform language; and

displaying said data responsive to said query in context by displaying logical relations between classes from different of the plurality of data sources made to determine said responsive data.

25. A computer program for integrating a plurality of different data sources, the computer program comprising computer executable instructions stored in a computer readable medium that when executed cause the computer to:

obtain semantic information from each of the plurality of data sources;

create a conceptual model for each of the plurality of data sources using said semantic information;

access a secondary knowledge source having information relating the data sources to one another; and

create an integrated semantic model using said conceptual models and said secondary knowledge source.

26. A computer program as in claim 25 wherein each of said conceptual models comprises a generic conceptual model in a uniform language.

27. A computer program as in claim 26 wherein each of said generic conceptual models comprise logic statements, and wherein said integrated semantic model comprises logic statements.

28. A computer program product as in claim 26 wherein the computer program instructions when executed further cause the computer to provide a plug-in for converting between one of the plurality of data source'"'"'s semantic formalism and said uniform language of said generic conceptual model.

29. A computer program as in claim 25 wherein said semantic information obtained from at least one of the plurality of data sources is expressed in one of either a unified modeling language, resource description framework, or an extended entity relationship language.

30. A computer program as in claim 25 wherein said semantic information comprises class schema and relationship schema.

31. A computer program as in claim 25 wherein each of the plurality of databases has at least a class, and wherein said integrated semantic model comprises logic statements relating at least some of said classes from different of the data sources to one another.

32. A computer program as in claim 31 wherein said logic statements comprise Frame logic.

33. A computer program as in claim 25 wherein said integrated semantic model comprises logic statements relating classes of data from different of the plurality of databases to one another, and wherein at least one of said logic statements comprises an instance declaration, at least one of said logic statements comprises a subclass declaration, and at least one of said logic statements comprises a method declaration.

34. A computer program as in claim 25 wherein each of the plurality of data sources has at least a class, and wherein said integrated semantic model comprises logic statements that express an instance, a subclass, and a method relation between at least one class from a first of the plurality of databases and one or more classes from others of the plurality of databases.

35. A computer program as in claim 25 wherein each of said conceptual models comprises a class hierarchy having at least a class and a subclass.

36. A computer program as in claim 25 wherein said secondary knowledge source comprises expert knowledge.

37. A computer program as in claim 25 wherein said secondary knowledge source comprises a digital data file.

38. A computer program as in claim 25 wherein said secondary knowledge source comprises a plurality of secondary knowledge sources.

39. A computer program as in claim 25 wherein each of the plurality of data sources define at least a class, and wherein said secondary knowledge source has information relating at least some of the classes from different of the plurality of data sources to one another.

40. A computer program as in claim 25 wherein said secondary knowledge source information relates at least a first class from one of the plurality of data sources in one of an instance, sub-class, or method relation to a second class from another of the plurality of databases.

41. A method as in claim 25 wherein said secondary knowledge source information is not available from any of the plurality of databases.

42. A computer program product as in claim 25 wherein the program instructions when executed cause the computer to convert data from each of the plurality of data sources into a uniform language.

43. A computer program product as in claim 42 wherein said uniform data language comprises a semistructured language.

44. A computer program product as in claim 43 wherein said uniform language comprises extensible markup language.

45. A computer program product as in claim 25 wherein the computer program instructions when executed cause the computer to process a user-input query and to use said integrated semantic model to identify data from one or more of the plurality of data sources responsive to said query.

46. A computer program product as in claim 45 wherein the computer program instructions further cause the computer to display said data responsive to said query in context by displaying logic relations made between classes from different of the plurality of data sources to identify said responsive data.

47. A computer program product for querying a plurality of individual heterogeneous data sources, the computer program product comprising computer readable instructions embedded in a computer readable medium that when executed cause the computer to:

obtain data from each of the plurality of data sources in a uniform, semi-structural language;

obtain semantic information from each of the plurality of data sources, said semantic information comprising at least a class schema;

convey said semantic information to a mediator;

create a generic conceptual model in a uniform language with said mediator for each of the plurality of data sources using said semantic information;

create a domain map with said mediator using at least one secondary knowledge source, said domain map comprising logic statements that at least relate a class for a first of the plurality of data sources to a class from another of the plurality of data sources in one of a instance, class, or method relation; and

process a query with said mediator by converting said query to a language consistent with said domain map, using said domain map to identify classes from one or more of the plurality of data sources responsive to said query, retrieve said responsive data, and display said responsive data.

48. A computer program product as in claim 47 wherein each of the plurality of data sources has a semantic information language, and wherein the product further causes the computer to:

provide a plug-in for converting between at least one of the data source semantic information languages and said generic conceptual model uniform language; and

display said responsive data in context by displaying logic relations made between said classes to identify said responsive data.