Methods for data warehousing based on heterogenous databases

• US 20040064456A1
• Filed: 09/27/2002
• Published: 04/01/2004
• Est. Priority Date: 09/27/2002
• Status: Abandoned Application

• Current Assignee: Joseph Shi Piu Fong, Qing Li
• Original Assignee: Joseph Shi Piu Fong, Qing Li
• Inventors: Li, Qing, Fong, Joseph Shi Piu
• Application Number:
  US10/259,208
• Publication Number:
  US 20040064456A1
• Time in Patent Office: Days
• US Class Current: 707/100
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP

Abstract

According to the present invention there is provided a method for establishing a data warehouse capable from a plurality of source databases including at least one relational database and at least one object-oriented database, comprising the steps of: integrating the schema of said plurality of source databases into a global schema, including resolving semantic conflicts between said source databases, and establishing a frame metadata model for describing data stored in said local databases, said frame metadata model including means for describing any constraints developed during schema integration and further including means for describing relationships between data stored in local object-oriented databases.

Claims

1. A method for establishing a data warehouse from a plurality of source databases including at least one relational database and at least one object-oriented database, comprising the steps of:

a. integrating the schema of said plurality of source databases into a global schema, including resolving semantic conflicts between said source databases, and

b. establishing a frame metadata model for describing data stored in said local databases, said frame metadata model including means for describing any constraints developed during schema integration and further including means for describing relationships between data stored in local object-oriented databases.

2. A method as claimed in claim 1 wherein data is abstracted from said local databases into a star schema to create a data cube for data analysis.

3. A method as claimed in claim 2 wherein said data cube may be either a relational or an object-oriented data cube.

4. A method as claimed in claim 2 wherein said data cube may be queried by online analytical processing techniques.

5. A method as claimed in claim 1 wherein said step of local schema integration is carried out by integrating database schemas in pairs.

6. A method as claimed in claim 5 wherein said step of local schema integration includes (a) resolving semantic conflicts between a said pair of database schemas, and (b) merging classes and relationships.

7. A method as claimed in claim 6 wherein semantic conflicts are resolved by user supervision.

8. A method as claimed in claim 6 wherein semantic conflicts are transformed into data relationships.

9. A method as claimed in claim 6 wherein data relationships are merged by capturing the cardinality of said relationships.

10. A method as claimed in claim 6 wherein classes are merged by subtype relationship.

11. A method as claimed in claim 6 wherein classes are merged by generalization.

12. A method as claimed in claim 6 wherein classes are merged by aggregation.

13. A method as claimed in claim 1 wherein said frame metadata model comprises a header class, attribute class, method class and constraint class.

14. A method as claimed in claim 13 wherein said header class comprises basic information representing said class identity.

15. A method as claimed in claim 13 wherein said attribute class represents the properties of a class.

16. A method as claimed in claim 13 wherein the method class represents the behaviour, active rules and/or deductive rules of a data object.

17. A method as claimed in claim 13 wherein the constraint class represents any constraints on a data object.

18. An architecture for a data warehouse comprising:

a plurality of local databases including at least one relational database and at least one object-oriented database, a global schema formed from integrating the schema of said local databases, a frame metadata model for describing data in said local databases and for describing relationships between data in said at least one object oriented database and for describing any constraints derived during schema integration, a star schema for abstracting data from said local databases into a data cube for analysis, and means for querying said data cube.

19. An architecture for a data warehouse as claimed in claim 18 wherein means are provided for abstracting data from said local databases into either a relational data cube or an object-oriented data cube for enabling relational or object oriented views of said abstracted data dependent on a user'"'"'s request.

20. An architecture for a data warehouse as claimed in claim 18 wherein said querying means comprises means for performing online analytical processing of said data cube.

21. An architecture for a data warehouse as claimed in claim 18 wherein said frame metadata model comprises a header class, attribute class, method class and constraint class.

22. An architecture for a data warehouse as claimed in claim 21 wherein said header class comprises basic information representing said class identity.

23. An architecture for a data warehouse as claimed in claim 21 wherein said attribute class represents the properties of a class.

24. An architecture for a data warehouse as claimed in claim 21 wherein said method class represents the behaviour, active rules and/or deductive rules of a data object.

25. An architecture for a data warehouse as claimed in claim 21 wherein said constraint class represents any constraints on a data object.

26. A data warehouse comprising a plurality of local databases including at least one relational database and at least one object-oriented database, comprising:

means for abstracting data from said local databases for analysis and means for querying said abstracted data, wherein said means for abstracting data is able to present said abstracted data for analysis in either relational or object-oriented views at the request of a user.

27. A method for integrating the schema of a plurality of local databases wherein said local database schemas are integrated in pairs, the integration of a pair of local database schemas including the resolving of semantic conflicts and merging of classes and relationships, and wherein a frame metadata model is established for describing the contents of said integrated local databases including any constraints established during said schema integration.

28. A method as claimed in claim 27 wherein semantic conflicts are resolved by user supervision.

29. A method as claimed in claim 27 wherein semantic conflicts are transformed into data relationships.

30. A method as claimed in claim 27 wherein data relationships are merged by capturing the cardinality of said relationships.

31. A method as claimed in claim 27 wherein classes are merged by subtype relationship.

32. A method as claimed in claim 27 wherein classes are merged by generalization.

33. A method as claimed in claim 27 wherein classes are merged by aggregation.