Mapping architecture for arbitrary data models

• US 20050050068A1
• Filed: 08/29/2003
• Published: 03/03/2005
• Est. Priority Date: 08/29/2003
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Laskos, Alex, Wiener, Adam J., Ari, Bertan, Vaschillo, Alexander, Aharoni, Avner Y., Bolognese, Luca, Conrad, Andrew J., Suver, Chris, Burugapalli, Srinivasa R., Zhu, Jason Z., White, Steven D., Schach, David, Cengiz, Ilker, Pfleiger, Todd F.
• Granted Patent: US 7,739,223 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 16/84 Mapping; Conversion
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

A data mapping architecture for mapping between two or more data sources without modifying the metadata or structure of the data sources themselves. Data mapping also supports updates. The architecture also supports at least the case where data sources that are being mapped, are given, their schemas predefined, and cannot be changed. The architecture includes a mapping component that receives respective metadata from at least two arbitrary data models, and maps expressions between the data models.

Claims

1. A system that facilitates mapping arbitrary data models, comprising a mapping component that receives respective metadata from at least two arbitrary data models, and maps expressions between the data models.

2. The system of claim 1, the data models are query languages.

3. The system of claim 1, the data models are data access languages.

4. The system of claim 1, the data models are data manipulation languages.

5. The system of claim 1, the data models are data definition languages.

6. The system of claim 1, the data models include at least an object model and at least one relational model where the object model is mapped to at least one of the relational models.

7. The system of claim 1, the data models include object models where one of the object models is mapped to at least one of the other object models.

8. The system of claim 1, the data models include an XML model and at least one relational model where the XML model is mapped to at least one of the relational models.

9. The system of claim 1, the data models are XML models where one of the XML models is mapped to at least one of the other XML models.

10. The system of claim 1, the data models include an XML model and at least one object model where the XML model is mapped to at least one of the object models.

11. The system of claim 1, the data models are relational models where one relational model is mapped to at least one of the other relational models.

12. The system of claim 1, the data models include an XML model and an object model where the object model is mapped to at least one of the XML models.

13. The system of claim 1, the data models are of the same structure.

14. The system of claim 1, the mapping component receives topology data that is derived from the metadata.

15. The system of claim 1, the data models are read-only.

16. The system of claim 1, the data models are mapped without modifying the metadata or structure of the data models themselves.

17. The system of claim 1, the expressions comprise at least one of a structure, field, and relationship.

18. The system of claim 17, the expressions mapped between the data models are at least one of the same, different, and a combination of the same and different.

19. The system of claim 1, the mapping component creates structural transformations on the data of a data model by at least one of creating or collapsing hierarchies, moving attributes from one element to another, and introducing new relationships.

20. The system of claim 1, the mapping component relates and connects the same mappable concepts between the data models.

21. The system of claim 1, the mapping between the data models is directional.

22. The system of claim 1, the data models include a source domain and a target domain, such that a structure and field of the target domain can be mapped at least once.

23. The system of claim 1, the data models include a source domain and a target domain, such that a structure and field of the source domain can be mapped multiple times.

24. The system of claim 1, the data models include a source domain and a target domain such that the mapping component allows a user to operate on the data models through a query language of the target domain.

25. The system of claim 1, the data models include a source domain and a target domain such that the source domain is the persistent location of the data.

26. The system of claim 1, the data models include a source domain and a target domain such that mapping translates a query written in a query language of the target domain into a query language of the source domain.

27. The system of claim 1, the mapping component facilitates automatically synchronizing updates made in a target data model to a source data model.

28. The system of claim 1, the mapping component includes a mapping file that maps like concepts of the respective metadata.

29. A computer executing the system of claim 1.

30. A system that facilitates mapping arbitrary data models, comprising:

source metadata that represents source concepts of a source data source;

target metadata that represents target concepts of at least one target data source; and

a mapping component that receives the source metadata and the target metadata and maps the concepts from the source data source to the target metadata associated with one or more of the target data sources.

31. The system of claim 30, the mapped concepts are at least one of the same, different, and a combination of the same and different.

32. The system of claim 30, the data sources are of the same structure.

33. The system of claim 30, the source concepts and the target concepts are the same in both of the data sources.

34. The system of claim 30, the mapping component relates and maps the same concepts between the data sources.

35. The system of claim 30, the source and target concepts include a relationship element that is a link and association between two structures in the same data source.

36. The system of claim 35, the relationship element defines how a first structure relates to a second structure in the same data source.

37. The system of claim 30, the source data source and the target data source are disposed on a network remote from the mapping component.

38. The system of claim 30, the mapping component is local to at least one of the source data source and the target data source.

39. A method of mapping data between data models, comprising:

receiving respective metadata from at least two arbitrary data models; and

mapping expressions between at least two of the data models based upon the metadata.

40. The method of claim 39, the expressions mapped between the two data models are the same expressions.

41. The method of claim 39, further comprising defining a source data schema and a target data schema and information missing in the schemas.

42. The method of claim 39, further comprising transforming data during a mapping of a source data model to a target data model using a function.

43. The method of claim 39, further comprising synchronizing changes made in a target data model with a source data model.

44. A method for mapping arbitrary data models, comprising:

receiving source metadata that represents source concepts of a source data source and target metadata that represents target concepts of a target data source; and

mapping the concepts between the source and target data sources based upon the source metadata and the target metadata.

45. The method of claim 44, the data sources are of the same structure.

46. The method of claim 44, further comprising,

creating a variable in a source domain;

restricting the variable with conditions; and

mapping the variable to the target concept.

47. The method of claim 46, the variable is created at least one of implicitly and explicitly.

48. The method of claim 46, the variable represents an empty result set.

49. The method of claim 44, the mapping is stackable between the source and target data via one or more intermediate mapping stages.

50. The method of claim 44, further comprising selecting an optimal path for mapping between the source and the target.

51. The method of claim 50, the optimal path is selected with a central control entity based on at least one of available bandwidth and interruptions in the path.

52. The method of claim 44, further comprising accessing a mapping algorithm in response to selecting an optimal path between a plurality of the data sources and plurality of the data targets.

53. The method of claim 52, the mapping algorithm is associated with a structure of the source data and the target data.

54. A system that facilitates mapping data between arbitrary data models, comprising:

means for receiving source metadata that represents source concepts of a source data source and target metadata that represents target concepts of a target data source; and

means for mapping the concepts between the source and target data sources based upon the source metadata and the target metadata.

55. The system of claim 54, the means for mapping includes a mapping means that relates and maps the same concepts between the data sources.