Skip to main content

Composing Mappings Between Schemas Using a Reference Ontology

  • Conference paper
On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE (OTM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3290))

Abstract

Large-scale database integration requires a significant cost in developing a global schema and finding mappings between the global and local schemas. Developing the global schema requires matching and merging the concepts in the data sources and is a bottleneck in the process. In this paper we propose a strategy for computing the mapping between schemas by performing a composition of the mappings between individual schemas and a reference ontology. Our premise is that many organizations have standard ontologies that, although they may not be suitable as a global schema, are useful in providing standard terminology and naming conventions for concepts and relationships. It is valuable to leverage these existing ontological resources to help automate the construction of a global schema and mappings between schemas. Our system semi-automates the matching between local schemas and a reference ontology then automatically composes the matchings to build mappings between schemas. Using these mappings, we use model management techniques to compute a global schema. A major advantage of this approach is that human intervention in validating matchings mostly occurs during the matching between schema and ontology. A problem is that matching schemas to ontologies is challenging because the ontology may only contain a subset of the concepts in the schema or may be more general than the schema. Further, the more complicated ontological graph structure limits the effectiveness of some matchers. Our contribution is showing how schema-to-ontology matchings can be used to compose mappings between schemas with high accuracy by adapting the COMA schema matching system to work with ontologies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Batini, C., Lenzerini, M., Navathe, S.: A Comparative Analysis of Methodologies for Database Schema Integration. ACM Computing Surveys 18, 323–364 (1986)

    Article  Google Scholar 

  2. Sheth, A., Larson, J.: Federated Database Systems for Managing Distributed, Heterogenous and Autonomous Databases. ACM Computing Surveys 22, 183–236 (1990)

    Article  Google Scholar 

  3. Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching. VLDB Journal 10, 334–350 (2001)

    Article  MATH  Google Scholar 

  4. Do, H.H., Rahm, E.: COMA - A System for Flexible Combination of Schema Matching Approaches. In: VLDB, pp. 610–621 (2002)

    Google Scholar 

  5. Bernstein, P.: Applying Model Management to Classical Meta Data Problems. In: CIDR (2003)

    Google Scholar 

  6. Beneventano, D., Bergamaschi, S., Guerra, F., Vincini, M.: Synthesizing an Integrated Ontology. IEEE Internet Computing 7, 42–51 (2003)

    Article  Google Scholar 

  7. Collet, C., Huhns, M., Shen, W.M.: Resource Integration Using a Large Knowledge Base in Carnot. IEEE Computer 24, 55–62 (1991)

    Google Scholar 

  8. Mena, E., Illarramendi, A., Kashyap, V., Sheth, A.: OBSERVER: An Approach for Query Processing in Global Information Systems based on Interoperation across Pre-existing Ontologies. Distributed and Parallel Databases 8, 223–271 (2000)

    Article  Google Scholar 

  9. Doan, A., Madhavan, J., Domingos, P., Halevy, A.: Learning to Map between Ontologies on the SemanticWeb. In: Proceedings of the 11th International Conference on the World Wide Web, pp. 662–673 (2002)

    Google Scholar 

  10. Lenat, D., Guha, R., Pittman, K., Pratt, D., Shepherd, M.: Cyc: Towards programs with common sense. Communications of the ACM 33, 30–49 (1990)

    Article  MATH  Google Scholar 

  11. Miller, G., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.: Five Papers on Word- Net. Technical Report CSL Report 43, Cognitive Systems Laboratory, Princeton University (1990)

    Google Scholar 

  12. Tzitzikas, Y., Constantopoulos, P., Spyratos, N.: Mediators over Ontology-Based Information Sources. In: WISE, pp. 31–40 (2001)

    Google Scholar 

  13. Decker, S., Erdmann, M., Studer, R.: ONTOBROKER: Ontology based access to distributed and semi-structured information. In: Database Semantics - Semantic Issues in Multimedia Systems. IFIP Conference Proceedings, vol. 138, Kluwer, Dordrecht (1998)

    Google Scholar 

  14. Madhavan, J., Bernstein, P., Rahm, E.: Generic Schema Matching with Cupid. In: VLDB, pp. 49–58 (2001)

    Google Scholar 

  15. Xu, L., Embley, D.: Discovering Direct and Indirect Matches for Schema Elements. In: DASFAA, pp. 39–46 (2003)

    Google Scholar 

  16. Doan, A., Domingos, P., Halevy, A.: Reconciling schemas of disparate data sources: a machine-learning approach. In: Proceedings of the ACM SIGMOD Conference on Management of Data, pp. 509–520 (2001)

    Google Scholar 

  17. Pottinger, R., Bernstein, P.: Merging Models Based on Given Correspondences. In: VLDB, pp. 826–873 (2003)

    Google Scholar 

  18. Noy, N., Musen, M.: PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: AAAI/IAAI, pp. 450–455 (2000)

    Google Scholar 

  19. Gal, A., Modica, G., Jamil, H.: OntoBuilder: Fully Automatic Extraction and Consolidation of Ontologies from Web Sources. In: ICDE, p. 853 (2004)

    Google Scholar 

  20. Ram, S., Park, J.: Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts. IEEE Trans. Knowl. Data Eng. 16, 189–202 (2004)

    Article  Google Scholar 

  21. Melnik, S., Rahm, E., Bernstein, P.: Rondo: A Programming Platform for Generic Model Management. In: SIGMOD, pp. 193–204 (2003)

    Google Scholar 

  22. Madhavan, J., Bernstein, P., Chen, K., Halvey, A., Shenoy, P.: Corpus-based Schema Matching. In: Workshop on Information Integration on the Web, IJCAI 2003 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dragut, E., Lawrence, R. (2004). Composing Mappings Between Schemas Using a Reference Ontology. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE. OTM 2004. Lecture Notes in Computer Science, vol 3290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30468-5_50

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30468-5_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23663-4

  • Online ISBN: 978-3-540-30468-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics