Ontology Mapping

  • Natalya F. NoyEmail author
Part of the International Handbooks on Information Systems book series (INFOSYS)


However, if we want to have the applications using different ontologies to “talk” to one another, or if we want to integrate data that is annotated with or structured according to different ontologies, we must first find the correspondences between concepts in these ontologies. The process of finding such correspondences is called ontology mapping. Ontology mapping (also referred to as ontology matching, or ontology alignment) is one of the most active areas of ontology research. Creating high-quality ontology mappings automatically is the holy grail of the Semantic Web research. Ontologies have gained popularity in the AI community as a means for establishing explicit formal vocabulary to share between applications. Therefore, one can say that one of the goals of using ontologies is not to have the problem of heterogeneity at all. It is of course unrealistic to hope that there will be an agreement on one or even a small set of ontologies. While having some common ground either within an application area or for some high-level general concepts could alleviate the problem of semantic heterogeneity, we will still need to map between ontologies, whether they extend the same foundational ontology or are developed independently.


Ontology Mapping Ontology Match Reference Ontology Local Ontology Source Ontology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Some portions of this chapter appeared as an article in SIGMOD Record in 2004. I would like to thank AnHai Doan, Michael Grüninger, and Yannis Kalfoglou for thoughtful and helpful comments on that article. Sean Falconer implemented many components of the Prompt plugin framework. Most important, I am extremely grateful to Mark Musen for the many years of guidance and support in this work.


  1. 1.
    Z. Aleksovski, M. Klein, W. ten Kate, and F. van Harmelen. Matching unstructured vocabularies using a background ontology. In 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW’06), 2006.Google Scholar
  2. 2.
    P. Bouquet, F. Giunchiglia, F. van Harmelen, L. Serafini, and H. Stuckenschmidt. C-OWL: Contextualizing ontologies. In International Semantic Web Conference (ISWC), Sanibel Isalnd, Florida, 2003.Google Scholar
  3. 3.
    D. Calvanese, G. Giacomo, and M. Lenzerini. Ontology of integration and integration of ontologies. In Description Logic Workshop (DL 2001), pages 10–19, 2001.Google Scholar
  4. 4.
    D. Calvanese, G. De Giacomo, M. Lenzerini, R. Rosati, and G. Vetere. DL-lite: Practical Reasoning for Rich DLs. In International Workshop on Description Logics (DL2004), Whistler, Canada, 2004.Google Scholar
  5. 5.
    M. Crubézy and M. A. Musen. Ontologies in support of problem solving. In S. Staab and R. Studer, editors, Handbook on Ontologies, pages 321–342. Springer, Berlin, 2003.Google Scholar
  6. 6.
    H. Do. Schema Matching and Mapping-based Data Integration. PhD thesis, Department of Computer Science, Universitt Leipzig, 2006.Google Scholar
  7. 7.
    A. Doan, J. Madhavan, P. Domingos, and A. Halevy. Learning to map between ontologies on the semantic web. In The Eleventh International WWW Conference, Hawaii, US, 2002.Google Scholar
  8. 8.
    D. Dou, D. McDermott, and P. Qi. Ontology translation on the semantic web. In International Conference on Ontologies, Databases and Applications of Semantics, 2003.Google Scholar
  9. 9.
    M. Ehrig and S. Staab. QOM – Quick Ontology Mapping. In 3rd International Semantic Web Conference (ISWC2004), Hiroshima, Japan, 2004.Google Scholar
  10. 10.
    M. Ehrig and Y. Sure. FOAM – framework for ontology alignment and mapping; results of the ontology alignment initiative. In Proceedings of the Workshop on Integrating Ontologies, volume 156, pages 72–76, October 2005.Google Scholar
  11. 11.
    J. Euzenat, A. Isaac, C. Meilicke, P. Shvaiko, H. Stuckenschmidt, O. Šváb, V. Svátek, W. van Hage, and M. Yatskevich. Results of the ontology alignment evaluation initiative 2007. In 2nd International Workshop on Ontology Matching (OM-2007) at ISWC 2007, 2007.Google Scholar
  12. 12.
    J. Euzenat and P. Valtchev. Similarity-based ontology alignment in OWL-Lite. In The 16th European Conference on Artificial Intelligence (ECAI-04), Valencia, Spain, 2004.Google Scholar
  13. 13.
    J. Euzenat, M. Mochol, P. Shvaiko, H. Stuckenschmidt, Ondrej Sváb, Vojtech Sváte, Willem Robert van Hage, and Mikalai Yatskevich. Results of the ontology alignment evaluation initiative 2006. In International Workshop on Ontology Matching at ISWC-2006, Athens, GA, 2006.Google Scholar
  14. 14.
    S. Falconer, N. Noy, and M. A. Storey. Towards understanding the needs of cognitive support for ontology mapping. In International Workshop on Ontology Matching at ISWC-2006, Athens, GA, 2006.Google Scholar
  15. 15.
    A. Gangemi, N. Guarino, C. Masolo, and A. Oltramari. Sweetening wordnet with DOLCE. AI Magazine, 24(3):13–24, 2003.zbMATHGoogle Scholar
  16. 16.
    F. Giunchiglia, P. Shvaiko, and M. Yatskevich. S-match: an algorithm and an implementation of semantic matching. In European Conference on Semantic Web (ESWC 2004), pages 61–75, 2004.Google Scholar
  17. 17.
    F. Giunchiglia, P. Shvaiko, and M. Yatskevich. Semantic matching. In 1st European semantic web symposium (ESWS’04), pages 61–75, Heraklion, Greece, 2004.Google Scholar
  18. 18.
    R. Gligorov, Z. Aleksovski, W. ten Kate, and F. van Harmelen. Using Google distance to weight approximate ontology matches. In Seventeenth World Wide Web Conference WWWW-07, Banff, Canada, 2007.Google Scholar
  19. 19.
    M. Grüninger. A guide to the ontology of the process specification language. In S. Staab and R. Studer, editors, Handbook on Ontologies. Springer, Berlin, 2003.Google Scholar
  20. 20.
    M. Grüninger and J. Kopena. Semantic integration through invariants. In A. Doan, A. Halevy, and N. Noy, editors, Workshop on Semantic Integration at ISWC-2003, Sanibel Island, FL, 2003.Google Scholar
  21. 21.
    M. Hernandez, R. Miller, L. Haas, L. Yan, C. T. Howard Ho, and X. Tian. Clio: A semi-automatic tool for schema mapping. In SIGMOD Record, 2001.Google Scholar
  22. 22.
    Y. Jean-Mary and M. Kabuka. ASMOV: ontology alignment with semantic validation. In JointSWDB-ODBIS Workshop on Semantics, Ontologies, Databases, Vienna, Austria, 2007.Google Scholar
  23. 23.
    N. Jian, W. Hu, G. Cheng, and Y. Qu. Falcon-ao: Aligning ontologies with falcon. In K-Cap Workshop on Integrating Ontologies, 2005.Google Scholar
  24. 24.
    Y. Kalfoglou and M. Schorlemmer. Ontology mapping: the state of the art. The Knowledge Engineering Review, 18(1):1–31, 2003.CrossRefzbMATHGoogle Scholar
  25. 25.
    M. Klein. Combining and relating ontologies: an analysis of problems and solutions. In IJCAI-2001 Workshop on Ontologies and Information Sharing, pages 53–62, Seattle, WA, 2001.Google Scholar
  26. 26.
    A. Maedche, B. Motik, N. Silva, and R. Volz. MAFRA - a mapping framework for distributed ontologies. In 13th European Conference on Knowledge Engineering and Knowledge Management EKAW, Madrid, Spain, 2002.Google Scholar
  27. 27.
    I. Niles and A. Pease. Towards a standard upper ontology. In The 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001), Ogunquit, Maine, 2001.Google Scholar
  28. 28.
    N. F. Noy and M. A. Musen. The PROMPT suite: Interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies, 59(6):983–1024, 2003.CrossRefGoogle Scholar
  29. 29.
    N. F. Noy. Tools for mapping and merging ontologies. In S. Staab and R. Studer, editors, Handbook on Ontologies, pages 365–384. Springer, Berlin, 2003.Google Scholar
  30. 30.
    S. Polyak, J. Lee, M. Grüninger, and C. Menzel. Applying the process interchange format(PIF) to a supply chain process interoperability scenario. In Workshop on Applications of Ontologies and Problem Solving Methods, ECAI’98, Brighton, England, 1998.Google Scholar
  31. 31.
    E. Rahm and P. A. Bernstein. A survey of approaches to automatic schema matching. VLDB Journal, 10(4), 2001.Google Scholar
  32. 32.
    D. L. Rubin, S. E. Lewis, C. J. Mungall, S. Misra, M. Westerfield, M. Ashburner, I. Sim, C. G. Chute, H. Solbrig, M. A. Storey, B. Smith, J. Day-Richter, N. F. Noy, and M. A. Musen. The national center for biomedical ontology: Advancing biomedicinethrough structured organization of scientific knowledge. OMICS: A Journal of Integrative Biology, 10(2), 2006.Google Scholar
  33. 33.
    M. Sabou, J. Gracia, S. Angeletou, M. dAquin, and E. Motta. Evaluating the semantic web: A task-based approach. In K. Aberer, K. S. Choi, and N. Noy, editors, 6th International Semantic Web Conference (ISWC 2007), Busan, Korea, 2007. Springer.Google Scholar
  34. 34.
    P Shvaiko and J Euzenat. A survey of schema-based matching approaches. Journal on Data Semantics, 4:146–171, 2005.zbMATHGoogle Scholar
  35. 35.
    A. Valente, T. Russ, R. MacGrecor, and W. Swartout. Building and (re)using an ontology for air campaign planning. IEEE Intelligent Systems, 14(1):27–36, 1999.CrossRefGoogle Scholar
  36. 36.
    S. Zhang and O. Bodenreider. Alignment of multiple ontologies of anatomy: Deriving indirect mappings from direct mappings to a reference. In AMIA Annual Symposium, pages 864–868, 2005.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Stanford UniversityStanfordUSA

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