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Towards Theory Translation

  • Dejing Dou
  • Drew McDermott
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4327)

Abstract

Ontologies play a key role in agent communication and the emerging Semantic Web to define a vocabulary of concepts and their relationships. Different agents and web services may use vocabularies from different ontologies to describe their data. The current research on ontology mapping and ontology translation mainly focuses on how to map and translate vocabularies and associated data instances from one ontology to another. However, more complicated true statements, such as axioms (rules), are used or being developed to describe the relationships among the concepts. When extending one ontology using complicated true statements (theory) from another, we must confront the problem of theory translation, which is difficult because of the asymmetry of translation. In this paper, using an inferential approach we call axiom derivation, we show how to translate complex axioms between different time ontologies. We also prove the validity of our algorithm.

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References

  1. 1.
    DAML+OIL web ontology language, http://www.w3.org/TR/daml+oil-reference
  2. 2.
    OWL Web Ontology Language, http://www.w3.org/TR/owl-ref/
  3. 3.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5) (May 2001)Google Scholar
  4. 4.
    Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L., Stuckenschmidt, H.: C-OWL: Contextualizing Ontologies. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 164–179. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  5. 5.
    Bouquet, P., Magnini, B., Serafini, L., Zanobini, S.: A SAT-based algorithm for context matching. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds.) CONTEXT 2003. LNCS, vol. 2680, pp. 66–79. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Buvac, S., Fikes, R.: A Declarative Formalization of Knowledge Translation. In: Proceedings of the ACM CIKM conference (1995)Google Scholar
  7. 7.
    Chalupsky, H.: Ontomorph: A Translation System for Symbolic Logic. In: Proceedings of the KR conference 2000, pp. 471–482 (2000)Google Scholar
  8. 8.
    Corcho, Ó., Gómez-Pérez, A.: A Layered Model for Building Ontology Translation Systems. Int. J. Semantic Web Inf. Syst. 1(2), 22–48 (2005)CrossRefGoogle Scholar
  9. 9.
    Dell’Erba, M., Fodor, O., Ricci, F., Werthner, H.: Harmonise: A solution for data interoperability. In: I3E 2002 (2002)Google Scholar
  10. 10.
    Doan, A., Madhavan, J., Domingos, P., Halevy, A.Y.: Learning to Map Between Ontologies on the Semantic Web. In: International World Wide Web Conferences (WWW), pp. 662–673 (2002)Google Scholar
  11. 11.
    Dou, D., LePendu, P.: Ontology-based Integration for Relational Databases. In: SAC 2006 Proceedings of the 2006 ACM symposium on Applied computing, pp. 461–466 (2006)Google Scholar
  12. 12.
    Dou, D., McDermott, D.: Deriving Axioms across Ontologies. In: Proceedings of International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2006), pp. 952–954 (2006)Google Scholar
  13. 13.
    Dou, D., McDermott, D.V., Qi, P.: Ontology Translation on the Semantic Web. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 952–969. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Dou, D., McDermott, D.V., Qi, P.: Ontology Translation on the Semantic Web. Journal of Data Semantics 2, 35–57 (2005)CrossRefGoogle Scholar
  15. 15.
    Gruber, T.: Ontolingua: A Translation Approach to Providing Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  16. 16.
    Horrocks, I., Patel-Schneider, P.F.: A proposal for an OWL rules language. In: WWW, pp. 723–731 (2004)Google Scholar
  17. 17.
    Maedche, A., Motik, B., Silva, N., Volz, R.: MAFRA - A MApping FRAmework for Distributed Ontologies, pp. 235–250 (2002)Google Scholar
  18. 18.
    McCarthy, J., Buvac, S.: Formalizing context (expanded notes). In: Aliseda, A., van Glabbeek, R., Westerstahl, D. (eds.) Computing Natural Language. University of Chicago Press (1997)Google Scholar
  19. 19.
    McDermott, D.V., Dou, D.: Representing Disjunction and Quantifiers in RDF. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 250–263. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  20. 20.
    Mitra, P., Wiederhold, G., Kersten, M.: A graph-oriented model for articulation of ontology interdependencies. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, p. 86. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  21. 21.
    Noy, N.F.: Semantic Integration: A Survey Of Ontology-Based Approaches. SIGMOD Record 33(4), 65–70 (2004)CrossRefGoogle Scholar
  22. 22.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall Inc., Englewood Cliffs (1995)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dejing Dou
    • 1
  • Drew McDermott
    • 2
  1. 1.Computer and Information ScienceUniversity of OregonEugeneUSA
  2. 2.Computer Science DepartmentYale UniversityNew HavenUSA

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