A Graph-Oriented Model for Articulation of Ontology Interdependencies

  • Prasenjit Mitra
  • Gio Wiederhold
  • Martin Kersten
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1777)


Ontologies explicate the contents, essential properties, and relationships between terms in a knowledge base. Many sources are now accessible with associated ontologies. Most prior work on the use of ontologies relies on the construction of a single global ontology covering all sources. Such an approach is not scalable and maintainable especially when the sources change frequently. We propose a scalable and easily maintainable approach based on the interoperation of ontologies. To handle user queries crossing the boundaries of the underlying information systems, the interoperation between the ontologies should be precisely defined. Our approach is to use rules that cross the semantic gap by creating an articulation or linkage between the systems. The rules are generated using a semi-automatic articulation tool with the help of a domain expert. To make the ontologies amenable for automatic composition, based on the accumulated knowledge rules, we represent them using a graph-oriented model extended with a small algebraic operator set. ONION, a user-friendly toolkit, aids the experts in bridging the semantic gap in real-life settings. Our framework provides a sound foundation to simplify the work of domain experts, enables integration with public semantic dictionaries, like Wordnet, and will derive ODMG-compliant mediators automatically.


semantic interoperation ontology algebra graph-based model 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    The context interchange project,
  2. 2.
    Cyc knowledge base,
  3. 3.
    Information integration using infomaster,
  4. 4.
  5. 5.
  6. 6.
    The stanford-ibm manager of multiple information sources,
  7. 7.
    Extensible markup language (xml) 1.0, Feb 1999.
  8. 8.
    Resource description framework (rdf) model and syntax specification,, February 1999.
  9. 9.
    P. Buneman, S. Davidson, and A. Kosky. Theoretical aspects of schema merging. In Proc. of EDBT’ 92, pages 152–167. EDBT, Springer Verlag, Mar. 1992.Google Scholar
  10. 10.
    M. Gyssens, J. Paredaens, and D. Van Gucht. A graph-oriented object database model. In Proc. PODS, pages 417–424, 1990.Google Scholar
  11. 11.
    J. Jannink. Resolution of Semantic Differences in Ontologies. PhD thesis, Stanford University.Google Scholar
  12. 12.
    C.A. Knoblock, S. Minton, J.L. Ambite, N. Ashish, P.J. Modi, Ion Muslea, A.G. Philpot, and S. Tejada. Modeling web sources for information integration. In Proc. of the Fifteenth National Conf. on Artificial Intelligence, Madison, WI, 1998.Google Scholar
  13. 13.
    A.T. McCray, A.M. Razi, A.K. Bangalore, A.C. Browne, and P.Z. Stavri. The umls knowledge source server: A versatile internet-based research tool. In Proc. AMIA Fall Symp, pages 164–168, 1996.Google Scholar
  14. 14.
    P. Mitra. Algorithms for answering queries efficiently using views, Technical report, Infolab, Stanford University, September 1999.
  15. 15.
    P. Mitra, G. Wiederhold, and J. Jannink. Semi-automatic integration of knowledge sources. In Proc. of the 2nd Int. Conf. On Information FUSION’99, 1999.Google Scholar
  16. 16.
    Y. Papakonstantinou, H. Garcia-Molina, and Widom J. Object exchange across heterogeneous information sources, March 1995.Google Scholar
  17. 17.
    P. Scheuermann, C. Yu, A. Elmagarmid, H. Garcia-Molina, F. Manola, D. McLeod, A. Rosenthal, and M. Templeton. Report on the workshop on heterogenous database systems. In ACM SIGMOD RECORD 19,4, pages 23–31, 1989.Google Scholar
  18. 18.
    A.P. Sheth and J.A. Larson. Federated database systems for managing distributed, heterogenous, and autonomous databases. In ACM Computing Surveys, pages 183–236, 1994.Google Scholar
  19. 19.
    M. Siegel and S. Madnick. A metadata approach to solving semantic conflicts. In Proc. of the 17th Int. Conf. on Very Large Data Bases, pages 133–145, 1991.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Prasenjit Mitra
    • 1
  • Gio Wiederhold
    • 1
  • Martin Kersten
    • 2
  1. 1.Stanford UniversityStanfordUSA
  2. 2.INSCWIAmsterdamThe Netherlands

Personalised recommendations