A Discovery-Based Approach to Database Ontology Design
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In this paper, we introduce an approach to task-driven ontology design which is based on information discovery from database schemas. Techniques for semi-automatically discovering terms and relationships used in the information space, denoting concepts, their properties and links are proposed, which are applied in two stages. At the first stage, the focus is on the discovery of heterogeneity/ambiguity of data representations in different schemas. For this purpose, schema elements are compared according to defined comparison features and similarity coefficients are evaluated. This stage produces a set of candidates for unification into ontology concepts. At the second stage, decisions are made on which candidates to unify into concepts and on how to relate concepts by semantic links. Ontology concepts and links can be accessed according to different perspectives, so that the ontology can serve different purposes, such as, providing a search space for powerful mechanisms for concept location, setting a basis for query formulation and processing, and establishing a reference for recognizing terminological relationships between elements in different schemas.
KeywordsOntology design Similarity techniques Schema analysis and clustering. Distributed and heterogeneous databases.
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- 2.P. Atzeni, V. De Antonellis, Relational Database Theory, The Benjamin/Cummings Publishing Company, 1993.Google Scholar
- 7.S. Castano, V. De Antonellis, M.G. Fugini, B. Pernici, “Conceptual Schema Analysis: Techniques and Applications,” ACM Transactions on Database Systems, (to appear).Google Scholar
- 8.S. Castano, V. De Antonellis, “Semantic Dictionary Design for Database Interoperability,” in Proc. of ICDE’97, 13th IEEE Conf. on Data Engineering, Birmingham, 1997, pp. 43–54.Google Scholar
- 9.R. Cattell (ed.), The Object Database Standard: ODMG-93, Morgan Kaufmann, 1996.Google Scholar
- 10.B. Everitt, Cluster Analysis, Heinemann Educational Books Ltd, Social Science Research Council, 1974.Google Scholar
- 11.N.V. Findler, (Ed.), Associative Networks, Academic Press, 1979.Google Scholar
- 12.H. Garcia-Molina, et al., “The TSIMMIS Approach to Mediation: Data Models and Languages,” in Proc. of the NGITS workshop, 1995Google Scholar
- available at ftp://db.stanford.edu/pub/garcia/1995/tsimmis-models-languages.ps).
- 13.J. Gilarranz J. Gonzalo, F. Verdejo, “Using the Euro Word Net Multilingual Semantic Database,” in Proc. of AAAI-96 Spring Symposium Cross-Language Text and Speech Retrieval, 1996.Google Scholar
- 15.T.R. Gruber, “Ontolingua: A Mechanism to Support Portable Ontologies,” Tech. Rep. KSL 91–66, Stanford University, Knowledge System Laboratory, March 1992.Google Scholar
- 17.N. Guarino, R. Poli, (eds.), Formal Ontology in Conceptual Analysis and Knowledge Representation, Special Issue of the Int. Journal of Human and Computer Studies, vol. 43, Nos.5/6, Academic Press, 1995.Google Scholar
- 19.M.A. Jeusfeld, M. Papazoglou, “Information Brokering,” in .Google Scholar
- 20.B. Kramer, M. Papazoglou, H.W. Schmidt, (eds.), Information Systems Interoperability, RSP Press, John Wiley, 1998.Google Scholar
- 21.Internet-Based Agents,“ Special Issue of IEEE Internet Computing, vol. 1, no. 4, July/August 1997.Google Scholar
- 23.A.Y. Levy, A. Rajaraman, J.J. Ordille, “Querying Heterogeneous Information Sources Using Source Descriptions,” in Proc. of VLDB’96, the 22th Int. Conf. on Very Large Databases, Mumbai (Bombay), 1996.Google Scholar
- 25.Documentation available at mcf.research.apple.com/.
- 26.D. McLeod, A. Si, “The Design and Experimental Evaluation of an Information Discovery Mechanism for Networks of Autonomous Database Systems,” in Proc. of ICDE’95, 11th Conf. on Data Engineering, Taiwan, 1995, pp. 15–24.Google Scholar
- 27.E. Mena, V. Kashyap, A. Sheth, A. Illarramendi, “OBSERVER: An Approach for Query Processing in Global Information Systems based on Interoperation across Pre-existing Ontologies,” in Proc. of First IFCIS International Conference on Cooperative Information Systems (CoopIS’96), Brussels ( Belgium),, June 1996, pp. 14–25.CrossRefGoogle Scholar
- 28.Mikrokosmos Ontology,“ Documentation available at http://crl.nmsu.edu/research/Projects/mikro/htmis/ontology-htmis/onto.index.html,1996.
- 30.G. Salton, Automatic Text Processing - The Transformation, Analysis and Retrieval of Information by Computer, Addison-Wesley, 1989.Google Scholar
- 32.T.J. Teorey, G. Wei, D. L. Bolton, Koenig, J.A., “ER Model Clustering as an Aid for User Communication and Documentation in Database Design,” Communications of the ACM, vol. 3, no. 8, 1989.Google Scholar
- 33.Guidelines for the Construction and Development of Monoligual Thesauri,“ UNI ISO Report N.2788, 1993.Google Scholar