A comparative analysis of methodologies for database schema integration
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CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
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In this paper, we introduce an approach to task-driven ontologydesign which isbased on information discovery from database schemas. Techniques forsemi-automatically discovering terms and relationships used in the informationspace, denoting concepts, their properties and links are proposed, which areapplied in two stages. At the first stage, the focus is on the discovery of heterogeneity/ambiguity of data representations in different schemas. For thispurpose, schema elements are compared according to defined comparison featuresand similarity coefficients are evaluated. This stage produces a set ofcandidates for unification into ontology concepts. At the second stage,decisions are made on which candidates to unify into concepts and on how torelate concepts by semantic links. Ontology concepts and links can be accessedaccording to different perspectives, so that the ontology can serve differentpurposes, such as, providing a search space for powerful mechanisms forconcept location, setting a basis for query formulation and processing, andestablishing a reference for recognizing terminological relationships betweenelements in different schemas.