Resolving semantic heterogeneity in schema integration

ABSTRACT

Interoperability and integration of data sources are becoming ever more important issues as both, the amount of data and the number of data producers are growing. Interoperability not only has to resolve the differences in data structures, it also has to deal with semantic heterogeneity. Semantics refer to the meaning of data in contrast to syntax, which only defines the structure of the schema items (e.g., classes and attributes). We focus on the part of semantics related to the meanings of the terms used as identifiers in schema definitions. This paper presents an approach to integrate schemas from different communities, where each such community is using its own ontology. The approach is based on merging ontologies based on similarity relations among concepts of different ontologies. We present formal definitions of similarity relations based on intensional definitions and conclude the extensional consequences. The process of merging ontologies based on the detected similarity relations is discussed. The merged ontology is finally used to derive an integrated schema. The resulting schema can be used as the global schema in a federated database system.

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INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
        D.2.12 Interoperability
            Subjects: Data mapping

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.5 Heterogeneous Databases

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods

General Terms:
Design

Keywords:
database integration, formal ontologies, semantic heterogeneity