On Matching Schemas Automatically

Abstract Schema matching is a basic problem in many database application domains, such as data integration,E-business, data warehousing, and semantic query processing. In current implementations, schemamatching is typically performed manually, which has significant limitations. On the other hand, inprevious research many techniques have been proposed to achieve a partial automation of the Matchoperation for specific application domains. We present a taxonomy that covers many of the existingapproaches, and we describe these approaches in some detail. In particular, we distinguish betweenschema- and instance-level, element- and structure-level, and language- and constraint-based match-ers. Based on our classification we review some previous match implementations thereby indicatingwhich part of the solution space they cover. We intend our taxonomy and review of past work to beuseful when comparing different approaches to schema matching, when developing a new matchalgorithm, and when implementing a schema matching component.

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