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, schema matching is typically performed manually, which has significant limitations. On the other hand, in previous research many techniques have been proposed to achieve a partial automation of the Match operation for specific application domains. We present a taxonomy that covers many of the existing approaches, and we describe these approaches in some detail. In particular, we distinguish between schema- and instance-level, element- and structure-level, and language- and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.

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