The VLDB Journal

, Volume 10, Issue 4, pp 334–350

A survey of approaches to automatic schema matching

Authors

  • Erhard Rahm
    • Universität Leipzig, Institut für Informatik, 04109 Leipzig, Germany; (e-mail: rahm@informatik.uni-leipzig.de)
  • Philip A. Bernstein
    • Microsoft Research, Redmond, WA 98052-6399, USA; (e-mail: philbe@microsoft.com)
Regular contribution

DOI: 10.1007/s007780100057

Cite this article as:
Rahm, E. & Bernstein, P. The VLDB Journal (2001) 10: 334. doi:10.1007/s007780100057

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, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based 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.

Key words: Schema matching – Schema integration – Graph matching – Model management – Machine learning

Copyright information

© Springer-Verlag Berlin Heidelberg 2001