Schema matching is the process of developing semantic matches between two or more schemas. The purpose of schema matching is generally either to merge two or more databases, or to enable queries on multiple, heterogeneous databases to be formulated on a single schema (Doan and Halevy 2005). This paper develops a taxonomy of schema matching approaches, classifying them as being based on a combination schema matching technique and the type of data used by those techniques. Schema matching techniques are categorized as being based on rules, learning, or ontology, and the type of data used is categorized as being based on schema elements or instance data. This taxonomy is an extension to previous work, and significant current research efforts are categorized using this taxonomy. Several of these research efforts are profiled and their categorization in the taxonomy is explored. The current research is used to identify the directions in which future research is headed.
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