Schema Matching over Relations, Attributes, and Data Values

Automatic schema matching algorithms are typically only concerned with finding attribute correspondences. However, real world data integration problems often require matchings whose arguments span all three types of elements in rela-tional databases: relation, attribute and data value. This paper introduces the definitions and semantics of three ad-ditional correspondence types. These correspondences cover the higher-order mappings identified in a seminal paper by Krishnamurthy, Litwin, and Kent. It is shown that these correspondences can be automatically translated to tuple generating dependencies (tgds), and thus this research is compatible with data integration applications that leverage tgds. Two methods for automatically identifying these corre-spondences are developed. One requiring a limited number of duplicates across data sources. The other is a general instance-based method with no such requirement. Experi-ments conducted on four real world data sets demonstrate the effectiveness of the two methods