Background Knowledge in Schema Matching: A Survey

Tracking #: 2683-3897

This paper is currently under review
Jan Portisch
Michael Hladik
Heiko Paulheim

Responsible editor: 
Jérôme Euzenat

Submission type: 
Survey Article
Schema matching is an integral part within the data integration process. One of the main challenges within the schema matching operation is semantic heterogeneity, i.e. modeling differences between the two schemas that are to be integrated. The semantics within most schemas are, however, typically incomplete because schemas are designed within a certain context which is not explicitly modeled. Therefore, external background knowledge plays a major role in the task of (semi-) automated schema matching. In this survey, we introduce the reader to the schema matching problem and its abstraction, the ontology matching task. We review the background knowledge sources as well as the approaches applied to make use of external knowledge. Our survey covers all schema matching systems that have been presented within the years 2004 -- 2020 at a well-known ontology matching competition together with significant publications in the research field. We present a classification system for external background knowledge, concept linking strategies, as well as for background knowledge exploitation approaches. We provide extensive examples and classify all schema matching systems under review in a resource/strategy matrix obtained by coalescing the two classification systems. Lastly, we outline interesting and yet underexplored research directions of applying external knowledge within the schema matching process.
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Also check "Experiences from the anatomy track in the ontology alignment evaluation initiative" that has a section on the use of background in 10 years of OAEI Anatomy.