OWL schema matching

Abstract

Abstract Schema matching is a fundamental issue to many database applications, such as query mediation and data warehousing. It becomes a challenge when different vocabularies are used to refer to the same real-world concepts. In this context, a convenient approach, sometimes called extensional, instance-based, or semantic, is to detect how the same real world objects are represented in different databases and to use the information thus obtained to match the schemas. Additionally, we argue that automatic approaches of schema matching should store provenance data about matchings. This paper describes an instance-based schema matching technique for an OWL dialect and proposes a data model for storing provenance data. The matching technique is based on similarity functions and is backed up by experimental results with real data downloaded from data sources found on the Web.