Towards Matching of Domain-Specific Schemas Using General-Purpose External Background Knowledge

Schema matching is an important and time consuming part within the data integration process. Yet, it is rarely automatized - particularly in the business world. In recent years, the amount of freely available structured knowledge has grown exponentially. Large knowledge graphs such as BabelNet, DBnary (Wiktionary in RDF format), DBpedia, or Wikidata are available. However, these knowledge bases are hardly exploited for automated matching. One exception is the biomedical domain: Here domain-specific background knowledge is broadly available and heavily used with a focus on reusing existing alignments and on exploiting larger, domain-specific mediation ontologies. Nonetheless, outside the life sciences domain such specialized structured resources are rare. In terms of general knowledge, few background knowledge sources are exploited except for WordNet. In this paper, we present our research idea towards further exploiting general-purpose background knowledge within the schema matching process. An overview of the state of the art is given and we outline how our proposed research approach fits in. Potentials and limitations are discussed and we summarize our intermediate findings.