Ontology-based integration for relational databases

Dejing Dou, Paea LePendu

Abstract: In this paper, we show that representation and reasoning techniques used in traditional knowledge engineering and the emerging Semantic Web can play an important role for heterogeneous database integration. Our OntoGrate architecture combines ontology-based schema representation, first order logic inference, and some SQL wrappers to integrate two sample relational databases. We define inferential data integration as the theoretical framework for our approach. The performance evaluation for query answering shows that OntoGrate reformulates conjunctive queries and retrieves over 100,000 answers from a target database in under 30 seconds. In addition to query answering, the system translates 40,000 database facts from source to target in under 30 seconds.