Enabling ontology evolution in data integration

Due to the rapid scientific development, ontologies and schemata need to change. When ontologies evolve, the changes should somehow be rendered and used by the pre-existing data integration systems, a problem that most of the integration systems available today seem to ignore. In this paper, we propose a data integration system that enables and exploits ontology evolution. We redefine data integration under ontology evolution and we show how to describe ontology evolution using logs. Then, we provide the algorithms for rewriting queries among different ontology versions and we present an algorithm based on MiniCon that uses these rewritings and that is guaranteed to find the set of maximally-contained rewritings for the sources. Our extension of the MiniCon algorithm does not involve a significant increase in computational complexity and remains scalable.