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. In most of these systems, when ontologies change their relations with the data sources i.e. the mappings, are recreated manually, a process which is known to be error-prone and time-consuming. In this dissertation, we provide a solution that allows query answering under evolving ontologies without mapping redefinition. This is achieved by exploiting query rewriting. We elegantly separate the semantics of query rewriting for different ontology versions and for the sources and we present a module that enables ontology evolution over traditional ontology-based data integration systems. That module gets as input the different ontology versions and the user query, and rewrites the query over data integration systems that use different ontology versions. This is performed by the automatic identification of changes among the ontology versions using a high-level language of changes, which are then interpreted as GAV mappings to enabl