Data integration aims to facilitate the exploitation of heterogeneous data by providing the user with a unified view of data residing in different sources. Currently, ontologies are commonly used to represent this unified view in terms of a global target schema due to their flexibility and expressiveness. However, most approaches still assume a predefined target schema and focus on generating the mappings between this schema and the sources. In this paper, we propose a solution that supports data integration tasks by employing semi-automatic ontology construction to create a target schema on the fly. To that end, we revisit existing ontology extraction, matching and merging techniques and integrate them into a single end-to-end system. Moreover, we extend the used techniques with the automatic generation of mappings between the extracted ontologies and the underlying data sources. Finally, to demonstrate the usefulness of our solution, we integrate it with an independent data integration system.

Peer Reviewed