A semi-automated approach to transforming database schemas into ontology language

Transforming database schemas into an ontology language opens the door wide to the many advantages offered by the Semantic Web. Industries in particular can benefit from intelligent systems (e.g., decision-support systems) arising from such transformations. In this paper, we propose a semi-automated algorithm to transform data to the ontology language, OWL, while taking advantage of the actual data stored in a database schema. These data are used to discover hidden patterns in a database schema with a minimal level of human involvement. Such an approach also ensures improved mappings for relatively loosely structured database schema. The evaluation results on a simple DBLP database schema show improved effectiveness of such transformations.