Ontology-based integration of data sources

Many applications, e.g., data/information fusion, data mining, and decision aids, need to access multiple heterogeneous data sources. These data sources may come from internal and external databases. They have to evolve due to requirement changes. Any change in an application domain induces semantics change in the data sources. The integration of these data sources raises several semantic heterogeneity problems. This has traditionally been the subject of data/schema integration and mapping. However, many heterogeneity conflicts remain in information integration due to lack of semantics. Therefore, richer semantics of data are needed to resolve the heterogeneity problems. Ontological approaches now offer new solution avenues to this interoperability limitation. In this perspective, we propose an ontology- based information integration with a local to global ontology mapping as an approach to the integration of heterogeneous data sources.