Contribution of ontology-based data modeling to automatic integration of electronic catalogues within engineering databases

Developing intelligent systems to integrate numerous, autonomous and heterogeneous data sources in order to give end users an uniform query interface is a great challenging issue. The process of constructing a global schema of the integrated system is usually done manually. This is due to the presence of semantic and schematic heterogeneities among schemas of sources. In most cases, sources do not contain enough knowledge to help in solving these heterogeneities and then generating the global schema. In this paper, we present an ontology-driven integration approach called a priori approach. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration process when all sources reference a shared ontology, and possibly extend it by adding their own concept specializations. We present two integration algorithms where (1) the shared ontology may be extended during the integration process, and (2) the instances of local sources are projected onto the shared ontology. Finally, we show that this theory allows to integrate automatically electronic catalogues into corporate engineering databases using the PLIB ontology model.