An automated information integration technique using an ontoly-based database approach

Developing intelligent systems to integrate numerous 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 because of the mechanisms of solving different conflicts existing in an heterogeneous context. Even more these data sources do not contain enough knowledge to help solving these conflicts and then generating the global schema. In this paper, we present a new approach to integrate heterogeneous sources based on a priori approach (ontology-based database). The originality of our approach is that each data source participating in the integration process contains an ontology that defines the meaning of its own data using an ontology model called PLIB. This approach ensures the automation of the integration process when (1) all data sources have the same ontology, and (2) all sources reference a shared ontology, and each one can extent this ontology by adding new concepts. Finally, we present integration algorithms for the previous cases.

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