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Hybrid Architecture of oWL-ontologies for relational data Sources integration
Abstract
Data integration is one of the most important tasks in the data warehousing process. The use of ontologies in the mediation process allows semantic and structural integration. In this paper, we propose a new mediation system based on an hybrid architecture of ontologies modelled according to GLAV (Generalized Local As View) model. The hybrid architecture builds a local ontology for each data source and a global ontology viewed as a mediator. The integration model defines how sources, local and global ontologies are mapped. So we propose an ascending method for building ontologies, which facilitates the semantic reconciliation between data sources. Moreover, we use OWL (Ontology Web Language) for defining ontologies and mappings between data sources and ontologies. User queries are expressed in our specific language which handles global ontology concepts and local ontologies properties because we assume that the user is expert in its domain. Queries are decomposed by the rewriting algorithm to obtain a set of equivalent subqueries that are sent to the corresponding sources for execution, and after that recomposed to obtain the final result.
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