A DL-Based Approach to Integrate Relational Data Sources into the Semantic Web

The SemanticWeb is a new Web paradigm that provides a common framework for data to be shared and reused across applications, enterprises and community boundaries. The biggest problem we face right now is a way to "link" information coming from different sources that are often heterogeneous syntactically as well as semantically. Today much information is stored in relational databases. Thus data integration from relational sources into the Semantic Web is in high demand. The objective of this thesis is to provide methods and techniques to address this problem. It proposes an approach based on a combination of ontology-based schema representation and description logics. Database schemas in the approach are designed using ORM methodology. The stability and flexibility of ORM facilitate the maintenance and evolution of integration systems. A new web ontology language and its logic foundation are proposed in order to capture the semantics of relational data sources while still assuring a decidable and automated reasoning over information from the sources. An automatic translation of ORM models into ontologies is introduced to allow capturing the data semantics without laboriousness and fallibility. This mechanism foresees the coexistence of others sources, such as hypertext, integrated into the Semantic Web environment. This thesis constitutes the advances in many fields, namely data integration, ontology engineering, description logics, and conceptual modeling. It is hoped to provide a foundation for further investigations of data integration from relational sources into the Semantic Web.