Mapping the semantic web to SQL query to extract knowledge Inaya Lahoud 1 . Davy Monticolo 2 , Vincent Hilaire 1 1 SET Laboratory, University of Technology of Belfort-Montbeliard, Belfort, France {Inaya.Lahoud, Vincent.Hilaire}@utbm.fr 2 ERPI Laboratory, Polytechnic National Institute of Lorraine, Nancy, France {Davy.Monticolo@ensgsi.inpl-nancy.fr} Abstract. Among the goals of Knowledge Management (KM) we can cite the identification and capitalization of the know-how of companies in order to organize and disseminate them. KM is recognized as a non- trivial task. In the context of extended enterprises it is even more diffi- cult because they are geographically distributed and use heterogeneous information systems. Indeed, information, from which knowledge is de- rived from, is stored in different databases, distributed in different sites across the entire network of the extended enterprise. This paper pro- poses a semi-automatic approach for knowledge extraction from sever- al databases. This knowledge will be stored in an organizational memory (OM). The approach is based upon the definition of ontologies for knowledge exchange and Model Driven Engineering concepts such as meta-models and transformation to process requests. Keywords: Ontology, Semantic Web Service, Knowledge Management, Model Driven Engineering, Interoperability, Mapping 1 Introduction: The process of designing manufactured products (called products from now on) fre- quently requires the use of several heterogeneous business tools (calculation tool, CAD tool, a tool for production management, PLM, PDM, etc.). Each of these tools deals with specific aspects of product design such as: CAD, project management, resource planning and PLM. In the nowadays context, these tools are distributed on different sites across the entire network of the extended enterprise. Moreover, to survive in an increasingly competitive business environment, manufac- turing enterprises are under unprecedented pressure to become leaner and more agile. The product range must be updated permanently and production costs the lowest pos- sible. Product leadership companies must continue to enter new market with innova- tive products. This requires optimizing process and methodologies used by engineer- ing department. The design process has to be rationalized in capitalizing knowledge,