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Today, databases provide the best technique for storing and retrieving data, but they suffer from the absence of a semantic perspective, which is needed to reach global goals such as the semantic web and data integration. Using ontologies will solve this problem by enriching databases semantically. Since building an ontology from scratch is a very complicated task, the authors propose an automatic transformation system to build Web Ontology Language OWL ontologies from a relational model written in Structured Query Language SQL. Their system also uses metadata, which helps to extract some semantic aspects which could not be inferred from the SQL. Their system analyzes database tuples to capture these metadata.
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