Today, most business tasks require the use of information from a variety of data sources. This information constitutes the knowledge of an organization and is an indispensable asset. Describing this large amount of knowledge, sharing a common understanding of it and reusing other domain-specific knowledge has become possible with the introduction of ontologies. Applying ontologies in information exchange and integration is becoming a common trend and a potential solution to the interoperability problem. Consequently, managing these ontologies from storage and maintenance till query processing and retrieval of ontological information has become a daunting task, and a what is now known as ontology management systems have been brought into our attention to tackle this problem. However, current ontology management systems lack the appropriate means to deal with the booming increase in information and face a serious scalability problem. Thus, a database-centric approach is introduced, which offers the storage of ontological data into relational databases. This approach might solve the scalability problem; nevertheless, databases are not yet optimised for such an application and new ways of utilizing databases for such a solution have to be investigated. Through out my research I plan to study a range of methods and techniques, like query optimisation and hybrid approaches to storage of ontological data, to enhance the database-centric approach. Eventually, this research will be concluded by a best-practice study for exploiting these techniques to improve the efficiency of ontology management systems.

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