Using Ontologies for Semantic Query Optimization of XML Database

As XML has gained prevalence in recent years, the management of XML compliant structured-document database has become a very interesting and compelling research area. Effective query optimization is crucial to obtaining good performance from an XML database given a declarative query specification because of the much enlarged optimization space. Query rewriting techniques based on semantic knowledge have been used in database management systems, namely for query optimization. The main goal of query optimization is to rewrite a user query into another one that uses less time and/or less resources during the execution. When using those query optimization strategies the transformed queries are equivalent to the submitted ones. This paper presents a new approach of query optimization using ontology semantics for query processing within XML database. In fact, our approach shows how ontologies can effectively be exploited to rewrite a user query into another one such that the new query provides equally meaningful results that satisfy the intention of the user. Based on practical examples and their usefulness we develop a set of rewriting rules. In addition, we prove that the results of the query rewriting are semantically correct by using a logical model.