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In this paper we identify the opportunities for the semantic transformation of XPath queries using the structural and explicit semantics defined in an XML schema. Our classification of transformation is the semantic path expression where a path can be semantically contracted, expanded or complemented. Among several applications of such transformations, an obvious one is the semantic optimization of XPath queries. The transformation is likely to result in an improved response time for a given system. We empirically evaluate the gain or loss of performance of the identified transformations with two representative off-the-shelf XML data management systems and XPath query processors.

In this paper, we propose a typology of the semantic transformations for XPath queries. We focus on two main areas. The first is structural transformation for XPath query, which can be semantically contracted, expanded or complemented using structural constraints. The second is semantic qualifier transformation where the predicates, specified by [ ], in an XPath query can be eliminated or transformed. We design a set of algorithms and implement a prototype system for evaluation. We adopt two representative off-the-shelf XML data management systems to validate the effectiveness of the semantic transformations. areas cover a wide range of advanced databases topics including XML databases, spatial and temporal databases and data warehousing, and semantic web and ontology. She is currently the Head of Data Engineering and Knowledge Management Laboratory at La Trobe University.Eric Pardede completed his Doctor of Philosophy in Computer Science and Master of Information Technology from La Trobe University. He has published his research works in various books, international journals and conference proceedings. Currently, he is a Lecturer in Software Engineering and Database

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This article proposes a data warehouse integration technique that combines data and documents from different underlying documents and database design approaches. The well-defined and structured data such as relational, object-oriented and object relational data, semi-structured data such as XML, and unstructured data such as HTML documents are integrated into a Web data warehouse system. The user specified requirements and data sources are combined to assist with the definitions of the hierarchical structures, which serve specific requirements and represent a certain type of data semantics using object-oriented features including inheritance, aggregation, association, and collection. A conceptual integrated data warehouse model is then specified based on a combination of user requirements and data source structure, which creates the need for a logical integrated data warehouse model. A case study is then developed into a prototype in a Web-based environment that enables the evaluation. The evaluation of the proposed integration Web data warehouse methodology includes the verification of correctness of the integrated data, and the overall benefits of utilizing this proposed integration technique.