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Semantic Web Data Partitioning

Semantic Web Data Partitioning
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Author(s): Trupti Padiya (DA-IICT Gandhinagar, India), Minal Bhise (DA-IICT Gandhinagar, India) and Sanjay Chaudhary (DA-IICT Gandhinagar, India)
Copyright: 2013
Pages: 12
Source title: Advancing Information Management through Semantic Web Concepts and Ontologies
Source Author(s)/Editor(s): Patricia Ordóñez de Pablos (Universidad de Oviedo, Spain), Héctor Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina), Robert D. Tennyson (University of Minnesota, USA), Sandra Elizabeth Gonzalez Cisaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina) and Waldemar Karwowski (University of Central Florida, USA)
DOI: 10.4018/978-1-4666-2494-8.ch008

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Abstract

Semantic Web database is an RDF database due to increased use of Semantic Web in real life applications; one can find heavy growth in RDF database. As there is a tremendous increase in RDF data, performance and scalability issues are of main concern. This chapter discusses improving and scaling up query performance for increasingly growing Semantic Web. It discusses current Semantic Web data storage techniques, which have been found to scale poorly and have poor query performance. It discusses the partitioning techniques vertical and horizontal partitioning to improve query performance. To further improve the query performance, along with these partitioning techniques, various compression techniques can also be used. Relational data offers faster execution of queries as compared to RDF data. To demonstrate these ideas, semantic data is converted to relational data and then query performance improvement techniques are applied. The scaling up of Semantic Web data is also discussed.

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