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Storing massive Resource Description Framework (RDF) data: a survey

Published online by Cambridge University Press:  07 December 2016

Zongmin Ma ,
Miriam A. M. Capretz  and
Li Yan
Zongmin Ma
Affiliation:
College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: zongmin_ma@yahoo.com Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China e-mail: yanli@nuaa.edu.cn
Miriam A. M. Capretz
Affiliation:
Department of Electrical and Computer Engineering, Western University, London, Canada, ON N6A 5B9 e-mail: mcapretz@uwo.ca
Li Yan
Affiliation:
College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China e-mail: zongmin_ma@yahoo.com Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China e-mail: yanli@nuaa.edu.cn
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Abstract

The Resource Description Framework (RDF) is a flexible model for representing information about resources on the Web. As a W3C (World Wide Web Consortium) Recommendation, RDF has rapidly gained popularity. With the widespread acceptance of RDF on the Web and in the enterprise, a huge amount of RDF data is being proliferated and becoming available. Efficient and scalable management of RDF data is therefore of increasing importance. RDF data management has attracted attention in the database and Semantic Web communities. Much work has been devoted to proposing different solutions to store RDF data efficiently. This paper focusses on using relational databases and NoSQL (for ‘not only SQL (Structured Query Language)’) databases to store massive RDF data. A full up-to-date overview of the current state of the art in RDF data storage is provided in the paper.

Type
Survey Article
Information
The Knowledge Engineering Review , Volume 31 , Special Issue 4: Spatial Computing , September 2016 , pp. 391 - 413
Copyright
© Cambridge University Press, 2016 

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