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2016•Unpublished venueRequires access

Research issues in RDF management systems

Tanvi Chawla, Girdhari Singh, Emmanuel S. Pilli, Mahesh Chandra Govil

Open publisher page 11 citations

Abstract

Resource Description Framework (RDF) and SPARQL are some of the common terms we hear with the Semantic Web. RDF is the de-facto standard for data representation on the Semantic Web. The universal adoption of this standard can be attributed to the fact that it has a flexible model. Due to the widespread adoption of Semantic web, a sudden steep increase in the amount of RDF data has been witnessed. This massive volume of RDF data can't be handled by the traditional Centralized RDF management systems. Thus comes into the picture the need for Distributed RDF data management systems which can distribute this RDF data on a cluster of nodes. So, the bottlenecks of the Centralized RDF systems regarding volume and efficient querying can be overcome. This paper presents a detailed description and comparison of the different Centralized and Distributed RDF data management systems.

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What this paper is about

Resource Description Framework (RDF) and SPARQL are some of the common terms we hear with the Semantic Web. RDF is the de-facto standard for data representation on the Semantic Web. The universal adoption of this standard can be attributed to the fact that it has a flexible model. Due to the widespread adoption of Semantic web, a sudden steep increase in the amount of RDF data has been witnessed. This massive volume of RDF data can't be handled by the traditional Centralized RDF management systems. Thus comes into the picture the need for Distributed RDF data management systems which can distribute this RDF data on a cluster of nodes. So, the bottlenecks of the Centralized RDF systems regarding volume and efficient querying can be overcome. This paper presents a detailed description and comparison of the different Centralized and Distributed RDF data management systems.

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Available abstract

Resource Description Framework (RDF) and SPARQL are some of the common terms we hear with the Semantic Web. RDF is the de-facto standard for data representation on the Semantic Web. The universal adoption of this standard can be attributed to the fact that it has a flexible model. Due to the widespread adoption of Semantic web, a sudden steep increase in the amount of RDF data has been witnessed. This massive volume of RDF data can't be handled by the traditional Centralized RDF management systems. Thus comes into the picture the need for Distributed RDF data management systems which can distribute this RDF data on a cluster of nodes. So, the bottlenecks of the Centralized RDF systems regarding volume and efficient querying can be overcome. This paper presents a detailed description and comparison of the different Centralized and Distributed RDF data management systems.

Key concepts: SPARQL, RDF, RDF Schema, Cwm, RDF/XML, Simple Knowledge Organization System, Computer science, Linked data

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