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Discovering Critical Factors Affecting RDF Stores Success

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Part of the Studies in Computational Intelligence book series (SCI, volume 941)

Abstract

Technologies for the effective and efficient handling of RDF data are one of the main success factors for a larger scale take-up of Semantic Web Technologies in real scenarios. In this regard, several software components (RDF Stores) devoted to the semantic data persistence and retrieval are available in literature. However, each of them may be appropriate and usable for some kinds of tasks and not for others, and a one-size-fits-all killer application for this type of solutions is still not (and probably will never be) available. The large number of available solutions and the lack of widely accepted benchmarks for their rigorous evaluation do not help the selection and the adoption of an appropriate RDF store compliant with the identified needs of a specific case study. In order to contribute to fill this gap, a methodological approach to evaluate and rank the relevant features of the RDF stores is presented in this paper. Such an approach can help on one hand other researchers to discover the factors affecting the success of the RDF stores and the other hand software architects to select which RDF stores best fits the requirements of a certain application scenario.

Notes

Acknowledgements

The present paper has been developed within CasAware project, approved by Lombardy region (id 147152) within the Call “Bando Linea RS per aggregazioni”.

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Authors and Affiliations

  1. 1.Institute of Intelligent Industrial Technologies and Systems for Advanced ManufacturingNational Research Council of ItalyBariItaly
  2. 2.Institute of Intelligent Industrial Technologies and Systems for Advanced ManufacturingNational Research Council of ItalyLeccoItaly

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