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.

Discovering Critical Factors Affecting RDF Stores Success

Modoni GE;Sacco M
2021

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.
2021
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
Semantic database
RDF store
Semantic Web
Ontologies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/394971
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