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Querying RDF Data: A Multigraph Based Approach

Vijay Ingalalli 1 Dino Ienco 2, 1 Pascal Poncelet 1 
1 ADVANSE - ADVanced Analytics for data SciencE
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Resource description framework (RDF) data are cherished and exploited by various domains such as life sciences, Semantic Web and social networks. This chapter provides basic definitions on the interplay between RDF and its multigraph representation. The multigraph representation enables to construct lightweight indexing structures that ameliorate the time performance of Attributed Multigraph Based Engine for RDF querying (AMbER). The chapter discusses a graph‐based RDF querying engine, AMbER, which involves two steps. The first step is an offline step, where RDF data are transformed into multigraph and are indexed. The second step is an online step, where an efficient approach to answer a SPARQL query is proposed. The proposed engine AMbER has been tested over large RDF triplestores. The chapter focuses on the SELECT/WHERE clause of the SPARQL language, which constitutes the most important operation of any RDF query engine.
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Submitted on : Thursday, November 1, 2018 - 5:03:28 PM
Last modification on : Friday, August 5, 2022 - 3:02:49 PM
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Vijay Ingalalli, Dino Ienco, Pascal Poncelet. Querying RDF Data: A Multigraph Based Approach. Olivier Pivert. NoSQL Data Models • Trends and Challenges, 1, ISTE–WILEY, 2018, Base de données et Big Data • Databases and Big Data, 9781786303646. ⟨10.1002/9781119528227.ch5⟩. ⟨lirmm-01910660⟩



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