Cloud-based RDF data management

Zoi Kaoudi 1 Ioana Manolescu 2, 3
3 OAK - Database optimizations and architectures for complex large data
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : The W3C's Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: flexible structure, optional schema, and rich, flexible URIs as a basis for information sharing. Moreover, RDF is uniquely positioned to benefit from the efforts of scientific communities studying databases, knowledge representation , and Web technologies. As a consequence, numerous collections of RDF data are published, going from scientific data to general-purpose ontologies to open government data, in particular published as part of the Linked Data movement. Managing such large volumes of RDF data is challenging, due to the sheer size, the heterogeneity, and the further complexity brought by RDF reasoning. To tackle the size challenge , distributed storage architectures are required. Cloud computing is an emerging paradigm massively adopted in many applications for the scalability, fault-tolerance and elasticity features it provides. This tutorial presents the challenges faced in order to efficiently handle massive amounts of RDF data in a cloud environment. We provide the necessary background, analyze and classify existing solutions, and discuss open problems and perspectives.
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Zoi Kaoudi, Ioana Manolescu. Cloud-based RDF data management. ACM SIGMOD, Jun 2014, Snowbird, United States. ⟨10.1145/2588555.2588891⟩. ⟨hal-01187855⟩

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