TY - GEN
T1 - Cloud-based RDF data management
AU - Kaoudi, Zoi
AU - Manolescu, Ioana
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The W3C's Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: exible structure, optional schema, and rich, exible 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 distributed paradigm massively adopted in many applications for the scalability, faulttolerance 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.
AB - The W3C's Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: exible structure, optional schema, and rich, exible 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 distributed paradigm massively adopted in many applications for the scalability, faulttolerance 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.
UR - https://www.scopus.com/pages/publications/84904368990
U2 - 10.1145/2588555.2588891
DO - 10.1145/2588555.2588891
M3 - Conference contribution
AN - SCOPUS:84904368990
SN - 9781450323765
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
SP - 725
EP - 729
BT - SIGMOD 2014 - Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data
PB - Association for Computing Machinery
T2 - 2014 ACM SIGMOD International Conference on Management of Data, SIGMOD 2014
Y2 - 22 June 2014 through 27 June 2014
ER -