Triples in the clouds

Zoi Kaoudi, Ioana Manolescu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The W3C's Resource Description Framework (or RDF, in short) is a promising candidate which may 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. Many RDF data collections are being published, going from scientific data to general-purpose ontologies to open government data, in particular in 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 discusses the problems involved in efficiently handling 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.

Original languageEnglish
Title of host publicationICDE 2013 - 29th International Conference on Data Engineering
Pages1258-1261
Number of pages4
DOIs
Publication statusPublished - 15 Aug 2013
Externally publishedYes
Event29th International Conference on Data Engineering, ICDE 2013 - Brisbane, QLD, Australia
Duration: 8 Apr 201311 Apr 2013

Other

Other29th International Conference on Data Engineering, ICDE 2013
CountryAustralia
CityBrisbane, QLD
Period8/4/1311/4/13

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Kaoudi, Z., & Manolescu, I. (2013). Triples in the clouds. In ICDE 2013 - 29th International Conference on Data Engineering (pp. 1258-1261). [6544918] https://doi.org/10.1109/ICDE.2013.6544918