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Encyclopedia of Big Data Technologies pp 1–8Cite as

Ontologies for Big Data

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Synonyms

Classically, in AI, ontologies were considered a form of knowledge representation and frequently denoted knowledge models. More recent near-synonyms include the term vocabulary, which is usually used for inexpressive ontologies on the Web that are used as vocabularies for online datasets. Even more recently the term knowledge graph has gained increased popularity. It can be viewed as a more general term, since a knowledge graph does not necessarily have to be an ontology; however, most ontologies could be considered to be knowledge graphs.

Overview

This chapter introduces the concept of ontology, in the context of computer science and in particular Big Data. First, some terminology is introduced and the concept is defined. Further, some background and history of ontologies in computer science is presented. Next, common representation formats and standards are introduced, followed by a discussion on methods for constructing, finding, and reusing ontologies. The chapter is...

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Authors and Affiliations

  1. Linköping University, Linköping, Sweden

    Eva Blomqvist

Authors
  1. Eva Blomqvist
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Corresponding author

Correspondence to Eva Blomqvist .

Editor information

Editors and Affiliations

  1. School of Comp. Sci. and Engineering, University of New South Wales School of Comp. Sci. and Engineering, Eveleigh, New South Wales, Australia

    Sherif Sakr

  2. Sch of Info Techno, Building J12, University of Sydney Sch of Info Techno, Building J12, Sydney, Australia

    Albert Zomaya

Section Editor information

  1. eXascale Infolab, University of Fribourg, Bd Perolles 90, 1700, Fribourg, Switzerland

    Philippe Cudré-Mauroux

  2. Linköping University http://olafhartig.de/

    Olaf Hartig PhD

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© 2018 Springer International Publishing AG

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Cite this entry

Blomqvist, E. (2018). Ontologies for Big Data. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_313-1

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  • DOI: https://doi.org/10.1007/978-3-319-63962-8_313-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63962-8

  • Online ISBN: 978-3-319-63962-8

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

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