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Graph Structures for Knowledge Representation and Reasoning pp 92–110Cite as

Inductive Triple Graphs: A Purely Functional Approach to Represent RDF

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8323))

Abstract

RDF is one of the cornerstones of the Semantic Web. It can be considered as a knowledge representation common language based on a graph model. In the functional programming community, inductive graphs have been proposed as a purely functional representation of graphs, which makes reasoning and concurrent programming simpler. In this paper, we propose a simplified representation of inductive graphs, called Inductive Triple Graphs, which can be used to represent RDF in a purely functional way. We show how to encode blank nodes using existential variables, and we describe two implementations of our approach in Haskell and Scala.

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Author information

Authors and Affiliations

  1. University of Oviedo, Spain

    Jose Emilio Labra Gayo

  2. Utrecht University, Open University of the Netherlands, The Netherlands

    Johan Jeuring

  3. South East European Research Center, Greece

    Jose María Álvarez Rodríguez

Authors
  1. Jose Emilio Labra Gayo
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  2. Johan Jeuring
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  3. Jose María Álvarez Rodríguez
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Editor information

Editors and Affiliations

  1. LIRMM, 161, rue ADA, 34392, Montpellier Cedex 5, France

    Madalina Croitoru

  2. Fakultät Informatik, Technische Universität Dresden, Nöthnitzer Str. 46, 01187, Dresden, Germany

    Sebastian Rudolph

  3. Institute of Information Systems, Vienna University of Technology, Austria

    Stefan Woltran

  4. Laboratoire d’Informatique de Paris 6 (LIP6/UPMC), Université Pierre et Marie Curie, 4, place Jussieu, 75005, Paris, France

    Christophe Gonzales

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© 2014 Springer International Publishing Switzerland

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Labra Gayo, J.E., Jeuring, J., Álvarez Rodríguez, J.M. (2014). Inductive Triple Graphs: A Purely Functional Approach to Represent RDF. In: Croitoru, M., Rudolph, S., Woltran, S., Gonzales, C. (eds) Graph Structures for Knowledge Representation and Reasoning. Lecture Notes in Computer Science(), vol 8323. Springer, Cham. https://doi.org/10.1007/978-3-319-04534-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-04534-4_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04533-7

  • Online ISBN: 978-3-319-04534-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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