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What Is Linked Historical Data?

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Knowledge Engineering and Knowledge Management (EKAW 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8876))

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Abstract

Datasets that represent historical sources are relative newcomers in the Linked Open Data (LOD) cloud. Following the standard LOD practices for publishing historical sources raises several questions: how can we distinguish between RDF graphs of primary and secondary sources? Should we treat archived and online RDF graphs differently in historical research? How do we deal with change and immutability of a triplified History? To answer these fundamental questions, we model historical primary and secondary sources using the OntoClean metaproperties and the theories of perdurance and endurance. We then use this model to give a definition of Linked Historical Data. We advocate a set of publishing practices for Linked Historical Data that preserve the ontological properties of historical sources.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, VU University Amsterdam, The Netherlands

    Albert Meroño-Peñuela & Rinke Hoekstra

  2. Data Archiving and Networked Services, KNAW, The Netherlands

    Albert Meroño-Peñuela

  3. Faculty of Law, University of Amsterdam, The Netherlands

    Rinke Hoekstra

Authors
  1. Albert Meroño-Peñuela
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  2. Rinke Hoekstra
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Editor information

Editors and Affiliations

  1. Department of Geography, University of California, Santa Barbara, CA, USA

    Krzysztof Janowicz

  2. Dept. of Computer Science, VU University Amsterdam, The Netherlands

    Stefan Schlobach

  3. University of Linköping, Sweden

    Patrick Lambrix

  4. Aalto University, Finland

    Eero Hyvönen

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© 2014 Springer International Publishing Switzerland

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Meroño-Peñuela, A., Hoekstra, R. (2014). What Is Linked Historical Data?. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds) Knowledge Engineering and Knowledge Management. EKAW 2014. Lecture Notes in Computer Science(), vol 8876. Springer, Cham. https://doi.org/10.1007/978-3-319-13704-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-13704-9_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13703-2

  • Online ISBN: 978-3-319-13704-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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