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A Core Ontology of Macroscopic Stuff

  • Conference paper
Knowledge Engineering and Knowledge Management (EKAW 2014)

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

Abstract

Domain ontologies contain representations of types of stuff (matter, mass, or substance), such as milk, alcohol, and mud, which are represented in a myriad of ways that are neither compatible with each other nor do they follow a structured approach within the domain ontology. Foundational ontologies and Ontology distinguish between pure stuff and mixtures only, if it contains stuff. We aim to fill this gap between foundational and domain ontologies by applying the notion of a ‘bridging’ core ontology, being an ontology of categories of stuff that is formalised in OWL. This core ontology both refines the DOLCE and BFO foundational ontologies and resolves the main type of interoperability issues with stuffs in domain ontologies, thereby also contributing to better ontology quality. Modelling guidelines are provided to facilitate the Stuff Ontology’s use.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Cape Town, South Africa

    C. Maria Keet

Authors
  1. C. Maria Keet
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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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Keet, C.M. (2014). A Core Ontology of Macroscopic Stuff. 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_17

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  • DOI: https://doi.org/10.1007/978-3-319-13704-9_17

  • 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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