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Knowledge Graphs for Semantically Integrating Cyber-Physical Systems

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Database and Expert Systems Applications (DEXA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11029))

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Abstract

Cyber-Physical Systems (CPSs) are engineered systems that result from the integration of both physical and computational components designed from different engineering perspectives (e.g., mechanical, electrical, and software). Standards related to Smart Manufacturing (e.g., AutomationML) are used to describe CPS components, as well as to facilitate their integration. Albeit expressive, smart manufacturing standards allow for the representation of the same features in various ways, thus hampering a fully integrated description of a CPS component. We tackle this integration problem of CPS components and propose an approach that captures the knowledge encoded in smart manufacturing standards to effectively describe CPSs. We devise SemCPS, a framework able to combine Probabilistic Soft Logic and Knowledge Graphs to semantically describe both a CPS and its components. We have empirically evaluated SemCPS on a benchmark of AutomationML documents describing CPS components from various perspectives. Results suggest that SemCPS enables not only the semantic integration of the descriptions of CPS components, but also allows for preserving the individual characterization of these components.

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Notes

  1. 1.

    https://github.com/i40-Tools/Related-Integration-Tools.

  2. 2.

    https://github.com/i40-Tools/CPSDocumentGenerator.

  3. 3.

    Source: Drath, GMA 6.16.

  4. 4.

    https://raw.githubusercontent.com/i40-Tools/iafCaseStudy/master/IAF_AMLModel_journal.aml.

  5. 5.

    https://github.com/i40-Tools/HeterogeneityExampleData/tree/master/AutomationML.

  6. 6.

    https://github.com/i40-Tools/SemCPS.

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Acknowledgements

This work has partly been supported by the German Federal Ministry of Education, Research (BMBF) in the context of the project Industrial Data Space Plus (grant no. 01IS17031), and EU H2020 Programme for the project BOOST 4.0 (grant no. 780732).

Author information

Authors and Affiliations

  1. Enterprise Information Systems (EIS), University of Bonn, Bonn, Germany

    Irlán Grangel-González, Lavdim Halilaj & Omar Rana

  2. Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany

    Irlán Grangel-González, Lavdim Halilaj & Steffen Lohmann

  3. L3S Research Center, Hanover, Germany

    Maria-Esther Vidal & Sören Auer

  4. TIB Leibniz Information Center for Science and Technology, Hanover, Germany

    Maria-Esther Vidal & Sören Auer

  5. Schaeffler Technologies, Herzogenaurach, Germany

    Andreas W. Müller

Authors
  1. Irlán Grangel-González
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  2. Lavdim Halilaj
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  3. Maria-Esther Vidal
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  4. Omar Rana
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  5. Steffen Lohmann
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  6. Sören Auer
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  7. Andreas W. Müller
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Correspondence to Irlán Grangel-González .

Editor information

Editors and Affiliations

  1. Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sven Hartmann

  2. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

  3. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  4. University of Regensburg, Regensburg, Germany

    Günther Pernul

  5. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Grangel-González, I. et al. (2018). Knowledge Graphs for Semantically Integrating Cyber-Physical Systems. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11029. Springer, Cham. https://doi.org/10.1007/978-3-319-98809-2_12

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  • DOI: https://doi.org/10.1007/978-3-319-98809-2_12

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