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Knowledge Graphs for Semantically Integrating Cyber-Physical Systems

: Grangel-Gonzalez, Irlan; Halilaj, Lavdim; Vidal, Maria-Esther; Rana, Omar; Lohmann, Steffen; Auer, Soeren; Mueller, Andreas W.


Hartmann, S.:
Database and Expert Systems Applications. 29th International Conference, DEXA 2018 : Regensburg, Germany, September 3-6, 2018, Proceedings, Part I
Cham: Springer International Publishing, 2018 (Lecture Notes in Computer Science 11029)
ISBN: 978-3-319-98808-5
ISBN: 978-3-319-98809-2
ISBN: 978-3-319-98810-8
International Conference on Database and Expert Systems Applications (DEXA) <29, 2018, Regensburg>
Bundesministerium für Bildung und Forschung BMBF
01IS17031; Industrial Data Space Plus
Conference Paper
Fraunhofer IAIS ()

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 a nd 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.