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Skill Modelling for Digital Factories

Abstract : In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. Despite the presence of many databases for industrial skills and professions, a formal representation, namely, an ontology, which meets the requirements of an existing tool for skill and capability analysis called CaMDiF is missing. In this research, the MSDL ontology, used by the tool in its initial version, is extended by importing modules of upper level and mid level ontologies (BFO and Agent Ontology) and by developing a new ontology for industry skills and professions based on an existing non-ontological resource (O*NET). As a result, an overview of the enriched data structure is provided along with some discussions on a use case related to skill analysis enabled by the new CaMDiF’s skill modelling features.
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Damiano Arena, F. Ameri, Dimitris Kiritsis. Skill Modelling for Digital Factories. IFIP International Conference on Advances in Production Management Systems (APMS), Aug 2018, Seoul, South Korea. pp.318-326, ⟨10.1007/978-3-319-99707-0_40⟩. ⟨hal-02177838⟩

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