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Skill Modelling for Digital Factories

  • D. ArenaEmail author
  • F. Ameri
  • D. Kiritsis
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 536)

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.

Keywords

Capability Skill modelling Ontology Digital factory 

Notes

Acknowledgement

This work was partially supported by the EU funded DILECO project (ID 785367).

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.École Polytechnique Fédérale de Lausanne (EPFL), SCI-STI-DK MELausanneSwitzerland
  2. 2.Department of Engineering TechnologyTexas State UniversitySan MarcosUSA

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