A Method for Converting Current Data to RDF in the Era of Industry 4.0

  • Marlène HildebrandEmail author
  • Ioannis Tourkogiorgis
  • Foivos Psarommatis
  • Damiano Arena
  • Dimitris Kiritsis
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 566)


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. With the rise of Industry 4.0, the data produced on assembly lines within factories is becoming particularly interesting to leverage precious information. However, adding semantics to data that already exists remains a challenging process. Most manufacturing assembly lines predate the outbreak of graph data, or have adopted other data format standards, and the data they produce is therefore difficult to automatically map to RDF. This has been a topic of research an ongoing technical issue for almost a decade, and if certain mapping approaches and mapping languages have been developed, they are difficult to use for an automatic, large-scale data conversion and are not standardized. In this research, a technical approach for converting existing data to semantics has been developed. This paper presents an overview of this approach, as well as two concrete tools that we have built based on it. The results of these tools are discussed as well as recommendations for future research.


Ontology Zero-defect manufacturing Data integration RDF Semantics JSON 



The work presented in this paper is partially supported by the project Z-Factor which is funded by the European Union’s Horizon 2020 program under grant agreement No 723906.


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Marlène Hildebrand
    • 1
    Email author
  • Ioannis Tourkogiorgis
    • 1
  • Foivos Psarommatis
    • 1
  • Damiano Arena
    • 1
  • Dimitris Kiritsis
    • 1
  1. 1.École polytechnique fédérale de Lausanne, ICT for Sustainable Manufacturing, EPFL SCI-STI-DKLausanneSwitzerland

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