Advertisement

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)

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. 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.

Keywords

Ontology Zero-defect manufacturing Data integration RDF Semantics JSON 

Notes

Acknowledgments

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.

References

  1. 1.
    Verscheure, O., Kiritsis, D.: The Meaning of Data. WMF Report (2018)Google Scholar
  2. 2.
    Martinez Lastra, J.L., Delamer, I.M.: Semantic web services in factory automation: fundamental insights and research roadmap (2006)CrossRefGoogle Scholar
  3. 3.
    Iarovyi, S., Mohammed, W.M., Lobov, A., Ferrer, B.R., Martinez Lastra, J.L.: Cyber–physical systems for open-knowledge-driven manufacturing execution systems (2016)Google Scholar
  4. 4.
    Kádár, B., Terkaj, W., Sacco, M.: Semantic Virtual Factory supporting interoperable modelling and evaluation of production systems (2013)CrossRefGoogle Scholar
  5. 5.
    Klyne, G., Carroll, J.J., McBride, B., Cyganiak, R., Wood, D., Lanthaler, M.: RDF 1.1 concepts and abstract syntax. World Wide Web Consortium (2004–2014). https://www.w3.org/TR/rdf11-concepts/
  6. 6.
    Sequeda, J.F., Arenas, M., Miranker, D.P.: On Directly Mapping Relational Databases to RDF and OWL (Extended Version) (2012)Google Scholar
  7. 7.
    Das, S., Sundara, S., Cyganiak, R.: R2RML: RDB to RDF mapping language. World Wide Web Consortium (2012). https://www.w3.org/TR/r2rml/
  8. 8.
    Sporny, M., Longley, D., Kellogg, G., Lanthale, M., Lindström, N.: JSON-LD 1.1: a JSON-based serialization for linked data. World Wide Wen Consortium (2018). https://www.w3.org/TR/json-ld11/
  9. 9.
    Dimou, A., Sande, M.V., Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: RML: a generic language for integrated RDF mappings of heterogeneous data (2014)Google Scholar
  10. 10.
    Connolly, D.: Gleaning resource descriptions from dialects of languages (GRDDL). World Wide Web Consortium (2007). https://www.w3.org/TR/grddl/
  11. 11.
    Bischof, S., Decker, S., Krennwallner, T., Lopes, N., Polleres, A.: Mapping between RDF and XML with XSPARQL (2012)Google Scholar

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

Personalised recommendations