Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

Katarina Milenković, Simon Mayer, Konrad Diwold, Josef Zehetner

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

Complex industrial processes produce a multitude of information during the product/service lifecycle. Those data are often stored, but rarely used in the context of overall process optimization, due to their unstructured format and the inability to integrate them with stored formal knowledge about the domain. This paper proposes a way to mitigate this problem, by extending the standard SPARQL query language to enable the integration of formal knowledge and unstructured data, as well as their joint processing. The paper constitutes an initial definition of the proposed SPARQL extension and demonstrates its applicability in the context of selected examples.
Original languageEnglish
Title of host publicationProceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy
ISBN (Electronic)978‐999‐54182‐0‐6
Publication statusPublished - 3 Jul 2019
Event2019 International Conference on Theory and Applications in the Knowledge Economy - Austria, Vienna, Austria
Duration: 3 Jul 20195 Jan 2020
https://www.take-conference2019.com/

Conference

Conference2019 International Conference on Theory and Applications in the Knowledge Economy
Abbreviated titleTAKE 2019
CountryAustria
CityVienna
Period3/07/195/01/20
Internet address

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Keywords

  • knowledge management
  • metadata
  • SPARQL
  • semantic web

Cite this

Milenković, K., Mayer, S., Diwold, K., & Zehetner, J. (2019). Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology. In Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy