Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

Item Type Conference or Workshop Item (Paper)
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.

Authors Milenkovic, Katarina; Mayer, Simon; Diwold, Konrad & Zehetner, Josef
Language English
Subjects computer science
HSG Classification contribution to scientific community
Date 3 July 2019
Title of Book Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy
ISSN 978‐999‐54182‐0‐6
Depositing User Prof. Dr. Simon Mayer
Date Deposited 03 Jul 2019 11:37
Last Modified 03 Jul 2019 11:37
URI: https://www.alexandria.unisg.ch/publications/257265

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Citation

Milenkovic, Katarina; Mayer, Simon; Diwold, Konrad & Zehetner, Josef: Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology. 2019.

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https://www.alexandria.unisg.ch/id/eprint/257265
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