Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

Katarina Milenković; Simon Mayer; Konrad Diwold; Josef Zehetner

Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

Katarina Milenković, Simon Mayer, Konrad Diwold, Josef Zehetner

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

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.

Originalsprache	englisch
Titel	Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy
ISBN (elektronisch)	978‐999‐54182‐0‐6
Publikationsstatus	Veröffentlicht - 3 Juli 2019
Veranstaltung	2019 International Conference on Theory and Applications in the Knowledge Economy - Austria, Vienna, Österreich Dauer: 3 Juli 2019 → 5 Jan. 2020 https://www.take-conference2019.com/

Konferenz

Konferenz	2019 International Conference on Theory and Applications in the Knowledge Economy
Kurztitel	TAKE 2019
Land/Gebiet	Österreich
Ort	Vienna
Zeitraum	3/07/19 → 5/01/20
Internetadresse	https://www.take-conference2019.com/

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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. 2019 International Conference on Theory and Applications in the Knowledge Economy, Vienna, Österreich, 3/07/19. <https://www.alexandria.unisg.ch/257265/1/TAKE_2019_full_paper.pdf>

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title = "Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology",

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.",

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author = "Katarina Milenkovi{\'c} and Simon Mayer and Konrad Diwold and Josef Zehetner",

year = "2019",

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language = "English",

booktitle = "Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy",

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T1 - Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

AU - Milenković, Katarina

AU - Mayer, Simon

AU - Diwold, Konrad

AU - Zehetner, Josef

PY - 2019/7/3

Y1 - 2019/7/3

N2 - 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.

AB - 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.

KW - knowledge management

KW - metadata

KW - SPARQL

KW - semantic web

M3 - Conference paper

BT - Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy

T2 - 2019 International Conference on Theory and Applications in the Knowledge Economy

Y2 - 3 July 2019 through 5 January 2020

ER -

Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

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