Enabling Exploratory Search on Manufacturing Knowledge Graphs

Kevin Haller*, Fajar J. Ekaputra, Marta Sabou, Fiorina Piroi

*Corresponding author for this work

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

Abstract

Knowledge graphs have been recognized in manufacturing as a suitable technology for integration of multidisciplinary knowledge from heterogeneous data sources. The effective reuse of this knowledge can better inform stakeholders in their decision making processes and consequently, establish a competitive advantage. In contrast to the utilization of knowledge graphs for autonomous decision making systems, less attention in production research has been given to the creative participation of humans in the exploration of manufacturing knowledge graphs. Exploratory search systems are a promising solution to facilitate this participation. However, most exploratory search systems focus on general knowledge graphs for which common knowledge is sufficient. We argue that within the complex environment of manufacturing, closer attention has to be paid to particular exploratory search features. In this paper, we therefore present a configurable and adaptive exploratory search system, which implements three special features. Firstly, adaptability of the system to multiple (engineering) perspectives. Secondly, visibility of provenance details about statements to simplify investigative work. And finally, a tree view for browsing deep hierarchical structures.

Original languageEnglish
Title of host publicationProceedings of the Seventh International Workshop on the Visualization and Interaction for Ontologies and Linked Data
Subtitle of host publicationco-located with the 21st International Semantic Web Conference (ISWC 2022)
EditorsBo Fu, Patrick Lambrix, Catia Pesquita
Place of PublicationAachen
PublisherCEUR WS
Pages16-28
Number of pages13
Volume3253
Publication statusPublished - 2022
Event7th International Workshop on the Visualization and Interaction for Ontologies and Linked Data, VOILA! 2022 - Virtual, Hangzhou, China
Duration: 23 Oct 2022 → …

Publication series

SeriesCEUR Workshop Proceedings
Volume3253
ISSN1613-0073

Conference

Conference7th International Workshop on the Visualization and Interaction for Ontologies and Linked Data, VOILA! 2022
Country/TerritoryChina
CityVirtual, Hangzhou
Period23/10/22 → …

Bibliographical note

Funding Information:
This work is supported by European Union's Horizon 2020 research project OntoTrans under Grant Agreement No 862136.

Publisher Copyright:
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

urn:nbn:de:0074-3253-0

Keywords

  • exploratory search
  • industry 4.0
  • knowledge graph

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