Details
| Original language | English |
|---|---|
| Title of host publication | The Semantic Web |
| Subtitle of host publication | 17th International Conference, ESWC 2020, Proceedings |
| Editors | Andreas Harth, Sabrina Kirrane, Axel-Cyrille Ngonga Ngomo, Heiko Paulheim, Anisa Rula, Anna Lisa Gentile, Peter Haase, Michael Cochez |
| Pages | 465-480 |
| Number of pages | 16 |
| Publication status | Published - 27 May 2020 |
| Externally published | Yes |
| Event | 17th Extended Semantic Web Conference, ESWC 2020 - Heraklion, Greece Duration: 31 May 2020 → 4 Jun 2020 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12123 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
One of the most crucial tasks for today’s knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches. For instance, the digital transformation of manufacturing systems, called Industry 4.0, currently faces an overwhelming amount of standardization efforts and reference initiatives, resulting in a sophisticated information environment. We propose a structured dataset in the form of a semantically annotated knowledge graph for Industry 4.0 related standards, norms and reference frameworks. The graph provides a Linked Data-conform collection of annotated, classified reference guidelines supporting newcomers and experts alike in understanding how to implement Industry 4.0 systems. We illustrate the suitability of the graph for various use cases, its already existing applications, present the maintenance process and evaluate its quality.
Keywords
- Industry 4.0, Knowledge graph, Knowledge representation, Standards
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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The Semantic Web: 17th International Conference, ESWC 2020, Proceedings. ed. / Andreas Harth; Sabrina Kirrane; Axel-Cyrille Ngonga Ngomo; Heiko Paulheim; Anisa Rula; Anna Lisa Gentile; Peter Haase; Michael Cochez. 2020. p. 465-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12123 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Knowledge Graph for Industry 4.0
AU - Bader, Sebastian R.
AU - Grangel-Gonzalez, Irlan
AU - Nanjappa, Priyanka
AU - Vidal, Maria Esther
AU - Maleshkova, Maria
N1 - Funding information: Acknowledgement. This work has been supported by the German Federal Ministry of Education and Research through the research project “Industrial Data Space Plus” (grant no. 01IS17031) and the EU H2020 project “BOOST4.0” (grant no. 780732).
PY - 2020/5/27
Y1 - 2020/5/27
N2 - One of the most crucial tasks for today’s knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches. For instance, the digital transformation of manufacturing systems, called Industry 4.0, currently faces an overwhelming amount of standardization efforts and reference initiatives, resulting in a sophisticated information environment. We propose a structured dataset in the form of a semantically annotated knowledge graph for Industry 4.0 related standards, norms and reference frameworks. The graph provides a Linked Data-conform collection of annotated, classified reference guidelines supporting newcomers and experts alike in understanding how to implement Industry 4.0 systems. We illustrate the suitability of the graph for various use cases, its already existing applications, present the maintenance process and evaluate its quality.
AB - One of the most crucial tasks for today’s knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches. For instance, the digital transformation of manufacturing systems, called Industry 4.0, currently faces an overwhelming amount of standardization efforts and reference initiatives, resulting in a sophisticated information environment. We propose a structured dataset in the form of a semantically annotated knowledge graph for Industry 4.0 related standards, norms and reference frameworks. The graph provides a Linked Data-conform collection of annotated, classified reference guidelines supporting newcomers and experts alike in understanding how to implement Industry 4.0 systems. We illustrate the suitability of the graph for various use cases, its already existing applications, present the maintenance process and evaluate its quality.
KW - Industry 4.0
KW - Knowledge graph
KW - Knowledge representation
KW - Standards
UR - http://www.scopus.com/inward/record.url?scp=85086139064&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-49461-2_27
DO - 10.1007/978-3-030-49461-2_27
M3 - Conference contribution
AN - SCOPUS:85086139064
SN - 9783030494605
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 465
EP - 480
BT - The Semantic Web
A2 - Harth, Andreas
A2 - Kirrane, Sabrina
A2 - Ngonga Ngomo, Axel-Cyrille
A2 - Paulheim, Heiko
A2 - Rula, Anisa
A2 - Gentile, Anna Lisa
A2 - Haase, Peter
A2 - Cochez, Michael
T2 - 17th Extended Semantic Web Conference, ESWC 2020
Y2 - 31 May 2020 through 4 June 2020
ER -