Details
| Original language | English |
|---|---|
| Title of host publication | Advances in System-Integrated Intelligence |
| Subtitle of host publication | Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy |
| Editors | Maurizio Valle, Dirk Lehmhus, Christian Gianoglio, Edoardo Ragusa, Lucia Seminara, Stefan Bosse, Ali Ibrahim, Klaus-Dieter Thoben |
| Place of Publication | Cham |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 205-214 |
| Number of pages | 10 |
| ISBN (electronic) | 978-3-031-16281-7 |
| ISBN (print) | 9783031162800 |
| Publication status | Published - 2023 |
| Event | 6th International Conference on System-Integrated Intelligence, SysInt 2022 - Genova, Italy Duration: 7 Sept 2022 → 9 Sept 2022 |
Publication series
| Name | Lecture Notes in Networks and Systems |
|---|---|
| Volume | 546 LNNS |
| ISSN (Print) | 2367-3370 |
| ISSN (electronic) | 2367-3389 |
Abstract
In engineering research, various sensors and data sources are utilized for data acquisition. Together with subsequent processing and analysis, a large, heterogeneous amount of data and information is generated. To structure data and information within the research project, intelligent tools for research data management (RDM) are required. However, existing tools for RDM focus on data management during a research project and lack of capabilities to describe a technical system over this life cycle in multiple projects. Thus this paper addresses the potential of the Digital Twin (DT) concept for RDM. Based on requirements from RDM we derive specifications for a DT concept in RDM and introduce three criteria to choose suitable technical systems for DT. We present a DT for a research vehicle, implemented within the open-source Industry 4.0 DT tool “AASX Package Explorer”, to show the benefits of using a DT for RDM.
Keywords
- Digital Twin, Field data, Research data management
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Computer Science(all)
- Computer Networks and Communications
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy. ed. / Maurizio Valle; Dirk Lehmhus; Christian Gianoglio; Edoardo Ragusa; Lucia Seminara; Stefan Bosse; Ali Ibrahim; Klaus-Dieter Thoben. Cham: Springer Science and Business Media Deutschland GmbH, 2023. p. 205-214 (Lecture Notes in Networks and Systems; Vol. 546 LNNS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Management of Research Field Data Within the Concept of Digital Twin
AU - Dierend, Hauke
AU - Altun, Osman
AU - Mozgova, Iryna
AU - Lachmayer, Roland
N1 - Funding Information: The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.
PY - 2023
Y1 - 2023
N2 - In engineering research, various sensors and data sources are utilized for data acquisition. Together with subsequent processing and analysis, a large, heterogeneous amount of data and information is generated. To structure data and information within the research project, intelligent tools for research data management (RDM) are required. However, existing tools for RDM focus on data management during a research project and lack of capabilities to describe a technical system over this life cycle in multiple projects. Thus this paper addresses the potential of the Digital Twin (DT) concept for RDM. Based on requirements from RDM we derive specifications for a DT concept in RDM and introduce three criteria to choose suitable technical systems for DT. We present a DT for a research vehicle, implemented within the open-source Industry 4.0 DT tool “AASX Package Explorer”, to show the benefits of using a DT for RDM.
AB - In engineering research, various sensors and data sources are utilized for data acquisition. Together with subsequent processing and analysis, a large, heterogeneous amount of data and information is generated. To structure data and information within the research project, intelligent tools for research data management (RDM) are required. However, existing tools for RDM focus on data management during a research project and lack of capabilities to describe a technical system over this life cycle in multiple projects. Thus this paper addresses the potential of the Digital Twin (DT) concept for RDM. Based on requirements from RDM we derive specifications for a DT concept in RDM and introduce three criteria to choose suitable technical systems for DT. We present a DT for a research vehicle, implemented within the open-source Industry 4.0 DT tool “AASX Package Explorer”, to show the benefits of using a DT for RDM.
KW - Digital Twin
KW - Field data
KW - Research data management
UR - http://www.scopus.com/inward/record.url?scp=85138004721&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-16281-7_20
DO - 10.1007/978-3-031-16281-7_20
M3 - Conference contribution
AN - SCOPUS:85138004721
SN - 9783031162800
T3 - Lecture Notes in Networks and Systems
SP - 205
EP - 214
BT - Advances in System-Integrated Intelligence
A2 - Valle, Maurizio
A2 - Lehmhus, Dirk
A2 - Gianoglio, Christian
A2 - Ragusa, Edoardo
A2 - Seminara, Lucia
A2 - Bosse, Stefan
A2 - Ibrahim, Ali
A2 - Thoben, Klaus-Dieter
PB - Springer Science and Business Media Deutschland GmbH
CY - Cham
T2 - 6th International Conference on System-Integrated Intelligence, SysInt 2022
Y2 - 7 September 2022 through 9 September 2022
ER -