FAIR Metric for Engineering Sciences: Work results

Context NFDI4ING is the National Research Data Infrastructure for the Engineering Sciences, developing concepts and services for Research Data Management (RDM) in the Engineering Sciences in Germany. Within NFDI4ING, Special Interest Groups (SIGs) are a temporary format for exchange on a certain topic with interested experts from within and beyond NFDI4ING. In SIGs the members work together in an interactive way, although - in contrast to e.g. project work packages - it is not mandatory to create a certain result. Goal Goal of the SIG "Engineering FAIR Metric" is to develop a FAIR Metric for the Engineering Sciences. "FAIR" is the acronym for "Findable, Accessible, Interoperable, Reusable" by Wilkinson et al. (2016). Various developments in RDM, esp. in engineering sciences, will be brought together to give engineering researchers a guideline how to provide their data in a FAIR way. Due to the heterogeneity and diversity of the engineering sciences - the classification by the German DFG lists for the engineering sciences the subjects areas 41 Mechanical and Industrial Engineering, 42 Thermal Engineering / Process Engineering, 43 Material Science and Engineering, 44 Computer Science, Systems and Electrical Engineering, and 45 Construction Engineering and Architecture - a community-driven approach in the SIG format is chosen to collect input. Documents The SIG Engineering FAIR Metric started in October 2025 with the Kick-Off which can be found at 10.5281/zenodo.17618584. Meetings are conducted on a weekly basis. The progress is document in this upload, where each week is represented by a new version of the document. The versions are named with both version number 0.## and creation date.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-21
DOI
https://doi.org/10.5281/zenodo.17703666
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

FAIR Metric for Engineering Sciences: Work results

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

FAIR Metric for Engineering Sciences: Work results

article en

Abstract

Context NFDI4ING is the National Research Data Infrastructure for the Engineering Sciences, developing concepts and services for Research Data Management (RDM) in the Engineering Sciences in Germany. Within NFDI4ING, Special Interest Groups (SIGs) are a temporary format for exchange on a certain topic with interested experts from within and beyond NFDI4ING. In SIGs the members work together in an interactive way, although - in contrast to e.g. project work packages - it is not mandatory to create a certain result. Goal Goal of the SIG "Engineering FAIR Metric" is to develop a FAIR Metric for the Engineering Sciences. "FAIR" is the acronym for "Findable, Accessible, Interoperable, Reusable" by Wilkinson et al. (2016). Various developments in RDM, esp. in engineering sciences, will be brought together to give engineering researchers a guideline how to provide their data in a FAIR way. Due to the heterogeneity and diversity of the engineering sciences - the classification by the German DFG lists for the engineering sciences the subjects areas 41 Mechanical and Industrial Engineering, 42 Thermal Engineering / Process Engineering, 43 Material Science and Engineering, 44 Computer Science, Systems and Electrical Engineering, and 45 Construction Engineering and Architecture - a community-driven approach in the SIG format is chosen to collect input. Documents The SIG Engineering FAIR Metric started in October 2025 with the Kick-Off which can be found at 10.5281/zenodo.17618584. Meetings are conducted on a weekly basis. The progress is document in this upload, where each week is represented by a new version of the document. The versions are named with both version number 0.## and creation date.

Zenodo (CERN European Organization for Nuclear Research)
RWTH Aachen University (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Research Data Management Practices
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