FAIR data management in the engineering sciences

The international and interdisciplinary specialist journal ing.grid, which was established in late 2022 by the Technical University of Darmstadt within the framework of the NFDI consortium NFDI4Ing (NFDI stands for National Research Data Infrastructure), is providing knowledge, methods, and tools to engineers and experts in data infrastructure in order to manage research data according to the FAIR principles, i.e., the data are intended to become “findable”, “accessible”, “interoperable”, and “reusable”.

“One year after the launch, ing.grid has established itself as an innovative publication, information, and discussion platform that will advance sustainable data management in the engineering sciences,” says Professor Bernd Flemisch from the Institute for Modelling Hydraulic and Environmental Systems at the University of Stuttgart. “Researchers from the University of Stuttgart can also obtain information here and, in cooperation with IT departments and libraries, use their own publications to help make FAIR data management easier and faster to implement in the future.”

The aim of the ing.grid specialist journal is to publish articles on the topics of data competence, data management, data infrastructure, data economy, and data ethics in the engineering sciences and put them up for discussion. In doing so, it brings together different disciplines and establishes ties between researchers and experts from the science-supporting infrastructure sector. Both groups are also represented in the editorial team. In addition, the submitted publications go through a transparent open peer review process. This means that the reviews are freely accessible and documented for both the submitters and the reviewers.

In October 2023, Flemisch and his cooperation partners also successfully placed a publication on the subject of “Evaluation of tools for describing, reproducing and reusing scientific workflows” in the ing.grid specialist journal for the first time. This article examines a selection of tools for the definition, execution, and reuse of digital workflows with regard to their suitability for engineering science problems. Based on a number of evaluation criteria, researchers should be able to select the best tool for their specific requirements.