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While experimental data and methods are commonly reported as “best outcome" figure of merits, the systematic process parameters (while being crucial for achieved outcome, in particular in combination and chains of different process steps) are often neglected or buried in
From its inception, members of NFDI4Ing have been working on a concept for the publication and organization of standards in the field of research data. By now, the concept is quite advanced and ready for the next step. The working
ield experiments mostly take place under difficult conditions. Due to the large number of sensors and computers, large amounts of data are usually generated, and data acquisition can be affected by small errors or external events. For further processing and
The recently published “Guidelines zum Text und Data Mining für Forschungszwecke in Deutschland” describe under which conditions text and data mining may be carried out for scientific purposes and what risks exist. An online workshop, “Urheberrechtliche Fragestellungen bei der Gestaltung
NFDI4Ing cordially invites you to participate with a contribution on this years conference! The motto of the NFDI4Ing conference 2023 is “Innovation in Research Data Management: Bridging the gaps between disciplines and opening new perspectives for research in engineering science”.
The international online journal ing.grid is now accepting submissions addressing FAIR data management in engineering sciences. With an open access policy, the journal bridges a gap in the field, offering a platform and recognition for sound scientific practice in generating
Getting and staying in touch with the community is the essence of NFDI4Ing. That’s why the consortium offers a broad variety of exchange formats like community meetings, conferences, and workshops. To meet the needs of the community, we continuously work
It was a close contest, but in the end two nominees prevailed in the NFDI4Ing Awards 2022 against 41 other contributors. We happily congratulate the winners, Wendy (Pengyin) Shan from the University of Alberta Library in Canada, and Rory Macneil
Virtually all scientific output is communicated through text publications, only suitable for humans and precluding searches beyond simple text matching. By contrast, SciMesh disseminates results as machine-actionable, comprehensive knowledge graphs.
