SciKGTeX enables authors to create “FAIR-by-Design” publications by enriching them with FAIR information once and in parallel to the time of creation. This information is embedded into the PDF’s XMP metadata for persistent and long-term availability.
You want to document your engineering workflows from simulations or post-processing on HPC systems in a controlled vocabulary? You want to contribute to our user-based ontology development? Then please try out our alpha-release and share your needs and feedback in the NFDI4Ing GitLab platform.
NFDI4Ing conducted its second community survey on the topic of research data management (RDM) in the engineering sciences. The findings will help tailor the consortium’s services precisely to the needs of engineers. Counting on your support, the third survey has just started.
Image: “Research Data Diversity” by Heinz-Vale, CC BY-SA 4.0
In this Workshop, Prof. Pelz provides examples of how data literacy is integrated into the Mechanical Engineering – Sustainable Engineering bachelor’s degree program at Darmstadt University of Technology. Read more…
The Call for Applications for the 2024 round of NFDI4Ing Seed Funds has been released!
The next regular meeting of the NFDI4Ing special interest group quality assurance and metrics for FAIR data (QA & metrics) will be on September 8th, from 9 AM to 11 AM. Read more…
The NFDI4Ing task area Doris designs transferable research data management concepts and tools for data from high-performance measurement and computation (HPMC).
Discover ing.grid, the journal for FAIR data management in engineering sciences.
We cordially invite you to this year’s NFDI4Ing Conference 2023 on 27th and 28th September 2023!
We’re excited to introduce SOFIRpy, a Python package that lets you co-simulate functional mock-up units (FMUs) with custom models.