The base service “Quality assurance in RDM processes and metrics for FAIR data” in NFDI4Ing includes the support of data management plans with RDMO, the development of maturity models for research data management processes and the provision and maintenance of FAIR data metrics. The common goal is to ensure the quality of research data management in engineering research through each individual service.

By ordering the RDM activities based on their occurrence in the engineering research process, Jarves provides a structure for RDM in engineering. Based on the research’s boundaries, Jarves offers information on the next steps and available tools.

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

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!

This year’s meeting of the mechanical and industrial engineering community (CC-41) focuses on the application of data models. Guests from the field of production engineering

Betty is the NFDI4Ing task area covering the research data management challenges faced by engineers who develop their own software solutions. Betty envisions a future

Providing Research Data Management (RDM) support and education is a central goal of NFDI4Ing. Together, the Base Service measure S-6, the Community Cluster measure CC-2,

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 hard-to-access lab books and similar sources. This complicates and prolongs process optimization, especially when different printing and post-processing steps need to be combined for a specific application. The project ReCIPE aimed at setting up a tool for researchers and users of printed electronics that can grow into a broad open database on process parameters and connected outcomes for the wider academic and industry-based community.

Data processing is usually not a  single task, but in general relies on a chain of tools. To achieve transparency, adaptability, and reproducibility of (computational)

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 group “Standardisation” (CC-5) is looking for interested persons from the community to support the work and to get the implementation underway.

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 von Dienstleistungen zum Text und Data Mining” will take place on April 25th to address copyright issues in designing services to support text and data mining.

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 research data, developing reusable tools for processing that data and curating the data to make it findable, accessible, interoperable, and reusable (FAIR).

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 to improve our engagement processes.

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 from Edinburgh, Scotland. The awards were endowed with 500€ each, sponsored by the WZL Aachen Stiftung.

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.

The NFDI4Ing Task Area DORIS designs transferable research-data management concepts and tools for data from high-performance measurement and computation (HPMC), enables, and supports the community to apply these solutions. In order to standardize and facilitate RDM for our peer group, we provide support for the complete data life cycle.