Data management plans are an important component of data management. One of the goals of the NFDI4Ing Base Service Quality Assurance in RDM processes and metrics for FAIR data (S-1) is to provide an engineering-specific customized Data Management Plan (DMP) template to support engineers.
The NFDI4Ing Base Service Research Software Development (S-2) provides infrastructure, best practices and templates to make research software and its development more replicable and reproducible while improving the quality of the written code.
On May 20th, the University of Bremen hosts a networking event for “NFDI consortia in the Bremer RDM ecosystem”. Read more…
The RDA/RDMinEng IG is hosting an e-seminar series on Laboratory Information Management Systems (LIMS) and Electronic Laboratory Notebooks (ELNs). The first talk is on May 5th, 5PM. Read more…
The first official meeting of the section as part of the NFDI e.V. will take place on Tuesday, May 3rd, starting at 11 AM. Read more…
The next NFDI4Ing onboarding event for new members will be delayed by a month. The new date is April 27th, 2022, starting at 09:00 PM. Read more…
The next general meeting of the special interest group (SIG) quality assurance & metrics will be on April 8th, 2022, from 9 a.m. to 11:00 a.m.. Read more…
The NFDI4Ing workshop for Research Data Management in High Performance Computing & Measurement is taking place on Wednesday, April 06, 2022 from 1 pm to 4 pm – free and open to all. Read more…
Together with the NFDI Task Force Tools for AAI and the FAIR Data Spaces project, we conducted a survey to assess the current state of AAI technologies in the NFDI. The results are now available and will be used to shape the future architecture of AAI for the „one NFDI”.
How can large data from high-performance measurement and computation (HPMC) become accessible for the research community? How can this data be processed or transferred? What are the possibilities for storage, repositories and metadata enrichment? DORIS has made a considerable progress in implementing the FAIR principles of HPMC data and passing the evolved knowledge to the community.
