NFDI4Ing is yielding results, and these and the documentation of our work want to be organized. But what can FAIR data management look like for research data management work? Maybe like this.
In the NFDI4Ing Base Service S-4, the Karlsruhe Institute of Technology, RWTH Aachen University, Technical University of Darmstadt and University of Stuttgart are working together on curating, facilitating and improving access to research data repositories and storage systems for engineers.
Many researchers struggle with the complexity of RDM. The NFDI4Ing Task Area Frank aims to simplify RDM for researchers by supporting them with needed RDM knowledge, specific decision support along the RDM process and tooltips for their current RDM-step.
We are delighted to invite everyone interested in the current status and future outlook of research data management in engineering science to the 2nd annual NFDI4Ing conference taking place on October 26 & 27, 2022.
SciMesh is Caden’s RDF graph topology to map scientific results onto a knowledge graph. In Caden, we use SciMesh as a standard to map content of an ELN to a data format that can be read by other ELNs. An unsolved problem has been how to deal with processes that involve more than one specimen, or with subprocesses. We addressed this problem by adding so-called “concurrents” to SciMesh.
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.
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.
ing.grid is a peer-reviewed open access journal currently in development, that provides a forum for engineers of all disciplines concerned with data management to share and exchange their knowledge.
