NFDI4Ing is running a community survey on the state of research data management (RDM) in the engineering sciences. One of the goals of the survey is to tailor the consortium’s services precisely to the needs of engineers. To obtain a detailed picture of the state of RDM in the individual engineering disciplines, we hope for numerous participants from all fields of engineering.
Analysing large collections of documents using text-and-data-mining methods can yield entirely new scientific insights. In the NFDI4Ing task area Automated data and knowledge discovery in engineering literature (S-7), services are developed to enable researchers to more easily apply these innovative methods in practice.
In NFDI4Ing, we develop engineering-specific RDM trainings and educational material and make them publicly available. Learn more about the formats, contents, and our platform.
Field experiments are characterized by environmental conditions that cannot be fully controlled by the experimenter. Examples for field experiments include testing driver assistance systems in traffic, submarine robots in open water, or monitoring traffic in cities. Task Area GOLO is developing services and solutions to support engineers conducting field experiments in their work.
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.
