NFDI4Ing: Tools and Competencies in Dealing with FAIR Research Data for Researchers and Students




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Research in the engineering sciences is becoming increasingly data-driven. The need for corresponding IT offerings is growing. The associated skills for researchers and students must be developed and nurtured. 

  Presentation of the NFDI4Ing offer Copyright: © WZL NFDI4Ing Offerings and Their Link to Lectures at WZL of RWTH Aachen University

Data is becoming increasingly important in engineering research. The collection, refinement and publication of new data as well as the reuse of existing data create the need for corresponding IT services and make the prudent handling of research data an essential core competence of researchers. This is where NFDI4Ing (National Research Data Infrastructure for Engineering Sciences), a consortium of engineering institutions from all over Germany, is creating appropriate opportunities. All engineering disciplines are represented in five Community Clusters (CC) according to the subject classification system of the German Research Foundation (DFG). In addition, research is viewed from the perspective of applied research methodology: The collection of field data has different requirements than high-performance computing, which in turn differs from the development of research software. To identify requirements, seven so-called Archetypes exist as prototypical research characters, each representing a research methodology with its own challenges and approaches. NFDI4Ing's structure is supplemented by Base Services, which provide basic services for the engineering sciences regardless of research discipline or methodology.

After the first half of the current NFDI4Ing project period, it is worth to look at how NFDI4Ing promotes skills and cultural change in the handling of research data in engineering sciences. NFDI4Ing offers the opportunity to exchange ideas, network, and obtain information: The NFDI4Ing conference takes place annually with national and international contributions. Experts meet regularly in Special Interest Groups to exchange ideas, e.g. monthly regarding research data management (RDM). Specifically for mechanical engineering and production technology, the Community Cluster CC41 will provide information on current developments in RDM at its Community Meeting on July 25, 2024. Moreover, ing.grid is a journal for the open access publication of manuscripts, data and software.

"The management of FAIR research data is the most important building block for the science of tomorrow. For us, this building block belongs to the research foundation: The curricular integration of research data management yields a head start for students at WZL of RWTH Aachen University at a very early stage of their scientific career."

Prof. Dr.-Ing. Robert Schmitt, Director and Chairholder at WZL of RWTH Aachen University and Spokesperson for the NFDI4Ing Consortium

While NFDI4Ing primarily addresses researchers with its diverse offerings, the WZL of RWTH Aachen University starts teaching data skills at an way earlier stage: Bachelor's and Master's students from mechanical engineering and related subjects are introduced to various research methodologies and their suitability for complex problems and issues in the courses "Communication and Organisation Development (COD)" and "Research Methodology and Research Data Management (Re²)". In particular, this includes a learning unit on dealing with personally collected or reused research data. In group projects, students apply what they have learned in practice by methodically analyzing a given problem and generating solution approaches as well as systematically investigating these using selected research methods. In addition to traditional literature research, this also includes the development and implementation of data collection and evaluation. Students acquire important skills in presenting and publishing research data and results by showcasing several interim reports and writing a term paper with a focus on the responsible handling of research data, for example when planning the research project (data management plan, DMP) and taking the FAIR principles into account: Data must be
I-interoperable and

The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.