Data literacy from the very beginning! Thus, the EduTrain section emphasizes the relevance of building data literacy in all areas of research and higher education teaching and opens a path to cross-disciplinary sustainability of research data management (FDM) and the development of a contemporary data culture.

“Data literacy from the start” has become a paradigm for comprehensive digital – transformation processes. These span the

• Further development of scientific methods and good scientific practice.
• Establishing and enhancing data quality as a resource for value-added knowledge gain and sustainable solutions to societal challenges.
• Developing a better understanding of data for more efficient, sustainable, and cross-disciplinary reuse.

An important prerequisite for this is adherence to the “FAIR” principles” and ensuring accessibility, transparency, and re-usability in both open and protected data spaces at both national and European levels.

The coordinated, user-oriented and tailored teaching of data literacy is of great importance for the competitiveness of Germany as a location for science and research. In the EduTrain section, actors from university teaching and research, libraries and computing centers, as well as from non-university research institutes and state initiatives, therefore work closely together to promote the cultural shift to FAIR data. Following Ridsdale et al. 2015, this includes training and strengthening the “capacity to collect, manage, evaluate, and apply data in critical ways.”

The work in the section is based on three pillars:

• Active dialogue and regular exchange with all NFDI consortia.
• Development of an overall framework for needs-based and target group-specific modules based on a modular and scalable training concept.
• Quality assurance through standardization, community building and didactic enhancement of offerings and materials.
• Establishment of an error culture in all branches of science.

Working groups

The responsible for the working groups meet regularly in a virtual format, the EduTrainExpress.

WP1: Target group and needs analysis

Contact: Britta Petersen, Sonja Herres-Pawlis, Peter F. Pelz

WP2: Inventory of materials

Contact: Peter F. Pelz, Sonja Herres-Pawlis

WP3: Development of a modular and scalable concept

Contact: Timo Mühlhaus, Kerstin Helbig

WP4: Development of joint multidimensional teaching materials and building a Knowledge Base

Contact: Kai-Christian Bruhn, Johannes Liermann, Peter F. Pelz

WP5: Training formats and certificate course

Contact: Konrad Förstner, Birte Lindstädt, Anja Perry

WP6: Quality assurance and evaluation 

together with WP4

WP7: Networking and Outreach

Contact: Jana Neumann, Kerstin Helbig, Sonja Herres-Pawlis

WP8: Error culture in science

Contact: John D. Joliffe  

Links and Useful Information

• https://dini.de/ag/dininestor-ag-forschungsdaten/
• https://www.forschungsdaten.org/index.php/UAG_Schulungen/Fortbildungen
• Materialsammlung zu Schulungen im Forschungsdatenmanagement (DINI/nestor UAG Schulungen/Fortbildungen) 
• https://forschungsdaten.info/ or https://forschungsdaten.info/praxis-kompakt/tutorials-kurse-und-anleitungen/ 
• https://datacarpentry.org/ 
• https://www.go-fair.org/ 
• https://zenodo.org/communities/dcc-rdm-training-materials/?page=1&size=20
• https://eudat.eu/

Deputy Speaker: Prof. Dr. Sonja Herres-Pawlis 

(RWTH Aachen)