Leading by Example: Data Literacy in the Physics Curricula
Lightning Talk
Michael Krieger1,2, Nina Owschimikow1,3, Christoph T. Koch1,4, and Heiko B. Weber1,2
1 FAIRmat Consortium, Humboldt-Universität zu Berlin
2 Department Physik, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
3 Institut für Physik und Astronomie, Technische Universität Berlin (TUB)
4 Department Physik, Humboldt-Universität zu Berlin (HUB)
Data literacy and digital research data management have become essential competencies in physics. Modern experiments, simulations, and data-driven methods produce increasingly large and complex datasets, while the growing use of artificial intelligence further increases the need for high-quality, well-documented, and reusable research data. The required competencies, however, are still rarely embedded systematically in physics curricula at universities.
The NFDI consortium FAIRmat has taken on this issue and has developed educational strategies in the physics curricula. At Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Technische Universität Berlin (TUB), and at Humboldt-Universität zu Berlin (HUB), basic programming skills are now taught in the first semester. This can be organized as 2-hour lecture, complemented by 2-hour hands-on exercises (FAU), as part of the first and fundamental physics course (HUB), or by modules on data analysis and data management (TUB).
While similar courses exist at other german physics departments as well, the Berlin/Erlangen approach takes up the programming skills for the lab courses, in which physics students perform experiments in several modules during both Bachelor and Master courses. There, Electronic Laboratory Notebooks instead of the classical pen and paper protocols give many opportunities to practice the programming skills in immediate relation to experimental data. Students learn to organize and evaluate data, elaborate protocols coherently in a digital way, they are experiencing the benefit of digitalization and explore the full lifecycle of data.
Other lecturers are acquiring these new skills and can now, building on a solid foundation, introduce further numerical content, data analysis or programming into their modules where appropriate. If we put “Ubiquitous emphasis on data”, the curricula may be transformed with very little formal changes. By experience, the acceptance by the students is very high.
These ideas have been expressed in a concept paper, supported by all three physics-related NFDI consortia, FAIRmat, PUNCH4NFDI and DAPHNE4NFDI, and have then been introduced to the Konferenz der Fachbereiche der Physik in May 2026. This is an informal body comprising physics departments in Germany, within which upcoming changes to teaching are discussed and where efforts are constantly made to find overarching solutions that are as uniform as possible. The discussion there has led to a strong support for the concept of “Ubiquitous emphasis on data”, which is now being discussed within the ~50 german physics departments.
[1] FAIRmat, PUNCH4NFDI, DAPHNE4NFDI, Burgard, C. D., Krieger, M.& Weber, H. B. (2026). Standardized Data Literacy and Research Data Management Competencies in the Physics Curriculum in Universities. Zenodo. https://doi.org/10.5281/zenodo.20850996