As part of the Master’s program in Neurosciences the Data Science Center (DSC) organized a teaching session on research data management and FAIR data on April 7, 2025. The program has a particularly interdisciplinary focus and is jointly offered by the departments of Physics/Electrical Engineering, Biology/Chemistry, Mathematics/Computer Science, and Human and Health Sciences.
The teaching session was led by Annika Nolte, a data scientist at the DSC, as part of the BMFTR-funded DataNord Data Competence Center. Under the title “A Tale of FAIR Data – Or How to Gain Knowledge From Your Research Data,” students received a practical introduction to key questions in data-intensive research: What is research data? Why does data need context? How can data be effectively organized, documented, stored, and reused? And what role do the FAIR principles play in ensuring transparent and responsible research?
Foster Data Literacy Early On
Especially in an interdisciplinary program like neuroscience, students begin working with different types of data, methods, and disciplinary perspectives early on. A fundamental understanding of research data management is therefore not only relevant for future research projects but is also an important component of good scientific practice even during their studies.
The course combined brief presentations with interactive exercises and concrete examples from data-intensive research. This allowed students to directly apply key concepts - such as the research data lifecycle, metadata, data management plans, and FAIR data - to their own research and academic contexts.
For the DSC and DataNord, this format exemplifies how data literacy can be integrated into teaching in an accessible and discipline-specific manner. The materials and training concepts developed at the DSC can be flexibly adapted to target groups and degree programs - from doctoral candidates and research consortia to students at the beginning of their academic careers.
Interested in a similar format?
If you’d like to integrate data literacy, research data management, or data science more deeply into your course, module, or degree program, please feel free to contact our coordinator, Dr. Lena Steinmann. For further inspiration, take a look at our training portfolio to date.
Related links:
More about the M.Sc. in Neurosciences: https://www.uni-bremen.de/en/mscneuro
An overview of our training portfolio: https://www.uni-bremen.de/en/data-science-center/trainings-services/trainings-works
More about DataNord: https://www.bremen-research.de/en/datanord
If you have any further questions, please contact:
Annika Nolte
Tel. +49 (421) 218 59856
E-Mail:anolteuniprotect me ?!bremenprotect me ?!.de
Sarah Büker
Tel. +49 (421) 218 59855
E-Mail: sbuekeruniprotect me ?!bremenprotect me ?!.de
