Curricular and subcurricular teaching of RDM in chemistry to reach the next generation

As we navigate an increasingly data-driven world, advanced skills in using digital tools are mandatory to survive in day-to-day life. This digitalization has also found its way into chemical research, where more and more electronic research data are being generated. Handling and management of the collected data has become a considerable part of every researcher's daily work. Scientists need to be trained in these topics and concepts to apply them successfully in their research processes. To have the ability to effectively manage and utilize data, education in data literacy should start from the very beginning. However, research data topics are largely missing in chemistry curricular. Furthermore, students and researchers have a high demand for early education in research data management and handling and think that their institute would benefit if it were part of the official curriculum.[1] Figure 1: Multidimensional teaching and training for the chemistry community. The chemistry consortium in the national research data infrastructure in Germany NFDI4Chem[2-4] tackles these challenges by providing several teaching and training courses and materials – for all career stages as well as all research data management (RDM) levels (Figure 1), e.g., workshops on research data management or electronic lab notebooks. As we believe that young chemists and students are key to the cultural change, we are increasingly paying attention to education, such as providing teaching courses, teaching materials, and knowledge bases. For comprehensive integration of RDM into chemistry curricular, the Study Commission of the German Chemical Society (Gesellschaft Deutscher Chemiker, GDCh) in-cluded data literacy in its recommendations for bachelor's degree programs in chemistry at universities in 2021.[5] These guidelines support institutions in updating their curricular which is often a time-consuming procedure. Therefore, some lecturers which did not want to waste time for that process to conclude already introduced RDM topics in their courses where possi-ble. These leading examples, from institutions such as the RWTH Aachen University or RPTU Kaiserslautern-Landau, serve as best practice for others that are planning to integrate RDM teaching into their study programs. This presentation will highlight teaching programs from RWTH Aachen University that have been implemented in theoretical and practical student courses and the collected feedback of students thereof from several years. For example, the integration of RDM into an inorganic lab course serves as a hands-on experience where the students are required to use an electronic lab notebook to document their syntheses.[6] Our approach of "subcurricular" integration into existing programs allowed a fast implementation into running chemistry lectures and avoided the major curricular changes mentioned above. Furthermore, similar educational efforts and institutional strategies from other institutions (e.g., RPTU Kaiserslautern-Landau, Friedrich Schiller University of Jena etc.) which were developed over the last years will be shown as well. Since these examples will also demonstrate differences among universities, we will in-troduce how and where we and others (can) openly share teaching materials for re-use to em-power others to adapt these curricular or subcurricular approaches for their individual institu-tions with minimal effort – not just for chemistry.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-04
DOI
https://doi.org/10.5281/zenodo.16736320
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Curricular and subcurricular teaching of RDM in chemistry to reach the next generation

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Curricular and subcurricular teaching of RDM in chemistry to reach the next generation

article en

Abstract

As we navigate an increasingly data-driven world, advanced skills in using digital tools are mandatory to survive in day-to-day life. This digitalization has also found its way into chemical research, where more and more electronic research data are being generated. Handling and management of the collected data has become a considerable part of every researcher's daily work. Scientists need to be trained in these topics and concepts to apply them successfully in their research processes. To have the ability to effectively manage and utilize data, education in data literacy should start from the very beginning. However, research data topics are largely missing in chemistry curricular. Furthermore, students and researchers have a high demand for early education in research data management and handling and think that their institute would benefit if it were part of the official curriculum.[1] Figure 1: Multidimensional teaching and training for the chemistry community. The chemistry consortium in the national research data infrastructure in Germany NFDI4Chem[2-4] tackles these challenges by providing several teaching and training courses and materials – for all career stages as well as all research data management (RDM) levels (Figure 1), e.g., workshops on research data management or electronic lab notebooks. As we believe that young chemists and students are key to the cultural change, we are increasingly paying attention to education, such as providing teaching courses, teaching materials, and knowledge bases. For comprehensive integration of RDM into chemistry curricular, the Study Commission of the German Chemical Society (Gesellschaft Deutscher Chemiker, GDCh) in-cluded data literacy in its recommendations for bachelor's degree programs in chemistry at universities in 2021.[5] These guidelines support institutions in updating their curricular which is often a time-consuming procedure. Therefore, some lecturers which did not want to waste time for that process to conclude already introduced RDM topics in their courses where possi-ble. These leading examples, from institutions such as the RWTH Aachen University or RPTU Kaiserslautern-Landau, serve as best practice for others that are planning to integrate RDM teaching into their study programs. This presentation will highlight teaching programs from RWTH Aachen University that have been implemented in theoretical and practical student courses and the collected feedback of students thereof from several years. For example, the integration of RDM into an inorganic lab course serves as a hands-on experience where the students are required to use an electronic lab notebook to document their syntheses.[6] Our approach of "subcurricular" integration into existing programs allowed a fast implementation into running chemistry lectures and avoided the major curricular changes mentioned above. Furthermore, similar educational efforts and institutional strategies from other institutions (e.g., RPTU Kaiserslautern-Landau, Friedrich Schiller University of Jena etc.) which were developed over the last years will be shown as well. Since these examples will also demonstrate differences among universities, we will in-troduce how and where we and others (can) openly share teaching materials for re-use to em-power others to adapt these curricular or subcurricular approaches for their individual institu-tions with minimal effort – not just for chemistry.

Zenodo (CERN European Organization for Nuclear Research)
RWTH Aachen University (DE)
Quality Education
Openalex Percentile: Top 45%
Research Data Management Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.