Research data management (RDM) is a key factor to ensure the quality and reusability of data in catalysis and the catalysis related sciences. These factors open up new approaches in research, such as machine learning, simulation and even the prediction of the activity of new catalysts based on existing data. Handling data according to the FAIR principles (findable, accessible, interoperable, reusable) guarantees that the value of research data is retained over long storage periods, even if an open publication is not always possible. Still, the data will be understandable and reusable independent from the original creator. Thus, proper management of research data also guarantees efficient workflows and provides the tools for effective collaboration within an institution or across multiple partners.
The RDM School of Catalysis was created to impart the necessary skills for the application of RDM in catalysis research, from the creation of data in the lab up to the publication, long-term storage or reuse, both in academia and industry. In five interactive modules, all important aspects of RDM will be covered with emphasis on the application in catalysis, including practical examples, exercises and room to discuss the challenges in establishing RDM.
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