FDM-Werkstatt - Into the RDM-Toolbox!

• A. Janz
• Event , RDM

The Center of Data Litercacy (German: “Zentrum für Datenkompetenz”) DKZ.2R was officially launched mid November 2023. Already a month later we joined forces with fdm.nrw to organise the very first DKZ.2R-event (find the call for participation here). The “FDM-Werkstatt – Into the RDM-Toolbox” took place from March 18 to 20, 2024 at the IT Center of RWTH Aachen University. In total, 50 participants from all over Germany took part in the workshops. Many of them brought their own topics of interest with them and presented it in one of the 12 sessions. The contents of the sessions ranged from low-level introductions and RDM-basics to elaborate and in-detail coding sessions. For three days we worked together, discussed use cases and new RDM tools. But we also enjoyed the social program such as a tour of the AiX Cave and the server room of the ITC’s High Performance Computing Center. There was a good balance between cognitively demanding workshop sessions and more relaxing social events and lunch breaks which hopefully resulted in an enjoyable and rewarding experience for all participants. On the very last day of the workshop we offered a session to especially discuss ideas and directions for the DKZ.2R. The feedback we got in this session will help us in moving forward with the DKZ.2R and making a lasting impact for future researchers.

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Love Data Week Cologne

DKZ.2R @ “Love Data Week” at University of Cologne

The DKZ.2R project is set to participate at this year’s “Love Data Week” at the University of Cologne on February 11th, 2025. DKZ.2R Consultants Marvin Lorber and Milagros Pacco are sharing their knowledge about Data FAIRness and reproducibility in their hybrid Workshop “How to do FAIR data for reproducible research”. You can take part in the workshop either on-site or via Zoom. To register, please use the Zoom registration Link.

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Documentation From User Experience

• Marvin Lorber
• Documentation , Software , RDM

This post is a condensed version of a talk at our Data Compentcy College

If you regularly use scientific software written by others, or tried to replicate interesting research that relies on software, you have probably also invested weeks of work to solve a software problem or even given up on a software because of missing documentation. Finding a project that might be the solution to your problem and then failing to run the code is frustrating. Being unable to run a project you have built yourself years ago is even worse. Having experienced all those setbacks myself in the past I want to use this post to channel that frustration to fuel solutions for better documentation for our current and future projects.

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