How To: Open Science

• A. Mielke
• Data , RDM , Open Science

Tired of Recreating someone else’s work? - How Open Science can accelerate research and overcome reinvention

Have you ever found papers on algorithms but their implementation is missing? Found an interesting analysis but there is no way to check the results, as you don’t have access to the data they were derived from? Ever thought you had a great idea for a project, just to find out a year later that you are not the only research group following that specific idea? Not having access to other people’s code, data, metrics or even their plans for research projects often leads to unnecessary delays and scientific redundancies. There is an easy solution to overcome (almost) all of these issues. It’s called Open Science! What is Open Science? The UNESCO defines Open Science as a construct of “movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone, to increase scientific collaborations and sharing of information for the benefits of science and society, and to open the processes of scientific knowledge creation, evaluation and communication to societal actors […]”. To ensure that everyone has access to scientific knowledge and infrastructure, Open Science focuses on four main concepts.

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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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How To: Good Scientific Practice

• C. Hillen
• Data , RDM , good scientific practice

“Scientific integrity forms the basis for trustworthy research”, so it says in the Guidelines for Safeguarding Good Research Practice of the DFG, the German Research Foundation. As a major funder of research in Germany the DFG, as well as many other funders of research in Germany and the European Union, requires researchers to follow a certain set of rules conducting their research. These rules are called “good scientific practice” and have to be followed by researchers to be viable for funding. According to the guidelines researchers are required to “document all information relevant to the production of a research result as clearly as is required by and is appropriate for the relevant subject area to allow the result to be reviewed and assessed”. But good scientific practice is not done by documenting your research. It also includes i.a. protecting the personality rights of your subjects and handling research data in an appropriate manner by e.g. “back(-ing) up research data and results made publicly available, as well as the central materials on which they are based and the research software used, by adequate means according to the standards of the relevant subject area, and retain them for an appropriate period of time.” This is where Research Data Management (RDM) comes in. Of course RDM is much more than just creating a backup of your data on a USB-Stick and handing it over to anyone asking for it. “Good scientific practice” in RDM follows the FAIR principles:

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