| Popis: |
Scientists produce huge amounts of data every day, unfortunately not the full potential of these data is exploited. Most of the time, data is generated in a special project, kept within only one working group and forgotten after a few years. Eventually, the interest in these data arises again, but unfortunately, the data then is lost for different reasons: The data cannot be found, the data cannot be opened because the software is no longer supported, the documentation of the data is incomplete, so nobody understands the data anymore, and the list goes on. To avoid these issues, the FAIR principles [1] for good research data management were established, which are required by more and more funders, e.g., the DFG, and journals, e.g. ChemMedChem. But the scientists are not left alone with these new challenges. The NFDI4Chem [2] and SIS Pharmacy [3] support with tools, information materials, workshops and more to make the transition to FAIR research data as easy as possible. In this poster, we want to offer support to scientists which are new to the field of FAIR research data management. We will give an overview of the important concepts and principles, useful tools and offer starting points on how to start with FAIR research data management. In detail, FAIR principles, electronic lab notebooks (ELNs), data management plans (DMPs), repositories will be introduced, and a practical guide starting now with good research data management, will be presented. [1] M. D. Wilkinson at al., Sci Data, 2016, 3, 160018/1-9. [2] S. Herres-Pawlis, BFDM, 2021, 34-45. [3] C. Draheim et al., PZ Prisma. 2019, 26(2), 68-74. |
