Research Data Management
All members of the CRC1080 are committed to adhering to the standards of good scientific practise regarding data acquisition, documentation, storage and transfer, following the recommendations of the Research Data Management (RDM) of the participating institutions and the guidelines of the DFG for Safeguarding Good Research Practice, Code of Conduct 2019 (link). In the implementation of the RDM strategies, we take into greatly consideration the FAIR principles to make data Findable, Accessible, Interoperable and Reusable and as well as the principles of the Open Source and Open Data policy. Due to the multidisciplinary facet of this CRC1080, a large variety formats of data are acquired in the different projects and subprojects. The data types range from electrophysiology, calcium imaging, confocal and multiphoton imaging, optogenetics, electron microscopy, behaviour experiments in different animal models, transcriptomics, proteomics, and computational models. These heterogeneous data are backed up on university secured servers at all sites to avoid data loss and to ensure traceability of scientific results for at least 10 years. IT staff at the participating institutions (HRZ GU Frankfurt and ZDV JGU Mainz, IT departments at the MPIBR and the IMB) support the CRC1080 members to ensure the safe data handling and storage.
An important aspect to ensure the proper data handling is the training of the scientists at different career stages on the principles of RDM. Therefore, the CRC1080 encourages all members of their corresponding labs to attend to workshops and courses on data management. GRADE offers special courses on RDM and also the department of RDM at the GU provides workshops to train on an overview on data management. Recommended online data courses are offered by MANTRA (link) and by FOSTER (link). The CRC1080 has also organized a workshop on Research Data Management instructed by Nina Dworschak (GU) with the support of Dr Anne Vieten (JGU). This workshop took place on 16th July 2020 via a digital platform (due to the current pandemic situation). The content of the workshop was an introduction to the good scientific practice for data management, data storage, data backup, as well as instructions and tools for organization of data, documentation and metadata, sharing and data publication, and finding and re-using data. Moreover, it provided an overview on RDM at GU and JGU and was taught at the theoretical and practical level regarding how to work with electronic lab books and with data management plans.