PT - JOURNAL ARTICLE AU - Klingner, Carsten M. AU - Denker, Michael AU - Grün, Sonja AU - Hanke, Michael AU - Oeltze-Jafra, Steffen AU - Ohl, Frank W. AU - Radny, Janina AU - Rotter, Stefan AU - Scherberger, Hansjörg AU - Stein, Alexandra AU - Wachtler, Thomas AU - Witte, Otto W. AU - Ritter, Petra TI - Research Data Management and Data Sharing for Reproducible Research—Results of a Community Survey of the German National Research Data Infrastructure Initiative Neuroscience AID - 10.1523/ENEURO.0215-22.2023 DP - 2023 Feb 01 TA - eneuro PG - ENEURO.0215-22.2023 VI - 10 IP - 2 4099 - http://www.eneuro.org/content/10/2/ENEURO.0215-22.2023.short 4100 - http://www.eneuro.org/content/10/2/ENEURO.0215-22.2023.full SO - eNeuro2023 Feb 01; 10 AB - Science is changing: the volume and complexity of data are increasing, the number of studies is growing and the goal of achieving reproducible results requires new solutions for scientific data management. In the field of neuroscience, the German National Research Data Infrastructure (NFDI-Neuro) initiative aims to develop sustainable solutions for research data management (RDM). To obtain an understanding of the present RDM situation in the neuroscience community, NFDI-Neuro conducted a comprehensive survey among the neuroscience community. Here, we report and analyze the results of the survey. We focused the survey and our analysis on current needs, challenges, and opinions about RDM. The German neuroscience community perceives barriers with respect to RDM and data sharing mainly linked to (1) lack of data and metadata standards, (2) lack of community adopted provenance tracking methods, (3) lack of secure and privacy preserving research infrastructure for sensitive data, (4) lack of RDM literacy, and (5) lack of resources (time, personnel, money) for proper RDM. However, an overwhelming majority of community members (91%) indicated that they would be willing to share their data with other researchers and are interested to increase their RDM skills. Taking advantage of this willingness and overcoming the existing barriers requires the systematic development of standards, tools, and infrastructure, the provision of training, education, and support, as well as additional resources for RDM to the research community and a constant dialogue with relevant stakeholders including policy makers to leverage of a culture change through adapted incentivization and regulation.