Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey.

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ID: 277012
2022
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Abstract
: Knowing the needs of the bioimaging community with respect to research data management (RDM) is essential for identifying measures that enable adoption of the FAIR (findable, accessible, interoperable, reusable) principles for microscopy and bioimage analysis data across disciplines. As an initiative within Germany's National Research Data Infrastructure, we conducted this community survey in summer 2021 to assess the state of the art of bioimaging RDM and the community needs. : An online survey was conducted with a mixed question-type design. We created a questionnaire tailored to relevant topics of the bioimaging community, including specific questions on bioimaging methods and bioimage analysis, as well as more general questions on RDM principles and tools. 203 survey entries were included in the analysis covering the perspectives from various life and biomedical science disciplines and from participants at different career levels. : The results highlight the importance and value of bioimaging RDM and data sharing. However, the practical implementation of FAIR practices is impeded by technical hurdles, lack of knowledge, and insecurity about the legal aspects of data sharing. The survey participants request metadata guidelines and annotation tools and endorse the usage of image data management platforms. At present, OMERO (Open Microscopy Environment Remote Objects) is the best known and most widely used platform. Most respondents rely on image processing and analysis, which they regard as the most time-consuming step of the bioimage data workflow. While knowledge about and implementation of electronic lab notebooks and data management plans is limited, respondents acknowledge their potential value for data handling and publication. : The bioimaging community acknowledges and endorses the value of RDM and data sharing. Still, there is a need for information, guidance, and standardization to foster the adoption of FAIR data handling. This survey may help inspiring targeted measures to close this gap.
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schmidt2022researchf1000research Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Schmidt, Christian;Hanne, Janina;Moore, Josh;Meesters, Christian;Ferrando-May, Elisa;Weidtkamp-Peters, Stefanie;, ;
Journal F1000Research
Year 2022
DOI
638
URL
Keywords
microscopy bioimaging omero research data management fair-principles bioimage analysis lesbian minority stress model sexual quality of life bisexual women internalized homonegativity

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