Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Christian Schmidt; Janina Hanne; Josh Moore; Christian Meesters; Elisa Ferrando-May; Stefanie Weidtkamp-Peters; members of the NFDI4BIOIMAGE initiative

doi:10.12688/f1000research.121714.2

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

F1000Res. 2022 Jun 10:11:638. doi: 10.12688/f1000research.121714.2. eCollection 2022.

Authors

Christian Schmidt^#^{1

2}, Janina Hanne^#³, Josh Moore^{3

4}, Christian Meesters⁵, Elisa Ferrando-May^{1

2

3}, Stefanie Weidtkamp-Peters^{3

6}; members of the NFDI4BIOIMAGE initiative

Affiliations

¹ Enabling Technology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany.
² Bioimaging Center, University of Konstanz, Konstanz, Germany.
³ German BioImaging - Society for Microscopy and Image Analysis e.V., Konstanz, Germany.
⁴ Open Microscopy Environment Consortium, University of Dundee, Dundee, UK.
⁵ High Performance Computing, Johannes Gutenberg University Mainz, Mainz, Germany.
⁶ Center for Advanced Imaging, Heinrich Heine University Dusseldorf, Dusseldorf, Germany.

^# Contributed equally.

Abstract

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Keywords: FAIR-principles; OMERO; Research data management; bioimage analysis; bioimaging; microscopy.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Data Management*
Humans
Information Dissemination
Metadata*
Surveys and Questionnaires
Workflow

Grants and funding

This work was supported by German BioImaging - Gesellschaft für Mikroskopie und Bildanalyse e.V., the University of Konstanz, funded as part of the Excellence Strategy of the German Federal and State Governments, and the work was funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 462231789, project I3D:bio.