Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

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.

A practical guide to bioimaging research data management in core facilities

“…relevant RDM topics throughout every step of experimental research, we use the data life cycle concept applied to bioimaging data. 14,16,17 We highlight issues commonly experienced in core facilities and describe our view on present and potential future roles for core facilities in bioimaging RDM. We exemplify tools and describe future directions for data handling.…”

“…5,29 However, researchers and core facility staff seem to have limited usage of DMPs in practice. 7,30 DMP templates that have been approved or provided by the core facility, if available within an institutional DMP tool, can guide scientists to questions regarding image data handling appropriate to their local IT environment. Core facility staff are familiar with the institutional resources for bioimaging, including acquisition machines, IT resources for storage and data transfer, workstations for processing and analysis and services by academic libraries such as providing persistent identifiers (PIDs).…”

“…[43][44][45] Tabular metadata collection formats are often used. 7,40 Optionally, core facilities can enforce metadata enrichment, especially for large data otherwise hard to manage. A mandatory metadata checklist could become part of the core facility's usage policy, for example, as recommended for high-content screening (HCS) data within the Dutch bioimaging network.…”

“…[4][5][6] Early career scientists especially rely on core facility specialists to learn about microscopy techniques and how to best apply them. 7,8 Besides providing training on microscopes, core facility staff regularly deal with various user questions, for example: How does the microscope choice influence data quality and quantity? How are microscopy files structured?…”

“…13 Moreover, more than 20 German institutions formed a consortium dedicated to bioimage data management within the National Research Data Infrastructure (NFDI). 14 This consortium, NFDI4BIOIMAGE, aims at fostering new standards for image data handling and metadata curation (https://nfdi4bioimage.de) and is embedded within a network of consortia (https://nfdi.de). These and more projects (e.g., FoundingGIDE, https://cordis.europa.eu/ project/id/101130216) aim to align strategies for bioimaging RDM while accounting for local and discipline-specific needs.…”