Enabling Technology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany.
Bioimaging Center, University of Konstanz, Konstanz, Germany.
F1000Res. 2022 Jun 10;11:638. doi: 10.12688/f1000research.121714.2. eCollection 2022.
: 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.
了解生物成像社区在研究数据管理 (RDM) 方面的需求对于确定能够在跨学科的显微镜和生物图像分析数据中采用 FAIR(可发现、可访问、可互操作、可重用)原则的措施至关重要。作为德国国家研究数据基础设施的一项倡议,我们在 2021 年夏天进行了这项社区调查,以评估生物成像 RDM 的现状和社区需求。
我们采用混合问题类型设计进行了在线调查。我们创建了一份针对生物成像社区相关主题的问卷,其中包括生物成像方法和生物图像分析的具体问题,以及关于 RDM 原则和工具的更一般问题。分析中包含了 203 份调查条目,涵盖了来自不同生命和生物医学科学学科以及不同职业水平的参与者的观点。
结果强调了生物成像 RDM 和数据共享的重要性和价值。然而,FAIR 实践的实际实施受到技术障碍、知识缺乏以及对数据共享法律方面的不安全感的阻碍。调查参与者要求元数据指南和注释工具,并支持使用图像数据管理平台。目前,OMERO(开放显微镜环境远程对象)是最知名和使用最广泛的平台。大多数受访者依赖图像处理和分析,他们认为这是生物图像数据工作流程中最耗时的步骤。虽然对电子实验室笔记本和数据管理计划的了解和实施有限,但受访者承认它们在数据处理和发布方面的潜在价值。
生物成像社区承认并认可 RDM 和数据共享的价值。尽管如此,仍然需要信息、指导和标准化来促进 FAIR 数据处理的采用。这项调查可能有助于激发有针对性的措施来缩小这一差距。