2020年生物图像分析调查:社区经验和未来需求

Nasim Jamali, E. T. Dobson, K. Eliceiri, Anne E Carpenter, B. Cimini
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引用次数: 11

摘要

在本文中,我们总结了2020年通过NIH开放生物图像分析中心(COBA)对成像界484名参与者进行的全球调查。这项23个问题的调查涵盖了图像分析的经验、科学背景和人口统计学,以及来自成像社区不同成员的观点和要求。通过开放式问题,我们要求社区为开源工具开发人员和工具用户组提供反馈。社区对工具开发人员的要求包括对工具文档和易于理解的教程进行全面改进。受访者鼓励工具用户遵循成像最佳实践指南,并在科学社区图像论坛(forum.image.sc)上提出他们的图像分析问题。我们根据计算熟练程度和工作描述分析了社区首选的学习方法。一般来说,书面的循序渐进和视频教程是社区首选的学习方法,其次是互动网络研讨会和与专家的办公时间。人们还热衷于将现有的教育资源集中在网上。调查结果将帮助社区,特别是开发人员、培训人员和像COBA这样的组织,决定如何组织和优先考虑他们的工作。Bioimage分析社区由软件开发人员、成像专家和用户组成,他们都具有不同的专业知识、科学背景和计算技能水平。美国国立卫生研究院资助的开放生物图像分析中心(COBA)于2020年启动,以满足细胞生物学界对光学显微镜图像分析的复杂开源软件和工作流程日益增长的需求。本文分享了COBA调查的结果,以评估社区中对软件和培训最紧迫的持续需求,并为在该领域工作的软件开发人员提供有用的资源。在这里,我们描述了开源生物图像分析的现状,来自社区的开发者和用户的要求,以及我们对共同目标的看法,这些目标将服务并加强社区,以推进成像科学。
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2020 BioImage Analysis Survey: Community experiences and needs for the future
In this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH Center for Open BioImage Analysis (COBA). This 23-question survey covered experience with image analysis, scientific background and demographics, and views and requests from different members of the imaging community. Through open-ended questions we asked the community to provide feedback for the opensource tool developers and tool user groups. The community’s requests for tool developers include general improvement of tool documentation and easy-to-follow tutorials. Respondents encourage tool users to follow the best practices guidelines for imaging and ask their image analysis questions on the Scientific Community Image forum (forum.image.sc). We analyzed the community’s preferred method of learning, based on level of computational proficiency and work description. In general, written step-by-step and video tutorials are preferred methods of learning by the community, followed by interactive webinars and office hours with an expert. There is also enthusiasm for a centralized location online for existing educational resources. The survey results will help the community, especially developers, trainers, and organizations like COBA, decide how to structure and prioritize their efforts. Impact statement The Bioimage analysis community consists of software developers, imaging experts, and users, all with different expertise, scientific background, and computational skill levels. The NIH funded Center for Open Bioimage Analysis (COBA) was launched in 2020 to serve the cell biology community’s growing need for sophisticated open-source software and workflows for light microscopy image analysis. This paper shares the result of a COBA survey to assess the most urgent ongoing needs for software and training in the community and provide a helpful resource for software developers working in this domain. Here, we describe the state of open-source bioimage analysis, developers’ and users’ requests from the community, and our resulting view of common goals that would serve and strengthen the community to advance imaging science.
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