2020 BioImage Analysis Survey: Community experiences and needs for the future

Abstract

In this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH-funded 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 practice 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 online location 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.

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

“…Self-education plays a crucial role in learning how to perform bioimage analysis ( Figure 3b ). In line with the 2020 survey of the NIH Center for Open Bioimage Analysis (COBA), 31 the most frequently and autonomously used image analysis tools are open-source and proprietary ‘point-and-click’ applications, mostly on local computers (in particular ImageJ or Fiji; Suppl. Figure 5b, c 35 ).…”

“…We drafted the questions presented in this survey inspired by the exchange between community members during the preparation phase of the NFDI4BIOIMAGE consortium and methodologically oriented on previous community surveys in the bioimaging field. 31 – 34 The questions were designed de-novo and not previously validated. Before the survey was conducted, the questions were reviewed by members of the NFDI4BIOIMAGE initiative with expertise in the relevant fields (e.g., bioimaging methods, bioimage analysis, general research data management).…”

A practical guide to bioimaging research data management in core facilities

“…[85][86][87][88] Image analysis is a science in itself, and aspects to consider are outlined elsewhere. [89][90][91][92][93][94] Notably, data management is crucial in image analysis: accessing large data sets, sharing copies of data or results, maintaining records of processed data and their provenance and associating results with the corresponding raw data for later exploration. 95 This becomes even more pivotal in the context of automated analysis pipelines, where the code heavily relies on well-structured data sources.…”

Challenges and opportunities for bioimage analysis core‐facilities

“…Our impression goes in line with a recently executed, international survey: More and more scientists seek to learn bioimage analysis skills themselves and thus, there is a large need for tutorials and workshops. 44…”