Insights into the Datasets, Tools, and Training Needs of the AnVIL Community: 2024

Background The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a secure cloud-based environment where research and education communities can analyze genomic and biomedical data. The platform supports a wide range of data analysis as well as the ability to safely store and access data in compliance with NIH policies. The purpose of this study is to better understand the current user base of the AnVIL platform. Methods We conducted the AnVIL Community Poll to collect baseline information, identify development opportunities, guide the prioritization of user support strategies, and succinctly but comprehensively describe the current AnVIL Community. The poll was shared through social media and relevant mailing lists. Respondents were categorized as potential or returning users depending on their usage description. Results Our sample of the AnVIL community found opportunities for platform adoption beyond the current user base and identified areas where training should be enhanced, training preferences, and user computational needs. Specifically, while most respondents were involved in human genomics research, there may be potential for growth in adoption of the platform by prioritizing materials to support clinical researchers. All respondents felt availability of specific tools or datasets was a key feature of the platform. The broader community may also benefit from further development or showcasing of resources to facilitate cost management, finding and incorporating analysis tools, and data import. Our sample greatly preferred virtual training opportunities and returning users of the platform foresaw needing large amounts of storage. Conclusion This poll provided an insightful snapshot of the current state of the AnVIL and demonstrated areas where the AnVIL Team can take specific steps to address barriers related to platform adoption and further support the existing and varied AnVIL Community. This work can be built upon through user interviews, community discussion, and coordinating a recurring poll.

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Publication Details

Journal
F1000Research
Published
2026-09-18
DOI
https://doi.org/10.12688/f1000research.173844.2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Insights into the Datasets, Tools, and Training Needs of the AnVIL Community: 2024

Stephen Mosher, Katherine E.L. Cox, Jeffrey T. Leek, Natalie Kucher et al.
F1000Research
Scientific Computing and Data Management
article

Insights into the Datasets, Tools, and Training Needs of the AnVIL Community: 2024

Stephen Mosher, Katherine E.L. Cox, Jeffrey T. Leek, Natalie Kucher, Frederick J. Tan, Kai Yin Ho, Elizabeth Humphries, Ava M. Hoffman, Kathryn J. Isaac, Michael Schatz
article en

Abstract

Background The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) provides a secure cloud-based environment where research and education communities can analyze genomic and biomedical data. The platform supports a wide range of data analysis as well as the ability to safely store and access data in compliance with NIH policies. The purpose of this study is to better understand the current user base of the AnVIL platform. Methods We conducted the AnVIL Community Poll to collect baseline information, identify development opportunities, guide the prioritization of user support strategies, and succinctly but comprehensively describe the current AnVIL Community. The poll was shared through social media and relevant mailing lists. Respondents were categorized as potential or returning users depending on their usage description. Results Our sample of the AnVIL community found opportunities for platform adoption beyond the current user base and identified areas where training should be enhanced, training preferences, and user computational needs. Specifically, while most respondents were involved in human genomics research, there may be potential for growth in adoption of the platform by prioritizing materials to support clinical researchers. All respondents felt availability of specific tools or datasets was a key feature of the platform. The broader community may also benefit from further development or showcasing of resources to facilitate cost management, finding and incorporating analysis tools, and data import. Our sample greatly preferred virtual training opportunities and returning users of the platform foresaw needing large amounts of storage. Conclusion This poll provided an insightful snapshot of the current state of the AnVIL and demonstrated areas where the AnVIL Team can take specific steps to address barriers related to platform adoption and further support the existing and varied AnVIL Community. This work can be built upon through user interviews, community discussion, and coordinating a recurring poll.

F1000ResearchVol. 14
Johns Hopkins University (US), Johns Hopkins Medicine (US), Fred Hutch Cancer Center (US), Vanderbilt University Medical Center (US)
Openalex Percentile: Top 4%
Scientific Computing and Data Management
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