Provide proactive reproducible analysis transparency with every publication
The high incidence of irreproducible research has led to urgent appeals for transparency and equitable practices in open science. For the scientific disciplines that rely on computationally intensive analyses of large datasets, a granular understanding of the analysis methodology is an essential com...
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| Format: | Article |
| Language: | English |
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The Royal Society
2025-03-01
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| Series: | Royal Society Open Science |
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| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.241936 |
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| author | Paul Meijer Nicole Howard Jessica Liang Autumn Kelsey Sathya Subramanian Ed Johnson Paul Mariz James Harvey Madeline Ambrose Vitalii Tereshchenko Aldan Beaubien Neelima Inala Yousef Aggoune Stark Pister Anne Vetto Melissa Kinsey Tom Bumol Ananda Goldrath Xiaojun Li Troy Torgerson Peter Skene Lauren Okada Christian La France Zach Thomson Lucas Graybuck |
| author_facet | Paul Meijer Nicole Howard Jessica Liang Autumn Kelsey Sathya Subramanian Ed Johnson Paul Mariz James Harvey Madeline Ambrose Vitalii Tereshchenko Aldan Beaubien Neelima Inala Yousef Aggoune Stark Pister Anne Vetto Melissa Kinsey Tom Bumol Ananda Goldrath Xiaojun Li Troy Torgerson Peter Skene Lauren Okada Christian La France Zach Thomson Lucas Graybuck |
| author_sort | Paul Meijer |
| collection | DOAJ |
| description | The high incidence of irreproducible research has led to urgent appeals for transparency and equitable practices in open science. For the scientific disciplines that rely on computationally intensive analyses of large datasets, a granular understanding of the analysis methodology is an essential component of reproducibility. This article discusses the guiding principles of a computational reproducibility framework that enables a scientist to proactively generate a complete reproducible trace as analysis unfolds, and share data, methods and executable tools as part of a scientific publication, allowing other researchers to verify results and easily re-execute the steps of the scientific investigation. |
| format | Article |
| id | doaj-art-20426fc7786b42cf923d4ff604526e9f |
| institution | OA Journals |
| issn | 2054-5703 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj-art-20426fc7786b42cf923d4ff604526e9f2025-08-20T02:02:21ZengThe Royal SocietyRoyal Society Open Science2054-57032025-03-0112310.1098/rsos.241936Provide proactive reproducible analysis transparency with every publicationPaul Meijer0Nicole Howard1Jessica Liang2Autumn Kelsey3Sathya Subramanian4Ed Johnson5Paul Mariz6James Harvey7Madeline Ambrose8Vitalii Tereshchenko9Aldan Beaubien10Neelima Inala11Yousef Aggoune12Stark Pister13Anne Vetto14Melissa Kinsey15Tom Bumol16Ananda Goldrath17Xiaojun Li18Troy Torgerson19Peter Skene20Lauren Okada21Christian La France22Zach Thomson23Lucas Graybuck24Allen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAAllen Institute for Immunology, 615 Westlake Avenue N, Seattle, WA 98109, USAThe high incidence of irreproducible research has led to urgent appeals for transparency and equitable practices in open science. For the scientific disciplines that rely on computationally intensive analyses of large datasets, a granular understanding of the analysis methodology is an essential component of reproducibility. This article discusses the guiding principles of a computational reproducibility framework that enables a scientist to proactively generate a complete reproducible trace as analysis unfolds, and share data, methods and executable tools as part of a scientific publication, allowing other researchers to verify results and easily re-execute the steps of the scientific investigation.https://royalsocietypublishing.org/doi/10.1098/rsos.241936reproducibility crisisopen scienceequity in sciencedata analysisimmunologylife sciences |
| spellingShingle | Paul Meijer Nicole Howard Jessica Liang Autumn Kelsey Sathya Subramanian Ed Johnson Paul Mariz James Harvey Madeline Ambrose Vitalii Tereshchenko Aldan Beaubien Neelima Inala Yousef Aggoune Stark Pister Anne Vetto Melissa Kinsey Tom Bumol Ananda Goldrath Xiaojun Li Troy Torgerson Peter Skene Lauren Okada Christian La France Zach Thomson Lucas Graybuck Provide proactive reproducible analysis transparency with every publication Royal Society Open Science reproducibility crisis open science equity in science data analysis immunology life sciences |
| title | Provide proactive reproducible analysis transparency with every publication |
| title_full | Provide proactive reproducible analysis transparency with every publication |
| title_fullStr | Provide proactive reproducible analysis transparency with every publication |
| title_full_unstemmed | Provide proactive reproducible analysis transparency with every publication |
| title_short | Provide proactive reproducible analysis transparency with every publication |
| title_sort | provide proactive reproducible analysis transparency with every publication |
| topic | reproducibility crisis open science equity in science data analysis immunology life sciences |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.241936 |
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