Better together: Elements of successful scientific software development in a distributed collaborative community
Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to un...
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| Published in | PLoS computational biology Vol. 16; no. 5; p. e1007507 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
04.05.2020
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities. |
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| AbstractList | Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities. Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities. |
| Audience | Academic |
| Author | Kortemme, Tanja Bystroff, Christopher Schueler-Furman, Ora Bonneau, Richard Leaver-Fay, Andrew Gray, Jeffrey J. Dunbrack, Roland Lyskov, Sergey Bradley, Philip Krys, Justyna Kuhlman, Brian Watkins, Andrew M. Lewis, Steven M. Adolf-Bryfogle, Jared Labonte, Jason W. Baker, David Meiler, Jens Schief, William Strauss, Charlie E. M. Koehler Leman, Julia Weitzner, Brian D. Moretti, Rocco Mulligan, Vikram Khipple Gront, Dominik Renfrew, P. Douglas |
| AuthorAffiliation | 15 Dept of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States of America 11 Dept of Biochemistry, Stanford University School of Medicine, Stanford CA, United States of America 5 Institute for Protein Design, University of Washington, Seattle, WA, United States of America 1 Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, United States of America 13 Dept of Chemistry, Franklin & Marshall College, Lancaster, PA, United States of America 3 Dept of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States of America 4 Dept of Biochemistry, University of Washington, Seattle, WA, United States of America 24 Institute for Drug Discovery, Leipzig University, Leipzig, Germany 17 Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America 16 Dept of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel 26 Center for D |
| AuthorAffiliation_xml | – name: 15 Dept of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States of America – name: 23 Institute for Chemical Biology, Vanderbilt University, Nashville, TN, United States of America – name: 1 Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, United States of America – name: 6 Lyell Immunopharma, Seattle, WA, United States of America – name: 13 Dept of Chemistry, Franklin & Marshall College, Lancaster, PA, United States of America – name: 7 Dept of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America – name: 22 Center for Structural Biology, Vanderbilt University, Nashville, TN, United States of America – name: Hebrew University of Jerusalem, ISRAEL – name: 8 Dept of Biochemistry, Duke University, Durham, NC, United States of America – name: 2 Dept of Biology, New York University, New York, NY, United States of America – name: 3 Dept of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States of America – name: 11 Dept of Biochemistry, Stanford University School of Medicine, Stanford CA, United States of America – name: 16 Dept of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel – name: 14 Dept of Chemistry, University of Warsaw, Warsaw, Poland – name: 5 Institute for Protein Design, University of Washington, Seattle, WA, United States of America – name: 21 Depts of Chemistry, Pharmacology and Biomedical Informatics, Vanderbilt University, Nashville, TN, United States of America – name: 19 Dept of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, United States of America – name: 25 Dept of Computer Science, New York University, New York, NY, United States of America – name: 12 Dept of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, United States of America – name: 17 Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America – name: 18 Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia PA, United States of America – name: 26 Center for Data Science, New York University, New York, NY, United States of America – name: 4 Dept of Biochemistry, University of Washington, Seattle, WA, United States of America – name: 10 Dept of Chemistry, Vanderbilt University, Nashville, TN, United States of America – name: 9 Cyrus Biotechnology, Seattle, WA United States of America – name: 20 Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States of America – name: 24 Institute for Drug Discovery, Leipzig University, Leipzig, Germany |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32365137$$D View this record in MEDLINE/PubMed https://www.osti.gov/servlets/purl/1659218$$D View this record in Osti.gov |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2020 Public Library of Science This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| DOI | 10.1371/journal.pcbi.1007507 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 LA-UR-20-24100 USDOE 89233218CNA000001 The Rosetta software has been licensed to numerous non-profit and for-profit organizations. Rosetta Licensing is managed by UW CoMotion, and royalty proceeds are managed by the RosettaCommons. Under institutional participation agreements between the University of Washington, acting on behalf of the RosettaCommons, their respective institutions may be entitled to a portion of revenue received on licensing Rosetta software including programs described here. Baker, Malmström, Yarov-Yarovoy, Gront, Meiler, Whitehead, Schueler-Furman, King, Gray, Sgourakis, Lindert, Strauss, Karanicolas, Bonneau, Sammond, Kortemme, and Bradley are unpaid board members of the RosettaCommons. As members of the Scientific Advisory Board of Cyrus Biotechnology, Baker and Gray are granted stock options. Yifan Song, Indigo C. King, Steven M. Lewis, Brandon Frenz, Karen Khar and Ryan Pavlovicz are currently employed at Cyrus Biotechnology with granted stock options. Cyrus Biotechnology distributes the Rosetta software. Brian D. Weitzner and Scott E. Boyken hold equity in Lyell Immunopharma. Vikram K. Mulligan is a co-founder of and shareholder in Menten Biotechnology Labs, Inc. The content of this manuscript is relevant to work performed at Lyell and Menten. Neil P. King is a co-founder and shareholder of Icosavax, Inc., a biotech company developing nanoparticle vaccines. Justin B. Siegel is a co-founder and shareholder of Digestiva, Inc. and PvP Biologics Inc. David Baker is a co-founder, shareholder, or advisor to the following companies: ARZEDA, PvP Biologics, Cyrus Biotechnology, Cue Biopharma, Icosavax, Neoleukin Therapeutics, Lyell Immunotherapeutics, Sana Biotechnology, and A-Alpha Bio. Membership of the RosettaCommons Consortium is listed in the S1 List. |
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| Title | Better together: Elements of successful scientific software development in a distributed collaborative community |
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