The Pegasus workflow management system: Translational computer science in practice
•Analysis of translational computer science with the lens of the Pegasus experience.•Application of TCS principles into the research and development process of Pegasus.•Discussion of challenges and potential solutions regarding translational research. Translational research (TR) has been extensively...
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| Published in: | Journal of computational science Vol. 52; p. 101200 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.05.2021
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| ISSN: | 1877-7503, 1877-7511 |
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| Abstract | •Analysis of translational computer science with the lens of the Pegasus experience.•Application of TCS principles into the research and development process of Pegasus.•Discussion of challenges and potential solutions regarding translational research.
Translational research (TR) has been extensively used in the health science domain, where results from laboratory research are translated to human studies and where evidence-based practices are adopted in real-world settings to reach broad communities. In computer science, much research stops at the result publication and dissemination stage without moving to the evaluation in real settings at scale and feeding the gained knowledge back to research. Additionally, there is a lack of steady funding and incentives to broadly promote translational computer science (TCS) in practice. In this paper, we present how, throughout its lifespan, the Pegasus workflow management system project has incorporated the principles of translational computer science. We report on our experience on building a strong, long-term engagement with a broad range of science communities to establish mutually beneficial relationships between the core R&D team and these communities. |
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| AbstractList | •Analysis of translational computer science with the lens of the Pegasus experience.•Application of TCS principles into the research and development process of Pegasus.•Discussion of challenges and potential solutions regarding translational research.
Translational research (TR) has been extensively used in the health science domain, where results from laboratory research are translated to human studies and where evidence-based practices are adopted in real-world settings to reach broad communities. In computer science, much research stops at the result publication and dissemination stage without moving to the evaluation in real settings at scale and feeding the gained knowledge back to research. Additionally, there is a lack of steady funding and incentives to broadly promote translational computer science (TCS) in practice. In this paper, we present how, throughout its lifespan, the Pegasus workflow management system project has incorporated the principles of translational computer science. We report on our experience on building a strong, long-term engagement with a broad range of science communities to establish mutually beneficial relationships between the core R&D team and these communities. |
| ArticleNumber | 101200 |
| Author | Whitcup, Wendy Ferreira da Silva, Rafael Vahi, Karan Rynge, Mats Tanaka, Ryan Deelman, Ewa Mayani, Rajiv Livny, Miron |
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| Cites_doi | 10.1038/s41586-019-1124-4 10.1016/j.future.2015.01.004 10.1038/sj.clpt.6100029 10.1109/MCSE.2019.2919690 10.1109/MCSE.2014.80 10.1103/PhysRevD.95.122003 10.1016/j.jand.2015.03.010 10.1097/ACM.0b013e3181ccd618 10.1109/TCC.2015.2427200 10.1109/MC.2019.2925650 10.1109/INDIS49552.2019.00012 10.1001/jama.2007.26 10.1002/cpe.938 10.1016/j.future.2014.10.008 10.1016/j.future.2019.06.016 |
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| Keywords | Large-scale distributed computing Translational research Scientific workflows Translational computer science Workflow management systems |
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| References | Deelman, Vahi, Rynge, Mayani, Ferreira da Silva, Papadimitriou, Livny (bib0035) 2019; 21 Singh, Vahi, Ramakrishnan, Mehta, Deelman, Zhao, Sakellariou, Blackburn, Brown, Fairhurst, Meyers, Berriman (bib0075) 2007 Woolf (bib0015) 2008; 299 Jordan, Callaghan, Graves, Wang, Milner, Goulet, Maechling (bib0065) 2018; 89 Abramson, Parashar (bib0025) 2019; 52 Towns, Cockerill, Dahan, Foster, Gaither, Grimshaw, Hazlewood, Lathrop, Lifka, Peterson (bib0120) 2014; 16 Deelman, Kesselman, Mehta, Meshkat, Pearlman, Blackburn, Ehrens, Lazzarini, Williams, Koranda (bib0040) 2002 Zerhouni (bib0005) 2007; 81 Couvares, Kosar, Roy, Weber, Wenger (bib0050) 2007 Chen, Ferreira da Silva, Deelman, Fahringer (bib0100) 2016; 4 Pordes, Petravick, Kramer, Olson, Livny, Roy, Avery, Blackburn, Wenaus, Würthwein, Foster, Gardner, Wilde, Blatecky, McGee, Quick (bib0115) 2007; 78 Zoellner, Van Horn, Gleason, Boushey (bib0010) 2015; 115 University of Michigan (bib0020) 2017 Deelman, Vahi, Juve, Rynge, Callaghan, Maechling, Mayani, Chen, Ferreira da Silva, Livny, Wenger (bib0030) 2015; 46 Collaboration (bib0045) 2019; 568 Rubio, Schoenbaum, Lee, Schteingart, Marantz, Anderson, Platt, Baez, Esposito (bib0080) 2010; 85 Ferreira da Silva, Callaghan, Do, Papadimitriou, Deelman (bib0095) 2019; 101 Rynge, Callaghan, Deelman, Juve, Mehta, Vahi, Maechling (bib0070) 2012 Papadimitriou, Kiran, Wang, Mandal, Deelman (bib0105) 2019 Abbott, Abbott, Abbott, Acernese, Ackley, Adams, Adams, Addesso, Adhikari, Adya (bib0060) 2017; 95 Rynge, Vahi, Deelman, Mandal, Baldin, Bhide, Heiland, Welch, Hill, Poehlman (bib0090) 2019 Do, Pottier, Thomas, Ferreira da Silva, Cuendet, Weinstein, Estrada, Taufer, Deelman (bib0110) 2020 Thain, Tannenbaum, Livny (bib0055) 2005; 17 Malawski, Juve, Deelman, Nabrzyski (bib0085) 2015; 48 Zoellner (10.1016/j.jocs.2020.101200_bib0010) 2015; 115 Collaboration (10.1016/j.jocs.2020.101200_bib0045) 2019; 568 Deelman (10.1016/j.jocs.2020.101200_bib0040) 2002 Chen (10.1016/j.jocs.2020.101200_bib0100) 2016; 4 Malawski (10.1016/j.jocs.2020.101200_bib0085) 2015; 48 Towns (10.1016/j.jocs.2020.101200_bib0120) 2014; 16 Couvares (10.1016/j.jocs.2020.101200_bib0050) 2007 Abramson (10.1016/j.jocs.2020.101200_bib0025) 2019; 52 Woolf (10.1016/j.jocs.2020.101200_bib0015) 2008; 299 Abbott (10.1016/j.jocs.2020.101200_bib0060) 2017; 95 Jordan (10.1016/j.jocs.2020.101200_bib0065) 2018; 89 Deelman (10.1016/j.jocs.2020.101200_bib0035) 2019; 21 Ferreira da Silva (10.1016/j.jocs.2020.101200_bib0095) 2019; 101 Rubio (10.1016/j.jocs.2020.101200_bib0080) 2010; 85 Zerhouni (10.1016/j.jocs.2020.101200_bib0005) 2007; 81 University of Michigan (10.1016/j.jocs.2020.101200_bib0020) 2017 Do (10.1016/j.jocs.2020.101200_bib0110) 2020 Pordes (10.1016/j.jocs.2020.101200_bib0115) 2007; 78 Papadimitriou (10.1016/j.jocs.2020.101200_bib0105) 2019 Rynge (10.1016/j.jocs.2020.101200_bib0070) 2012 Rynge (10.1016/j.jocs.2020.101200_bib0090) 2019 Deelman (10.1016/j.jocs.2020.101200_bib0030) 2015; 46 Thain (10.1016/j.jocs.2020.101200_bib0055) 2005; 17 Singh (10.1016/j.jocs.2020.101200_bib0075) 2007 |
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