PeerJ Computer Science (Dec 2017)
Sustainable computational science: the ReScience initiative
- Nicolas P. Rougier,
- Konrad Hinsen,
- Frédéric Alexandre,
- Thomas Arildsen,
- Lorena A. Barba,
- Fabien C.Y. Benureau,
- C. Titus Brown,
- Pierre de Buyl,
- Ozan Caglayan,
- Andrew P. Davison,
- Marc-André Delsuc,
- Georgios Detorakis,
- Alexandra K. Diem,
- Damien Drix,
- Pierre Enel,
- Benoît Girard,
- Olivia Guest,
- Matt G. Hall,
- Rafael N. Henriques,
- Xavier Hinaut,
- Kamil S. Jaron,
- Mehdi Khamassi,
- Almar Klein,
- Tiina Manninen,
- Pietro Marchesi,
- Daniel McGlinn,
- Christoph Metzner,
- Owen Petchey,
- Hans Ekkehard Plesser,
- Timothée Poisot,
- Karthik Ram,
- Yoav Ram,
- Etienne Roesch,
- Cyrille Rossant,
- Vahid Rostami,
- Aaron Shifman,
- Joseph Stachelek,
- Marcel Stimberg,
- Frank Stollmeier,
- Federico Vaggi,
- Guillaume Viejo,
- Julien Vitay,
- Anya E. Vostinar,
- Roman Yurchak,
- Tiziano Zito
Affiliations
- Nicolas P. Rougier
- INRIA Bordeaux Sud-Ouest, Talence, France
- Konrad Hinsen
- Centre de Biophysique Moléculaire UPR4301, CNRS, Orléans, France
- Frédéric Alexandre
- INRIA Bordeaux Sud-Ouest, Talence, France
- Thomas Arildsen
- Department of Electronic Systems, Technical Faculty of IT and Design, Aalborg University, Aalborg, Denmark
- Lorena A. Barba
- Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, D.C., USA
- Fabien C.Y. Benureau
- INRIA Bordeaux Sud-Ouest, Talence, France
- C. Titus Brown
- Department of Population Health and Reproduction, University of California Davis, Davis, CA, USA
- Pierre de Buyl
- Instituut voor Theoretische Fysica, KU Leuven, Leuven, Belgium
- Ozan Caglayan
- Laboratoire d’Informatique (LIUM), Le Mans University, Le Mans, France
- Andrew P. Davison
- UNIC FRE 3693, CNRS, Gif-sur-Yvette, France
- Marc-André Delsuc
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France
- Georgios Detorakis
- Department of Cognitive Sciences, University of California Irvine, Irvine, CA, USA
- Alexandra K. Diem
- Computational Engineering and Design, University of Southampton, Southampton, United Kingdom
- Damien Drix
- Humboldt Universität zu Berlin, Berlin, Germany
- Pierre Enel
- Department of Neuroscience, Mount Sinai School of Medicine, New York, NY, USA
- Benoît Girard
- Institute of Intelligent Systems and Robotics, Sorbonne Universités - UPMC Univ Paris 06 - CNRS, Paris, France
- Olivia Guest
- Experimental Psychology, University College London, London, Greater London, United Kingdom
- Matt G. Hall
- UCL Great Ormond St Institute of Child Health, London, United Kingdom
- Rafael N. Henriques
- Champalimaud Centre for the Unknown, Champalimaud Neuroscience Program, Lisbon, Portugal
- Xavier Hinaut
- INRIA Bordeaux Sud-Ouest, Talence, France
- Kamil S. Jaron
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
- Mehdi Khamassi
- Institute of Intelligent Systems and Robotics, Sorbonne Universités - UPMC Univ Paris 06 - CNRS, Paris, France
- Almar Klein
- Independent scholar, Enschede, The Netherlands
- Tiina Manninen
- BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
- Pietro Marchesi
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Daniel McGlinn
- Department of Biology, College of Charleston, Charleston, SC, USA
- Christoph Metzner
- Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, United Kingdom
- Owen Petchey
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
- Hans Ekkehard Plesser
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway
- Timothée Poisot
- Département de Sciences Biologiques, Université de Montréal, Montréal, QC, Canada
- Karthik Ram
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
- Yoav Ram
- Department of Biology, Stanford University, Stanford, CA, USA
- Etienne Roesch
- Centre for Integrative Neuroscience, University of Reading, Reading, United Kingdom
- Cyrille Rossant
- Institute of Neurology, University College London, London, United Kingdom
- Vahid Rostami
- Institute of Neuroscience & Medicine, Juelich Forschungszentrum, Jülich, Germany
- Aaron Shifman
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
- Joseph Stachelek
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
- Marcel Stimberg
- Sorbonne Universités/UPMC Univ Paris 06/INSERM/CNRS/Institut de la Vision, Paris, France
- Frank Stollmeier
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Lower Saxony, Germany
- Federico Vaggi
- Amazon, Seattle, WA, USA
- Guillaume Viejo
- Institute of Intelligent Systems and Robotics, Sorbonne Universités - UPMC Univ Paris 06 - CNRS, Paris, France
- Julien Vitay
- Department of Computer Science, Chemnitz University of Technology, Chemnitz, Saxony, Germany
- Anya E. Vostinar
- Department of Computer Science, Grinnell College, Grinnell, IA, USA
- Roman Yurchak
- Symerio, Palaiseau, France
- Tiziano Zito
- Neural Information Processing Group, Eberhard Karls Universität Tübingen, Tübingen, Germany
- DOI
- https://doi.org/10.7717/peerj-cs.142
- Journal volume & issue
-
Vol. 3
p. e142
Abstract
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested and are hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.
Keywords