Bæredygtig beregningsbaseret videnskab: ReScience-initiativet: the ReScience initiative

Nicolas Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, Fabien Benureau, C. Titus Brown, Pierre de Buyl, Ozan Caglayan, Andrew Davison, Marc André Delsuc, Georgios Detorakis, Alexandra Diem, Damien Drix, Pierre Enel, Benoît Girard, Olivia Guest, Matt Hall, Rafael Henriques, Xavier Hinaut & 25 andre Kamil Jaron, Mehdi Khamassi, Almar Klein, Tiina Manninen, Pietro Marchesi, Dan 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 Stollmeyer, Federico Vaggi, Guillaume Viejo, Julien Vitay, Anya Vostinar, Roman Yurchak, Tiziano Zito

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Resumé

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, 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.
Bidragets oversatte titelBæredygtig beregningsbaseret videnskab: ReScience-initiativet
OriginalsprogEngelsk
TidsskriftPeerJ
Vol/bind3
Udgave nummer142e
Antal sider17
ISSN2167-8359
DOI
StatusUdgivet - 2017

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    Rougier, N., Hinsen, K., Alexandre, F., Arildsen, T., Barba, L., Benureau, F., ... Zito, T. (2017). Sustainable computational science: the ReScience initiative. PeerJ, 3(142e). https://doi.org/10.7717/peerj-cs.142
    Rougier, Nicolas ; Hinsen, Konrad ; Alexandre, Frédéric ; Arildsen, Thomas ; Barba, Lorena ; Benureau, Fabien ; Brown, C. Titus ; de Buyl, Pierre ; Caglayan, Ozan ; Davison, Andrew ; Delsuc, Marc André ; Detorakis, Georgios ; Diem, Alexandra ; Drix, Damien ; Enel, Pierre ; Girard, Benoît ; Guest, Olivia ; Hall, Matt ; Henriques, Rafael ; Hinaut, Xavier ; Jaron, Kamil ; Khamassi, Mehdi ; Klein, Almar ; Manninen, Tiina ; Marchesi, Pietro ; McGlinn, Dan ; Metzner, Christoph ; Petchey, Owen ; Ekkehard Plesser, Hans ; Poisot, Timothée ; Ram, Karthik ; Ram, Yoav ; Roesch, Etienne ; Rossant, Cyrille ; Rostami, Vahid ; Shifman, Aaron ; Stachelek, Joseph ; Stimberg, Marcel ; Stollmeyer, Frank ; Vaggi, Federico ; Viejo, Guillaume ; Vitay, Julien ; Vostinar, Anya ; Yurchak, Roman ; Zito, Tiziano. / Sustainable computational science : the ReScience initiative. I: PeerJ. 2017 ; Bind 3, Nr. 142e.
    @article{df04949073ef44b2835f2fc6da4c5ceb,
    title = "Sustainable computational science: the ReScience initiative",
    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, 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 = "Open Science, computational science, Reproducibility, replicability, Journal, Publication",
    author = "Nicolas Rougier and Konrad Hinsen and Fr{\'e}d{\'e}ric Alexandre and Thomas Arildsen and Lorena Barba and Fabien Benureau and Brown, {C. Titus} and {de Buyl}, Pierre and Ozan Caglayan and Andrew Davison and Delsuc, {Marc Andr{\'e}} and Georgios Detorakis and Alexandra Diem and Damien Drix and Pierre Enel and Beno{\^i}t Girard and Olivia Guest and Matt Hall and Rafael Henriques and Xavier Hinaut and Kamil Jaron and Mehdi Khamassi and Almar Klein and Tiina Manninen and Pietro Marchesi and Dan McGlinn and Christoph Metzner and Owen Petchey and {Ekkehard Plesser}, Hans and Timoth{\'e}e Poisot and Karthik Ram and Yoav Ram and Etienne Roesch and Cyrille Rossant and Vahid Rostami and Aaron Shifman and Joseph Stachelek and Marcel Stimberg and Frank Stollmeyer and Federico Vaggi and Guillaume Viejo and Julien Vitay and Anya Vostinar and Roman Yurchak and Tiziano Zito",
    year = "2017",
    doi = "10.7717/peerj-cs.142",
    language = "English",
    volume = "3",
    journal = "PeerJ",
    issn = "2167-8359",
    publisher = "PeerJ",
    number = "142e",

    }

    Rougier, N, Hinsen, K, Alexandre, F, Arildsen, T, Barba, L, Benureau, F, Brown, CT, de Buyl, P, Caglayan, O, Davison, A, Delsuc, MA, Detorakis, G, Diem, A, Drix, D, Enel, P, Girard, B, Guest, O, Hall, M, Henriques, R, Hinaut, X, Jaron, K, Khamassi, M, Klein, A, Manninen, T, Marchesi, P, McGlinn, D, Metzner, C, Petchey, O, Ekkehard Plesser, H, Poisot, T, Ram, K, Ram, Y, Roesch, E, Rossant, C, Rostami, V, Shifman, A, Stachelek, J, Stimberg, M, Stollmeyer, F, Vaggi, F, Viejo, G, Vitay, J, Vostinar, A, Yurchak, R & Zito, T 2017, 'Sustainable computational science: the ReScience initiative' PeerJ, bind 3, nr. 142e. https://doi.org/10.7717/peerj-cs.142

    Sustainable computational science : the ReScience initiative. / Rougier, Nicolas; Hinsen, Konrad; Alexandre, Frédéric; Arildsen, Thomas; Barba, Lorena; Benureau, Fabien; Brown, C. Titus; de Buyl, Pierre; Caglayan, Ozan; Davison, Andrew; Delsuc, Marc André; Detorakis, Georgios; Diem, Alexandra; Drix, Damien; Enel, Pierre; Girard, Benoît; Guest, Olivia; Hall, Matt; Henriques, Rafael; Hinaut, Xavier; Jaron, Kamil; Khamassi, Mehdi; Klein, Almar; Manninen, Tiina; Marchesi, Pietro; McGlinn, Dan; Metzner, Christoph; Petchey, Owen; Ekkehard Plesser, Hans; Poisot, Timothée; Ram, Karthik; Ram, Yoav; Roesch, Etienne; Rossant, Cyrille; Rostami, Vahid; Shifman, Aaron; Stachelek, Joseph; Stimberg, Marcel; Stollmeyer, Frank; Vaggi, Federico; Viejo, Guillaume; Vitay, Julien; Vostinar, Anya; Yurchak, Roman; Zito, Tiziano.

    I: PeerJ, Bind 3, Nr. 142e, 2017.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    TY - JOUR

    T1 - Sustainable computational science

    T2 - the ReScience initiative

    AU - Rougier, Nicolas

    AU - Hinsen, Konrad

    AU - Alexandre, Frédéric

    AU - Arildsen, Thomas

    AU - Barba, Lorena

    AU - Benureau, Fabien

    AU - Brown, C. Titus

    AU - de Buyl, Pierre

    AU - Caglayan, Ozan

    AU - Davison, Andrew

    AU - Delsuc, Marc André

    AU - Detorakis, Georgios

    AU - Diem, Alexandra

    AU - Drix, Damien

    AU - Enel, Pierre

    AU - Girard, Benoît

    AU - Guest, Olivia

    AU - Hall, Matt

    AU - Henriques, Rafael

    AU - Hinaut, Xavier

    AU - Jaron, Kamil

    AU - Khamassi, Mehdi

    AU - Klein, Almar

    AU - Manninen, Tiina

    AU - Marchesi, Pietro

    AU - McGlinn, Dan

    AU - Metzner, Christoph

    AU - Petchey, Owen

    AU - Ekkehard Plesser, Hans

    AU - Poisot, Timothée

    AU - Ram, Karthik

    AU - Ram, Yoav

    AU - Roesch, Etienne

    AU - Rossant, Cyrille

    AU - Rostami, Vahid

    AU - Shifman, Aaron

    AU - Stachelek, Joseph

    AU - Stimberg, Marcel

    AU - Stollmeyer, Frank

    AU - Vaggi, Federico

    AU - Viejo, Guillaume

    AU - Vitay, Julien

    AU - Vostinar, Anya

    AU - Yurchak, Roman

    AU - Zito, Tiziano

    PY - 2017

    Y1 - 2017

    N2 - 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, 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.

    AB - 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, 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.

    KW - Open Science

    KW - computational science

    KW - Reproducibility

    KW - replicability

    KW - Journal

    KW - Publication

    U2 - 10.7717/peerj-cs.142

    DO - 10.7717/peerj-cs.142

    M3 - Journal article

    VL - 3

    JO - PeerJ

    JF - PeerJ

    SN - 2167-8359

    IS - 142e

    ER -

    Rougier N, Hinsen K, Alexandre F, Arildsen T, Barba L, Benureau F et al. Sustainable computational science: the ReScience initiative. PeerJ. 2017;3(142e). https://doi.org/10.7717/peerj-cs.142