Rougier Nicolas P, Hinsen Konrad, Alexandre Frédéric, Arildsen Thomas, Barba Lorena A, Benureau Fabien C Y, Brown C Titus, de Buyl Pierre, Caglayan Ozan, Davison Andrew P, Delsuc Marc-André, Detorakis Georgios, Diem Alexandra K, Drix Damien, Enel Pierre, Girard Benoît, Guest Olivia, Hall Matt G, Henriques Rafael N, Hinaut Xavier, Jaron Kamil S, Khamassi Mehdi, Klein Almar, Manninen Tiina, Marchesi Pietro, McGlinn Daniel, Metzner Christoph, Petchey Owen, Plesser Hans Ekkehard, Poisot Timothée, Ram Karthik, Ram Yoav, Roesch Etienne, Rossant Cyrille, Rostami Vahid, Shifman Aaron, Stachelek Jemma, Stimberg Marcel, Stollmeier Frank, Vaggi Federico, Viejo Guillaume, Vitay Julien, Vostinar Anya E, Yurchak Roman, Zito Tiziano
INRIA Bordeaux Sud-Ouest, Talence, France.
Centre de Biophysique Moléculaire UPR4301, CNRS, Orléans, France.
PeerJ Comput Sci. 2017 Dec 18;3:e142. doi: 10.7717/peerj-cs.142. eCollection 2017.
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.
计算机科学提供了大量用于原型设计、编写、运行、测试、验证、共享和重现结果的工具；然而，计算科学却落后了。在最好的情况下，作者可能会将其源代码作为压缩存档提供，并可能确信他们的研究是可重现的。但这并不完全正确。二十多年前，詹姆斯·布赫海特（James Buckheit）和大卫·多诺霍（David Donoho）提出，一篇关于计算结果的文章是广告，而不是学术成果。真正的学术成果是产生结果的完整软件环境、代码和数据。这意味着需要新的工作流程，尤其是在同行评审方面。现有期刊适应缓慢：很少要求提供源代码，而且几乎从未实际执行过以检查它们是否能产生文章中所宣称的结果。《重新科学》（ReScience）是一本同行评审期刊，专注于计算研究，并鼓励对已发表的研究进行明确的复制，推广新的开源实现方式，以确保原始研究能够根据其描述进行复制。为了实现这一目标，整个出版链与其他传统科学期刊截然不同。《重新科学》驻留在GitHub上，在那里，每项计算研究的新实现都与注释、解释和软件测试一同提供。
