Sustainable computational science: the ReScience initiative.
Fiche publication
Date publication
janvier 2017
Journal
PeerJ. Computer science
Auteurs
Membres identifiés du Cancéropôle Est :
Dr DELSUC Marc-André
Tous les auteurs :
Rougier NP, Hinsen K, Alexandre F, Arildsen T, Barba LA, Benureau FCY, Brown CT, de Buyl P, Caglayan O, Davison AP, Delsuc MA, Detorakis G, Diem AK, Drix D, Enel P, Girard B, Guest O, Hall MG, Henriques RN, Hinaut X, Jaron KS, Khamassi M, Klein A, Manninen T, Marchesi P, McGlinn D, Metzner C, Petchey O, Plesser HE, Poisot T, Ram K, Ram Y, Roesch E, Rossant C, Rostami V, Shifman A, Stachelek J, Stimberg M, Stollmeier F, Vaggi F, Viejo G, Vitay J, Vostinar AE, Yurchak R, Zito T
Lien Pubmed
Résumé
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.
Mots clés
Computational science, GitHub, Open peer-review, Open science, Publication, Replicable, Reproducible, Sustainable
Référence
PeerJ Comput Sci. 2017 ;3:e142