Sustainable computational science : the

@inproceedings{Rougier2018SustainableCS,
  title={Sustainable computational science : the},
  author={Nicolas P. Rougier and Konrad Hinsen and Fr{\'e}d{\'e}ric Alexandre and omas Arildsen and Lorena A. Barba and Fabien and C. Y. Benureau and C. Titus Brown and Pierre de Buyl and Ozan Caglayan and Andrew P. Davison and Michael R. Andre and Delsuc and Georgios Detorakis and Alexandra K. Diem and Damien Drix and Pierre Enel and Benoı̂t Girard and Olivia Guest and Matt G. Hall and Rafael Neto Henriques and Xavier Hinaut and Kamil S. Jaron and Kasbparast Jr. Mehdi and Khamassi and Almar Klein and Tiina Manninen and Pietro Marchesi and Dan McGlinn and Lemell Christoph and Metzner and Owen L. Petchey and Hans Ekkehard Plesser and Timoth{\'e}e Poisot and Karthik Ram and Yoav and Ram and Etienne B. Roesch and Cyrille Rossant and Vahid Rostami and Aaron R Shifman and Joseph Stachelek and Marcel Stimberg and Frank Stollmeier and Federico Vaggi and Guillaume Viejo and Julien Vitay and Anya and Vostinar and Roman Yurchak and Tiziano Zito},
  year={2018}
}
Computer science o‚ers 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 con€dent their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. ‘e… CONTINUE READING