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Diversity in Reproducibility

Olivia Guest 1 Nicolas P. Rougier 2 
2 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
Abstract : In our previous contribution, we proposed computational modelling-related definitions for replicable, i.e., experiments within a model can be recreated using its original codebase, and reproducible, i.e., a model can be recreated based on its specification. We stressed the importance of specifications and of access to codebases. Furthermore, we highlighted an issue in scholarly communication — many journals do not require nor facilitate the sharing of code. In contrast, many third-party services have filled the gaps left by traditional publishers (e.g., Binder, 2016; GitHub, 2007; Open Science Framework, 2011; ReScience, 2015). Notwithstanding, journals and peers rarely request or expect use of such services. We ended by asking: are we ready to associate codebases with articles and are we prepared to ensure computational theories are well-specified and coherently implemented?
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Submitted on : Monday, April 24, 2017 - 8:12:09 PM
Last modification on : Saturday, June 25, 2022 - 7:44:23 PM
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  • HAL Id : hal-01513273, version 1



Olivia Guest, Nicolas P. Rougier. Diversity in Reproducibility. IEEE CIS Newsletter on Cognitive and Developmental Systems, IEEE CIS Technical Committee on CDS, 2016, 13 (2). ⟨hal-01513273⟩



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