Scientists are increasingly dependent on computational techniques to analyse large volumes of data. These computational methods are often tailored to the particular analysis in mind, and as such are valuable research outputs. Furthermore, unlike experimental techniques, computational methods can be easily shared. However, at least in neuroscience, computational methods are not routinely shared upon publication of associated manuscripts.
To improve this situation, we have worked with the editors of Nature Neuroscience to establish a pilot code review project. Once papers have been approved in principle for publication, authors can opt-in to the code review. The code (and data) will be checked to see if independent reviewers can reproduce key findings of the paper. The details of the code review process are outlined in the editorial, and we have written a commentary to describe good practice for sharing of code and data. For example, we suggest the minimum requirement for sharing is that sufficient code and data be provided to regenerate a key figure/table of the paper. This follows the well-established requirements for submitting code to modeldb.
Although our current guidelines are focused around code and data in Neuroscience, most of our suggestions apply across many scientific disciplines. Just as journals (and funders) now require the sharing of data underlying a research paper, we believe the underlying code should also be freely shared. We hope that other journals will adapt appropriate policies to allow for the long-term sharing and reuse of scientific code. By sharing the code and data relating to research articles, communities will be able to reproduce and extend upon each other’s work. This should lead to more robust scientific results and reduce duplication of effort.
This project emerged from discussions at a workshop to encourage sharing in neuroscience, held in Cambridge, December 2014. It was financially supported and organized by the International Neuroinformatics Coordinating Facility, with additional support from the Software Sustainability Institute.
 Extending transparency to code. Nat Neurosci 20:761–761. (Article)
 Eglen SJ, Marwick B, Halchenko YO, Hanke M, Sufi S, Gleeson P, Angus Silver R, Davison AP, Lanyon L, Abrams M, Wachtler T, Willshaw DJ, Pouzat C, Poline J-B (2017) Toward standard practices for sharing computer code and programs in neuroscience. Nat Neurosci 20:770–773. (Article)