Nüst Daniel, Sochat Vanessa, Marwick Ben, Eglen Stephen, Head Tim, Hirst Tony, Evans Benjamin
Other scientific publication
Computational science has been greatly improved by the use of containers for packaging software and data dependencies. In a scholarly context, the main drivers for using these containers are transparency and support of reproducibility; in turn, a workflow's reproducibility can be greatly affected by the choices that are made with respect to building containers. In many cases, the build process for the container's image is created from instructions provided in a Dockerfile format. In support of this approach, we present a set of rules to help researchers write understandable Dockerfiles for typical data science workflows. By following the rules in this article, researchers can create containers suitable for sharing with fellow scientists, for including in scholarly communication such as education or scientific papers, and for effective and sustainable personal workflows.
Release year: 2020
Language in which the publication is written: English
Event: OSF Preprints
Link to the full text: https://osf.io/fsd7t/download