Publishing computational research -- A review of infrastructures for reproducible and transparent scholarly communication

Funding agencies increasingly ask applicants to include data and software management plans into proposals. In addition, the author guidelines of scientific journals and conferences more often include a statement on data availability, and some reviewers reject unreproducible submissions. This trend towards open science increases the pressure on authors to provide access to the source code and data underlying the computational results in their scientific papers. Still, publishing reproducible articles is a demanding task and not achieved simply by providing access to code scripts and data files. Consequently, several projects develop solutions to support the publication of executable analyses alongside articles considering the needs of the aforementioned stakeholders. The key contribution of this paper is a review of applications addressing the issue of publishing executable computational research results. We compare the approaches across properties relevant for the involved stakeholders, e.g., provided features and deployment options, and also critically discuss trends and limitations. The review can support publishers to decide which system to integrate into their submission process, editors to recommend tools for researchers, and authors of scientific papers to adhere to reproducibility principles.