Among the top challenges of reproducible computational science are the following: 1) creation, curation, usage, and publication of research software; 2) acceptance, adoption, and standardization of open-science practices; and 3) misalignment with academic incentive structures and institutional processes for career progression. I will mainly address the first two here, proposing a praxis of reproducible computational science.
While comprehensive and expert searching may be part of the traditional aspects of academic librarianship, systematic reviews also require transparency and reproducibility of search methodology. This work is supported by use of reporting guidelines and related librarian expertise. This guide provides resources that are useful to librarians assisting with systematic reviews in a broad range of disciplines outside the biomedical sciences. Because the bulk of published literature on systematic reviews is concentrated in the health sciences, some resources are subject-specific in title, but have broader applications.
A paper which analyzes terminologies related to reproducible research -- exploring differences and patterns among them -- aiming to resolve some contradictions.
Prof. Lorena Barba has just posted a reading list for reproducible research that includes ten key papers to understand reproducibility.
This group is for sharing reproducibility related citeable resources within the Moore and Sloan Data Science Environments reproducibility working group effort.