38  Peer review facilitates package publishing

38.0.1 rOpenSci

aims and goals:

rOpenSci fosters a culture that values open and reproducible research using shared data and reusable software.

We do this by: - Creating technical infrastructure in the form of carefully vetted, staff- and community-contributed R software tools that lower barriers to working with scientific data sources on the web

  • Creating social infrastructure through a welcoming and diverse community

  • Making the right data, tools and best practices more discoverable

  • Building capacity of software users and developers and fostering a sense of pride in their work

  • Promoting advocacy for a culture of data sharing and reusable software.

Source: https://ropensci.org/about/

38.0.2 rOpenSci’s open peer review process

  • Authors submit complete R packages to rOpenSci.

  • Editors check that packages fit into rOpenSci’s scope, run a series of automated tests to ensure a baseline of code quality and completeness, and then assign two independent reviewers.

  • Reviewers comment on usability, quality, and style of software code as well as documentation.

  • Authors make changes in response.

  • Once reviewers are satisfied with the updates, the package receives a badge of approval and joins rOpenSci’s suite of approved pacakges.

  • Happens openly, and publicly on GitHub in issues.

  • Process is quite iterative and fast. After reviewers post a first round of extensive reviews, authors and reviewers chat in an informal back-and-forth, only lightly moderated by an editor.

Source: https://numfocus.org/blog/how-ropensci-uses-code-review-to-promote-reproducible-science

38.0.3 rOpenSci’s Guidance and Standards

What aspects of a package are reviewed?

  • high-level best practices:
    • is the code reusable (e.g. follow the DRY principle)?
    • are sufficient edge cases tested?
    • etc
  • low-level standards:
    • are naming conventions for functions followed?
    • did they make the best choices of dependencies for the package’s intended tasks?
    • etc

Source: https://numfocus.org/blog/how-ropensci-uses-code-review-to-promote-reproducible-science

38.0.4 rOpenSci’s Review Guidebook

38.0.5 rOpenSci-reviewed packages:

38.0.6 Let’s look at an rOpenSci review!

All packages currently under review: https://github.com/ropensci/software-review/issues

38.0.7 What do you get for having your package reviewed by rOpenSci?

  • valuable feedback from the knowledgeable editors and reviewers
  • help with package maintenance and submission of your package to CRAN
  • promotion of your package on their website, blog and social media
  • packages that have a short accompanying paper can be automatically submitted to JOSS and fast-tracked for publication.

38.1 pyOpenSci

  • A new organization, modelled after rOpenSci
  • scope is Python packages
  • First package submitted to pyOpenSci was in May 2019