This is a work-in-progress emerging from the DataONE Prov-a-thon
meeting (August 2017, New
Mexico). We’re still working on the guidelines, and warmly welcome
feedback, especially as a issue
post.
DataONE Reproducible Research Compendia Onboarding
Thank you for considering submitting your research compendium for the
DataONE reproducibility review process. All compendia go through a
process of open peer review to ensure a consistent level of quality for
our users, inspired by the
rOpenSci package
onboarding process. This process also allows us to ensure that your
compendia meets our guidelines and provides opportunity for discussion
where exceptions are requested. The origin explains why parts of the
guidelines assume a compendium based the programming language
R and its tools, but compendia in other
languages and from all communities of research are welcome and
documentation will be steadily improved.
Why submit your compendia for DataONE review?
- First, and foremost, we hope you submit your compendia for review
because you value the feedback. We aim to provide useful
feedback to compendia authors and for our review process to be open,
non-adversarial, and focused on improving software quality.
- Once aboard, your compendia will continue to receive support from
the DataONE community. You’ll retain ownership and control of of
your compendia, but we can help with ongoing maintenance issues such
as those associated with updates to R and dependencies.
- Compendia reviewed here can be cross-listed with other
repositories.
Why review compendia for DataONE?
- As in any peer-review process, we hope you choose to review to
give back to the DataONE and scientific communities. Our mission
to expand access to scientific data and promote a culture of
reproducible research is only possible through the volunteer efforts
of community members like you.
- Review is a two-way conversation. By reviewing compendia, you’ll
have the chance to continue to learn development practices from
authors and other reviewers.
- The open nature of our review process allows you to network and
meet colleagues and collaborators through the review process. Our
community is friendly and filled with supportive members expert in R
development and many other areas of science and scientific
computing.
- To volunteer to be one of our reviewers, please let us know by
opening a new
issue
and providing your contact information and areas of expertise. We
are always looking for more reviewers with both experience in
reproducible research and domain expertise in the fields compendia
are used
for.
How to submit your compendium for review
- Consult our policies see if your compendia meets our
criteria for review
- If you are unsure whether a compendium meets our criteria, feel
free to open an issue as a pre-submission inquiry to ask if the
compendium is appropriate.
- Follow our compendia style guide to ensure
your compendia meets our style and quality criteria.
- Next, open a new
issue
in this repository and fill out the template.
- An editor will review your submission within 5 business
days and respond with next steps (see editors
guide for details). The editor may assign the
compendia to reviewers, request that the compendia be updated to
meet minimal criteria before review, or reject the compendia due to
lack of fit or overlap.
- If your compendia meets minimal criteria, the editor will assign 1-3
reviewers. They will be asked to provide reviews as comments on your
issue within 3 weeks.
- We ask that you respond to reviewers’ comments within 2 weeks of the
last-submitted review, but you may make updates to your compendia or
respond at any time. We encourage ongoing conversations between
authors and reviewers. If you update your compendium, please leave a
short notice in your issue about the change. See the reviewing
guide for more details.
- Once your compendium is approved, we will provide further
instructions on transferring your repository to the DataONE
repository.
Our code of conduct is mandatory for
everyone involved in our review process.
Our review process is always in development, and we encourage feedback
and discussion on how to improve the process on our issue
tracker.
Useful documents in this repository
Editors and reviewers
DataONE’s onboarding process is run by: