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CCMcr19 ReproHack slides |
ReproHack, introduction, slides |
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Contains all event information and links to materials
- Research Software Engineer University of Sheffield
- Software Peer Review Editor rOpenSci
- Co-organiser Sheffield R Users Group
I believe there's lots to learn about Reproducibility from working with real published projects.
Stitch!
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Project review and team formation
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Select and register your project
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Work on your project!
- Finished early? Consider attempting replication!
- Replications could be considered for publication in ReScience C Journal
ReScience C is an open-access peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible.
- Repeating a published protocol
- Respecting its spirit and intentions
- Varying the technical details, e.g. using different software, initial conditions, etc.
Change something that everyone believes shouldn’t matter, and see if the scientific conclusions are affected
- Regroup part way through to discuss progress and troubleshoot any sticking points
- Feedback to authors using form by end of session
- Feedback to group at the end
Event governed by Carpentries Code of Conduct
- Fine to work individually
- Register your team and paper / topic by opening a new issue. <bit.ly/CCMcr19-ReproHack>
- Add your details to the hackpad.
- Briefly describe the approach to reproducibility the paper has taken.
- Anything in particular you like about the paper's approach?
- Anything you're having difficulty with?
- Please complete the feedback form for authors <bit.ly/CCMcr19-ReproHack-feedback>
- Feel free to take notes on the hackpad
- So, how did you get on?
- Final comments
- One thing you liked, one thing that can be improved (use post it's if you prefer)
- The Turing Way: a lightly opinionated guide to reproducible data science.
- Packaging data analytical work reproducibly using R (and friends): how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools