I have included a handful of links to papers, software packages and tutorials/manuals about some tools I mention in my talk. Pull requests or issues on additional ones to include are welcome.
Examples of Research Compendia on GitHub
Below are a few links to real world examples of research compendia in R. To have a minimal compendium, all you really need is a valid
DESCRIPTION file containing a handful of fields such as type, name, version and dependencies. See Marwick et al 2017 for a detailed description of the different types of compendia.
Software packages related to research compendia
rrtoolsby Ben Marwick (also the author of the packaging data analysis paper mentioned above) extends functions in
devtoolsand provides instructions, templates, and functions to make a basic compendium suitable for doing reproducible research with R.
usethisMany of the major function in
rrtoolsare imported from
usethis.A savvy user can get by setting up and maintaining a compendium purely with
goodpractice- Designed to help you build more robust packages, the package does a deep dive on your package contents and provide advice on syntax pitfalls to avoid, code formatting suggestions, and helps you improve overall package structure.
rticlespackage by JJ has numerous journal templates and together with Rstudio addins like word
piggyback, [docs]: This clever R package allows you to attach arbitrary data (or other) files (upto 2gb each) to a GitHub release. Given GitHub's fast CDN, this would be an easy way to quickly attach large files to a compendium and read them back in a local/collaborator/remote environment very easily. As always be sure to archive a long-term copy on Zenodo.
arkdb[docs]: This package allows you to archive and unarchive databases as flat text files.
repo2dockerA Python module that will turn any repo (or local folder) into a Docker Image.
Other hosted Binder hubs
Setting up Binder for your analysis
I have captured all the various ways to set up mybinder with a R project in a separate document.
Are you interested in setting up or hosting a binderhub for the R community? Get in touch via the issues.
Software packages related to setting up computational environments
Containerit. Detailed blog post This sweet package will generate a Dockerfile for you by examining the code inside a folder or just from your session info. This is analogous to
repo2dockerbut is very R centric
stevedoreAlthough there are a few docker clients (docker, harbor), this is my recommendation for managing docker containers from inside R.
drake- An R-focused pipeline toolkit for reproducibility and high-performance computing. Install the package from here or CRAN.
bookdownguide on how to setup and use drake for projects of varying levels of complexity.
Real world drake examples
Many thanks to Chris Holdgraf, Carl Boettiger, Will Landau, and Ben Marwick for various discussions on these topics. Also thanks to Ciera Martinez, Kara Woo, and Nick Tierney for comments on the presentation.