r-cubed: An Introductory Workshop on Modern Data Analyses and Workflows for Reproducible Research in R
Reproducibility and open scientific practices are increasingly being requested or required of scientists and researchers, but training on these practices has not kept pace. This course intends to help bridge that gap and covers the fundamentals and workflow of data analysis in R.
This repository contains the lesson, lecture, and assignment material for the course, including the website source files and other associated course administration files.
For more detail on the course, check out the welcome page and the syllabus. For re-using and learning more about the course, check out our paper describing it.
The lectures and lessons in this course are designed to be presented primarily with a participatory live-coding approach. This involves an instructor typing and running code in RStudio in front of the class, while the class follows along using their own computers. Challenges are interspersed in the lesson material, allowing participants to collaboratively work on smaller coding problems for a few minutes. All lesson materials are provided ahead of time on the course website for participants to refer to during lectures.
Throughout the course, participants undertake a group project, wherein they attempt to address a scientific question by applying techniques learned over the course to a (preferably open) dataset. The assignment is primarily code-based and is designed to be completed in RStudio using the Quarto format.
The teaching material is found mainly in these locations:
index.qmd: Contains the overview of the course.preamble/folder: Contains the files necessary for use before the course, for instance the syllabus, schedule, and pre-course tasks.sessions/folder: Contains the files used during the course (e.g. code-along material)appendix/folder: Contains the files used to support the course, such as pre-course tasks, code of conduct, resources, and instructions for instructors.slides/: The lecture slides are rendered into HTML slides from Markdown.
The website is generated from Quarto, so it follows the file and folder structure conventions from that package.
If you are interested in contributing to the course material, please refer to the contributing guidelines. For guidelines on how to be a helper or instructor, check out the For Instructors page.
Please note that the project is released with a Contributor Code of Conduct. By contributing to or being involved in this project, you agree to abide by its terms.
The course is largely designed to be taught in the order given, as each session builds off of the previous ones. The easiest way to use this material is to use it as-is, making use of the tips and instructions found throughout this page. The only thing you might want to make as your own would be the slides, however, they are also good enough to use on their own too.
But if you want to customize a bit more, the best approach is to fork the repository into your own GitHub account and modify it to fit your needs from there. The website is built automatically with GitHub Actions and then published as a website through Netlify. More detail on how to build your own website from the material is outside the scope of this document but you can find more information on Quarto's Publishing page.
To help with general admin tasks of running the course, there is the r3admin R package. For details of the license and acknowledgement of content used from sources, see the license page of the website.
Please cite the material as:
Johnston LW, Juel HB, Lengger B, Witte DR, Chatwin H, Christiansen MR, Isaksen A. r-cubed: Guiding the overwhelmed scientist from random wrangling to Reproducible Research in R. Journal of Open Source Education. 2021 Oct 9;4(44):122.
Or as BibTeX:
@article{Johnston2021,
doi = {10.21105/jose.00122},
url = {https://doi.org/10.21105/jose.00122},
year = {2021},
publisher = {The Open Journal},
volume = {4},
number = {44},
pages = {122},
author = {Luke Johnston and Helene Juel and Bettina Lengger and Daniel Witte and Hannah Chatwin and Malene Christiansen and Anders Isaksen},
title = {r-cubed: Guiding the overwhelmed scientist from random wrangling to Reproducible Research in R},
journal = {Journal of Open Source Education}
}