17.7 Organize an R Markdown project into a research website with workflowr
The workflowr package (Blischak, Carbonetto, and Stephens 2020, 2019) can help you organize a (data analysis) project with a project template and the version control tool GIT. Every time you make a change to the project, you can log the change, and workflowr can build a website corresponding to that particular version of your project. This means that you will be able to view the full history of your analysis results. Although this package uses GIT as the backend for version control, you do not really have to be familiar with GIT. The package provides R functions that do the GIT operations under the hood, and you only need to call these R functions. Furthermore, workflowr automates best practices for reproducible code. Each time an R Markdown document is rendered, workflowr automatically sets a seed with
set.seed(), records the session information with
sessionInfo(), and scans for absolute file paths, etc. Please see the package documentation for how to get started and more information.
The main author of workflowr, John Blischak, has also put together a non-exhaustive list of R packages and guides related to the workflow of R projects, which can be found in this GitHub repo: https://github.com/jdblischak/r-project-workflows.
Blischak, John, Peter Carbonetto, and Matthew Stephens. 2020. Workflowr: A Framework for Reproducible and Collaborative Data Science. https://github.com/jdblischak/workflowr.
Blischak, John D, Peter Carbonetto, and Matthew Stephens. 2019. “Creating and Sharing Reproducible Research Code the Workflowr Way [Version 1; Peer Review: 3 Approved].” F1000Research 8 (1749). https://doi.org/10.12688/f1000research.20843.1.