Under the hood

Modified

April 23, 2026

About

This page provides additional information about how the website was created.

Overview

The website uses Quarto to generate documents and GitHub pages to serve the site.

The typical workflow is as follows:

  1. Merge any pending GitHub pull requests at github.com/penn-state-open-science/bootcamp-2026.
  2. From RStudio on a local machine, open the bootcamp-2026 project.
  3. Pull the merged code.
  4. Edit any files that need to be updated.
  5. Render specific Quarto files in a terminal using quarto render this-file.qmd or the entire site using quarto render.
  6. Inspect the rendered site in docs/.
  7. If further changes are needed, repeat 4-6.
  8. Commit the changes and push to GitHub.
Note

You may inspect the Markdown for each page on the site by clicking on the </> Code button in the upper right.

Pages with more extensive data processing (e.g., registration.qmd) have “chunk-specific” buttons that hide and reveal the code.

Styles

This site makes use of a Sassy Cascading Style Sheet (SCSS) that makes the site’s styling compatible with Penn State’s Strategic Communication recommendations for visual identity, specifically color and typography.

The file is located in include/css/psu.scss.

Packages

We used R v. 4.6.0 (R Core Team, 2026) and the following R packages: assertthat v. 0.2.1 (Wickham, 2019), here v. 1.0.2 (Müller, 2025), janitor v. 2.2.1 (Firke, 2024), knitr v. 1.51 (Xie, 2014, 2015, 2025), qrcode v. 0.3.0 (Onkelinx & Teh, 2024), renv v. 1.1.4 (Ushey & Wickham, 2025), reticulate v. 1.46.0 (Ushey, Allaire, & Tang, 2026), rmarkdown v. 2.31 (Allaire et al., 2026; Xie, Allaire, & Grolemund, 2018; Xie, Dervieux, & Riederer, 2020), shiny v. 1.13.0 (Chang et al., 2026), tidyverse v. 2.0.0 (Wickham et al., 2019).

References

Allaire, J., Xie, Y., Dervieux, C., McPherson, J., Luraschi, J., Ushey, K., … Iannone, R. (2026). rmarkdown: Dynamic documents for r. Retrieved from https://github.com/rstudio/rmarkdown
Chang, W., Cheng, J., Allaire, J., Sievert, C., Schloerke, B., Aden-Buie, G., … Borges, B. (2026). shiny: Web application framework for r. https://doi.org/10.32614/CRAN.package.shiny
Firke, S. (2024). janitor: Simple tools for examining and cleaning dirty data. https://doi.org/10.32614/CRAN.package.janitor
Müller, K. (2025). here: A simpler way to find your files. https://doi.org/10.32614/CRAN.package.here
Onkelinx, T., & Teh, V. (2024). qrcode: Generate QRcodes with r. Version 0.3.0. https://doi.org/10.5281/zenodo.5040088
R Core Team. (2026). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://doi.org/10.32614/R.manuals
Ushey, K., Allaire, J., & Tang, Y. (2026). reticulate: Interface to “Python”. https://doi.org/10.32614/CRAN.package.reticulate
Ushey, K., & Wickham, H. (2025). renv: Project environments. https://doi.org/10.32614/CRAN.package.renv
Wickham, H. (2019). assertthat: Easy pre and post assertions. https://doi.org/10.32614/CRAN.package.assertthat
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Xie, Y. (2014). knitr: A comprehensive tool for reproducible research in R. In V. Stodden, F. Leisch, & R. D. Peng (Eds.), Implementing reproducible computational research. Chapman; Hall/CRC.
Xie, Y. (2015). Dynamic documents with R and knitr (2nd ed.). Boca Raton, Florida: Chapman; Hall/CRC. Retrieved from https://yihui.org/knitr/
Xie, Y. (2025). knitr: A general-purpose package for dynamic report generation in R. Retrieved from https://yihui.org/knitr/
Xie, Y., Allaire, J. J., & Grolemund, G. (2018). R markdown: The definitive guide. Boca Raton, Florida: Chapman; Hall/CRC. Retrieved from https://yihui.org/rmarkdown/
Xie, Y., Dervieux, C., & Riederer, E. (2020). R markdown cookbook. Boca Raton, Florida: Chapman; Hall/CRC. Retrieved from https://yihui.org/rmarkdown-cookbook