Pre-course work: Quarto - authoring and publishing tools for collaborative scientific writing

Thank you for your interest in this course. Your course instructor Lars Schöbitz is looking forward to meet you.

We will meet on Zoom at the following times:

Please ensure you have the following available:

This course uses participatory live coding techniques and it is advantageous to have a second screen available. One screen can be used to watch the Zoom meeting and the other screen can be used to follow along with the live coding.

Prior to Day 1, there is some pre-work for you to do. This pre-work will ensure that we can focus our time together on learning instead of setting up infrastructure.

What do I need to prepare before Day 1?

Prior to Day 1, please complete the following seven steps:

  • Step 1: Register your ORCID iD
  • Step 2: Log into Posit Cloud and join the course workspace
  • Step 3: Create an account for Quarto Pub
  • Step 4: Fill out the pre-course survey by Tuesday, 2nd April
  • Step 5: Read Wilson et al. (2017) and prepare for a discussion

Day 1

Time Module
12:00 - 13:00 Hello Quarto
13:00 - 13:10 Break
13:10 - 14:00 Documents

Day 2

Time Module
12:00 - 12:50 Presentations
12:50 - 13:00 Break
13:00 - 13:30 Websites
13:30 - 13:50 Publish
13:50 - 14:00 Wrap-up

Learning objectives

This course has the following learning objectives

  1. Learn to use the Quarto file format and the RStudio IDE visual editing mode to produce scholarly documents with citations, footnotes, cross-references, figures, and tables.

  2. Learn to use Quarto Pub to publish a website and share research with a broader audience.

Thanks!

Thank you for working through these steps. You will hear from us again a day before the start of the course.

Attribution

Content was re-used from a workshop hosted by Mine Çetinkaya-Rundel at the 2023 Symposium on Data Science and Statistics and stored at https://github.com/mine-cetinkaya-rundel/quarto-sdss. The original content is licensed under a Creative Commons Attribution 4.0 International License.

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Wilson, Greg, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, and Tracy K. Teal. 2017. “Good Enough Practices in Scientific Computing.” PLOS Computational Biology 13 (6): e1005510. https://doi.org/10.1371/journal.pcbi.1005510.