| Time | Module |
|---|---|
| 15:30 - 16:20 | Hello Quarto |
| 16:20 - 16:25 | Break |
| 16:25 - 16:55 | Documents |
| 16:55 - 17:15 | Websites |
| 17:15 - 17:25 | Publish |
| 17:25 - 17:30 | Wrap-up |
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 Day 4 of the ETH Research Data Management Summer School 2024 in room CHN G 42 at the following time:
- 13 June 2024 - 15:30 to 17:30 CET
Please ensure you have the following available:
- a laptop, connected to wifi
- a browser installation on your laptop that is not the Internet Explorer
Prior to the course, 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 Wednesday, 12th June 2024.
- Step 5: Prepare information for an About page for a personal website.
- Step 6: Read Wilson et al. (2017) (optional)
Course schedule
Learning objectives
This course has the following learning objectives
Learn to use the Quarto file format and the RStudio IDE visual editing mode to produce scholarly documents with footnotes, cross-references, figures, and tables.
Learn to use Quarto Pub to publish a website and share research with a broader audience.
The complete abstract for this course is available at: Abstract
Thanks!
Thank you for working through these steps. We are looking forward to meeting you at 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.