A World of Possibilities for Reproducible Publishing with Quarto

Abstract Number:

1309 

Submission Type:

Invited Paper Session 

Participants:

Mine Cetinkaya-Rundel (1), Andrew Bray (2), Charlotte Wickham (3), Hadley Wickham (4), Mine Cetinkaya-Rundel (1), Emil Hvitfeldt (3), Tracy Teal (5)

Institutions:

(1) Duke University + Posit, N/A, (2) Reed College, N/A, (3) Posit, N/A, (4) RStudio, N/A, (5) N/A, N/A

Chair:

Andrew Bray  
Reed College

Session Organizer:

Mine Cetinkaya-Rundel  
Duke University + Posit

Speaker(s):

Charlotte Wickham  
Posit
Hadley Wickham  
RStudio
Mine Cetinkaya-Rundel  
Duke University + Posit
Emil Hvitfeldt  
Posit
Tracy Teal  
N/A

Session Description:

Quarto is an open-source scientific and technical publishing system that unifies and extends the R Markdown ecosystem. This feature-rich system is suitable for reproducible data analysis at all levels, from a simple homework assignment in an introductory statistics course to a computing-intensive, multi-language project. This session aims to introduce Quarto to those who are new to it as well as help those who have worked with it before diving deeper to help them find features of the toolkit that might help them in various aspects of their work. The session features five speakers who have been developing, using, and teaching Quarto over the last three years. The speakers will share their experiences with a wide range of features of Quarto, from creating single documents to complex book projects. The talks will also touch on multiple programming languages (R and Python) and tools (RStudio and Jupyter Notebooks). Topics discussed will include tips for creating highly stylized, reproducible slide decks, authoring technical books and documentation, and publication-ready scientific manuscripts with embedded computing. The session will also feature a walkthrough of making a personal/academic/research group website with a blog. The talks will feature code examples in R and Python, and one talk specifically will focus on using Quarto with Jupyter Notebooks and Python.

Sponsors:

Section on Statistical Computing 2
Section on Statistical Graphics 1
Section on Statistics and Data Science Education 3

Theme: Statistics and Data Science: Informing Policy and Countering Misinformation

No

Applied

Yes

Estimated Audience Size

Large (150-275)

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.

I understand