Quarto (software)
| Quarto | |
|---|---|
| Developer | Posit PBC |
| Initial release | July 2022 |
| Operating system | Cross-platform |
| Platform | x86-64, ARM64 |
| Type | Electronic publishing, Literate programming |
| License | GNU General Public License |
| Website | quarto |
Quarto is a free and open-source scientific and technical publishing system developed by Posit PBC (formerly RStudio). It is a command-line tool built on Pandoc that converts plain text documents mixed with executable code including Python, R, Julia, and Observable JavaScript into static formats including PDF, HTML, MS Word, Powerpoint, ePub, RevealJS, and MediaWiki.[1][2]
Quarto is considered the successor to R Markdown, extending support beyond the R ecosystem to support a broader range of data science languages and environments.[3]
History
[edit]Quarto was officially announced in July 2022 at the `rstudio::conf(2022)` conference.[1] The release coincided with the corporate rebranding of the developer from RStudio to Posit. This rebranding and the launch of Quarto reflected a strategic shift to support language-agnostic data science workflows, specifically acknowledging the growing adoption of Python alongside R in scientific research.[1]
Design and implementation
[edit]Quarto is implemented as a Command Line Interface (CLI), which allows it to function independently of any specific Integrated Development Environment (IDE). However, extensions are available for IDEs such as RStudio, Visual Studio Code, and Jupyter.[4]
File formats
[edit]The native source format for Quarto uses the `.qmd` extension. These files are plain text files that combine Markdown with executable code blocks. Quarto can also render existing Jupyter Notebooks (`.ipynb`) into publication-quality documents without converting them to Markdown first.[1]
Functionality
[edit]Quarto is designed to support reproducible research workflows. By integrating narrative and code into a single source file, the software is intended to ensure that analysis and reporting remain consistent.[5]
Key features include:
- Scientific Publishing: Native support for academic citations, bibliographies, and cross-referencing of figures, tables, and equations.[4]
- Multi-format Output: A single source file can be rendered into dozens of formats, including HTML websites, PDF (via LaTeX), EPUB, and presentations (e.g., Reveal.js, Microsoft PowerPoint).[4][2]
Adoption
[edit]Quarto has been adopted in various institutions for technical reporting, official statistics, open science workflows and documentation.
- The United States Geological Survey (USGS) has released templates and workflows for using Quarto to generate reproducible scientific manuscripts.[6]
- Fisheries and Oceans Canada utilizes Quarto for generating reproducible spatial reports.[7]
- The Deutsche Bundesbank (German Central Bank) integrates Quarto into its production of official statistics to automate "publication-ready visualisations."[8]
- The Bank for International Settlements (BIS) identifies Quarto as a standard platform for conducting deep, reproducible analysis in central banking.[9]
See also
[edit]
References
[edit]- ^ a b c d Machlis, Sharon (2022-07-27). "What is Quarto? RStudio quietly rolls out next-generation R Markdown". InfoWorld. Retrieved 2024-01-01.
- ^ a b "All Formats". Quarto Documentation. Posit PBC. Retrieved 2025-11-29.
- ^ Hofman, N.; Heer, J. (2023). "Living Papers: A Language Toolkit for Augmented Scholarly Communication". Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. New York, NY, USA: Association for Computing Machinery. pp. 1–13. doi:10.1145/3586183.3606791.
- ^ a b c Cook, Joshua J. (2024). "An introduction to Quarto: A Versatile Open-source Tool for Data Reporting and Visualization" (PDF). PharmaSUG 2024 Proceedings. PharmaSUG.
- ^ "Open-access Open Science in Three Acts: Foundations, Practice, and Implementation". Brazilian Administration Review. 22 (3). SciELO. 2025. doi:10.1590/1807-7692bar2025250162.
- ^ Erickson, R.A.; et al. (2024). "A reproducible manuscript workflow with a Quarto template". United States Geological Survey.
- ^ Stoyel, Quentin; et al. (2022). An open, efficient, and transparent spatial reproducible reporting tool for data discovery and science advice (PDF) (Technical report). Fisheries and Oceans Canada. 3495.
- ^ Doll, Hendrik Christian; Ollech, Daniel (2024). "Data-driven visualisations for official statistics – A case study implementing corporate design in R" (PDF). Romanian Statistical Review. 1: 3–18.
- ^ Araujo, Douglas; et al. (2024). "Data science in central banking: applications and tools" (PDF). IFC Bulletin. 59. Bank for International Settlements.