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R Markdown at a glance
R Markdown
R Markdown grew from the knitr and RStudio ecosystem and became the dominant reproducible-reporting format for R-centered data science before Quarto generalized the model across more languages.
FFF at a glance
FFF
Hasselblad's workflow tooling treated raw capture and high-end processing as parts of one integrated medium-format imaging environment, which is why formats like FFF survive in specialist archives.
Format comparison
| Feature | R Markdown | FFF |
|---|---|---|
| File type | Document | Image |
| Extensions |
|
|
| MIME type |
|
|
| Created year | 2012 | 2002 |
| Inventor | Yihui Xie (RStudio / knitr) | Hasselblad |
| Status | active | proprietary |
| Primary use cases |
|
|
| Vector scaling | Not supported | Not supported |
When to use each format
When to use R Markdown
- Your source file is already in R Markdown.
- Preserve source expectations before exporting to FFF.
- R Markdown is commonly used in document workflows.
When to use FFF
- Your target workflow expects FFF.
- Improve delivery compatibility with FFF.
- FFF is commonly used in image workflows.
FAQs
Why convert R Markdown to FFF?
Convert to FFF when maintaining compatibility with a specialized high-end imaging archive or recovering source material from that ecosystem.
It is mainly an archival and specialist workflow format.
What changes when converting R Markdown to FFF?
This conversion changes how the format behaves in downstream tools and delivery environments.
What should I review after converting R Markdown to FFF?
Validate output quality on representative files and confirm the target format behaves correctly in the destination workflow.