Welcome back

Loading data and reporting models

Daniela Palleschi

April 29, 2026

Overview

• Review
• Today’s topics
• Motivating dynamic reports

publishr-workshop GitHub repo

• https://github.com/daniela-palleschi/publishr-workshop
• make sure you have the new:
  • exercises/: 01-cleaning.qmd, 02-analysis.qmd, 03-manuscript.qmd
  • R/ folder
  • updated references.bib
  • data/raw/data_example.csv

Review: Quarto foundations

• RProjects
• Writing in Quarto: Markdown
• Output formats: PDF/tex, Word, HTML

Today

• adding data to our scripts
• running a model in an analysis script
• reporting a model in a manuscript script

Motivating dynamic reports

Why reproducibility matters

• Open science encourages transparent, verifiable, and reusable research
• FAIR principles: data and code should be Findable, Accessible, Interoperable, and Reusable
• in practice: share your data, share your code, document your workflow

Modular analyses

• separate your workflow into distinct scripts: data cleaning, modelling, reporting
• each script does one thing and does it well
• changes upstream (e.g. a preprocessing decision) propagate automatically downstream

Dynamic reports

• a dynamic report links prose directly to code and data
• no more copy-pasting results — values update when the data or model changes
• reduces human error and makes your work easier to reproduce and audit

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