About This Project

Credits, methodology, and how this site was built

The Story Behind This Site

This website was born from a simple question: What are the most important data visualizations in the history of public health?

What started as a research conversation evolved into a fully realized teaching resource — 25+ landmark visualizations, spanning 180 years, recreated in R and organized for medical students. The entire project — from initial research to final code — was developed in a single collaborative session between a human and an AI.

Credits

Conceptualized & Directed By

Dr Abhijit P Pakhare, Professor, Community and Family Medicine, All India Institute of Medical Sciences, Bhopal

The idea, the scope, the editorial direction, and the pedagogical framing of this project were driven entirely by a human educator with a vision: to help medical students understand that data visualization is not a decorative skill — it is a clinical and public health superpower.

Key contributions:

Identified the need for a curated, historically grounded teaching resource
Directed the focus toward public health and epidemiology (rather than general data viz)
Requested the India-specific section to ground the resource in the local health system context
Provided editorial judgment on which visualizations matter most and why
Shaped the pedagogical approach: historical narrative + R recreation + discussion prompts

Developed By

Claude (Anthropic) Claude Opus 4.6 — February 2026

The research, writing, R code, Quarto site architecture, and visualization recreations were produced by Claude, Anthropic’s AI assistant, working under the direction and editorial guidance of the human collaborator.

Technical contributions:

Researched and identified 25 landmark public health visualizations with citations
Organized them into five chronological eras plus an India-focused section
Wrote all narrative text, historical context, and teaching callouts
Created all R code for visualization recreations (using ggplot2, HistData, survival, gapminder, and other packages)
Designed the Quarto website structure, navigation, and custom CSS
Produced the README, installation script, and deployment documentation

Methodology

How Visualizations Were Selected

The 25 core visualizations (plus 7 India-focused additions) were selected based on:

Historical impact — Did this visualization change policy, funding, or clinical practice?
Methodological significance — Did it introduce a new way of seeing health data?
Pedagogical value — Can medical students learn something transferable from it?
Diversity of approaches — Maps, charts, curves, dashboards, models, and even physical objects (the AIDS Quilt)
Chronological coverage — From 1843 to the present day

Data Sources

Original historical data: Used where available via R packages (HistData for Snow and Nightingale, gapminder for Rosling-style charts, survival for Kaplan-Meier demonstrations)
Simulated data: Where original datasets are not publicly available, data was simulated to match documented patterns and published statistics. All simulated data is clearly labelled.
Approximate data: Some charts use approximate values drawn from published reports (WHO, CDC, UNAIDS, GBD, NFHS). These are cited in chart captions.

A Note on Simulated Data

Several visualizations on this site use simulated data rather than original datasets. This is done for pedagogical reasons — the goal is to demonstrate the type of visualization and its historical significance, not to present the data as authoritative. Do not cite the specific numbers from these charts in academic work. Instead, consult the original sources linked throughout the site.

Technical Details

Built With

Component	Technology
Site framework	Quarto (R-based static site generator)
Programming language	R (≥ 4.2)
Core plotting	ggplot2
Data manipulation	dplyr, tidyr
Historical data	HistData (Snow, Nightingale)
Global health data	gapminder
Survival analysis	survival
Treemaps	treemapify
Styling	Custom CSS + Cosmo theme

Deployment

This is a static website that can be deployed to GitHub Pages, Netlify, or any web server. See the README for instructions.

Pedagogical Philosophy

This site is designed around three principles:

History teaches method. By seeing how Nightingale, Snow, Doll, and Rosling chose to present data, students learn transferable design principles — not just R syntax.
Code transparency builds trust. Every chart has a “Show R Code” button. Students can see exactly how each visualization was built, modify parameters, and learn by doing.
Discussion drives learning. Each era ends with discussion questions designed to connect historical visualizations to modern clinical and public health practice.

License & Reuse

This site is intended as a free educational resource. You are welcome to:

Use it in your teaching (with attribution)
Modify the code for your own courses
Adapt the content for different audiences

Please credit both the human director and Claude (Anthropic) if you redistribute or adapt this work.

Acknowledgments

The creators of the R packages used throughout this site
The original scientists, epidemiologists, and data artists whose work is honoured here — from William Farr to the volunteers at covid19india.org
The medical students for whom this was built: may you see data not as a chore, but as a tool that saves lives

A Final Thought: This project is itself a data point in the story of AI and education. A human had a pedagogical vision; an AI had the capacity to research, write, and code at scale. Neither could have produced this alone. The future of teaching may look a lot like this collaboration.

--- title: "About This Project" subtitle: "Credits, methodology, and how this site was built" --- ::: {.hero-banner} ## A Collaboration Between Human Curiosity and AI Capability ::: ## The Story Behind This Site This website was born from a simple question: *What are the most important data visualizations in the history of public health?* What started as a research conversation evolved into a fully realized teaching resource — 25+ landmark visualizations, spanning 180 years, recreated in R and organized for medical students. The entire project — from initial research to final code — was developed in a single collaborative session between a human and an AI. --- ## Credits ### Conceptualized & Directed By **Dr Abhijit P Pakhare, Professor, Community and Family Medicine, All India Institute of Medical Sciences, Bhopal** The idea, the scope, the editorial direction, and the pedagogical framing of this project were driven entirely by a human educator with a vision: to help medical students understand that **data visualization is not a decorative skill — it is a clinical and public health superpower.** Key contributions: - Identified the need for a curated, historically grounded teaching resource - Directed the focus toward public health and epidemiology (rather than general data viz) - Requested the India-specific section to ground the resource in the local health system context - Provided editorial judgment on which visualizations matter most and why - Shaped the pedagogical approach: historical narrative + R recreation + discussion prompts ### Developed By **Claude (Anthropic)** *Claude Opus 4.6 — February 2026* The research, writing, R code, Quarto site architecture, and visualization recreations were produced by Claude, Anthropic's AI assistant, working under the direction and editorial guidance of the human collaborator. Technical contributions: - Researched and identified 25 landmark public health visualizations with citations - Organized them into five chronological eras plus an India-focused section - Wrote all narrative text, historical context, and teaching callouts - Created all R code for visualization recreations (using ggplot2, HistData, survival, gapminder, and other packages) - Designed the Quarto website structure, navigation, and custom CSS - Produced the README, installation script, and deployment documentation --- ## Methodology ### How Visualizations Were Selected The 25 core visualizations (plus 7 India-focused additions) were selected based on: 1. **Historical impact** — Did this visualization change policy, funding, or clinical practice? 2. **Methodological significance** — Did it introduce a new way of seeing health data? 3. **Pedagogical value** — Can medical students learn something transferable from it? 4. **Diversity of approaches** — Maps, charts, curves, dashboards, models, and even physical objects (the AIDS Quilt) 5. **Chronological coverage** — From 1843 to the present day ### Data Sources - **Original historical data**: Used where available via R packages (`HistData` for Snow and Nightingale, `gapminder` for Rosling-style charts, `survival` for Kaplan-Meier demonstrations) - **Simulated data**: Where original datasets are not publicly available, data was simulated to **match documented patterns and published statistics**. All simulated data is clearly labelled. - **Approximate data**: Some charts use approximate values drawn from published reports (WHO, CDC, UNAIDS, GBD, NFHS). These are cited in chart captions. ### A Note on Simulated Data Several visualizations on this site use simulated data rather than original datasets. This is done for pedagogical reasons — the goal is to demonstrate the *type* of visualization and its historical significance, not to present the data as authoritative. **Do not cite the specific numbers from these charts in academic work.** Instead, consult the original sources linked throughout the site. --- ## Technical Details ### Built With | Component | Technology | |-----------|-----------| | Site framework | [Quarto](https://quarto.org/) (R-based static site generator) | | Programming language | R (≥ 4.2) | | Core plotting | [ggplot2](https://ggplot2.tidyverse.org/) | | Data manipulation | dplyr, tidyr | | Historical data | [HistData](https://cran.r-project.org/package=HistData) (Snow, Nightingale) | | Global health data | [gapminder](https://cran.r-project.org/package=gapminder) | | Survival analysis | [survival](https://cran.r-project.org/package=survival) | | Treemaps | [treemapify](https://cran.r-project.org/package=treemapify) | | Styling | Custom CSS + Cosmo theme | ### Deployment This is a static website that can be deployed to GitHub Pages, Netlify, or any web server. See the README for instructions. --- ## Pedagogical Philosophy This site is designed around three principles: 1. **History teaches method.** By seeing *how* Nightingale, Snow, Doll, and Rosling chose to present data, students learn transferable design principles — not just R syntax. 2. **Code transparency builds trust.** Every chart has a "Show R Code" button. Students can see exactly how each visualization was built, modify parameters, and learn by doing. 3. **Discussion drives learning.** Each era ends with discussion questions designed to connect historical visualizations to modern clinical and public health practice. --- ## License & Reuse This site is intended as a **free educational resource**. You are welcome to: - Use it in your teaching (with attribution) - Modify the code for your own courses - Adapt the content for different audiences Please credit both the human director and Claude (Anthropic) if you redistribute or adapt this work. --- ## Acknowledgments - The creators of the R packages used throughout this site - The original scientists, epidemiologists, and data artists whose work is honoured here — from William Farr to the volunteers at covid19india.org - The medical students for whom this was built: may you see data not as a chore, but as a tool that saves lives --- ::: {.callout-insight} **A Final Thought:** This project is itself a data point in the story of AI and education. A human had a pedagogical vision; an AI had the capacity to research, write, and code at scale. Neither could have produced this alone. The future of teaching may look a lot like this collaboration. :::