Olympic Inequalities

Project created in the context of EPFL COM-480 Data visualisation course in 2026.

Have a look at our website.

Motivation

The Olympic Games are often seen as a symbol of fairness: athletes from all around the world competing on equal ground. But are the Olympics really as equal as they appear?

Our project explores how sociocultural, economic, and geopolitical contexts have shaped Olympic participation and success over time. Through a series of interactive visualizations, we investigate how wealth, population, gender representation, politics, and historical events influence the Games.

By combining storytelling with interactive data visualizations, our website reveals the inequalities hidden behind medal counts and athelete participation.

We explore the following themes:

• Gender Representation
  The evolution of men's and women’s participation across Olympic history.

• Medal Distribution
  How medals are distributed across continents, countries, sports, and disciplines.

• Athlete Body Types
  Exploring physical characteristics associated with different sports and disciplines.

• Geopolitical Contexts
  Wars, boycotts, and political tensions that shaped participation in the Games.

• Economic Fairness
  Comparing medal counts while accounting for GDP and population differences.

Target Audience

This website is accessible for everybody interested in how inequalities are reflected through the Olympics.
Try out our visualisations and have fun on the website !

Screen cast

Have a look at ou screencast to have an idea of what you can expect from our website.

Dataset

We combined many datasets from Kaggle:

• athlete_events.csv
• noc_regions.csv
• gdp_per_capita.csv
• pop_count.csv
• conflicts.csv

We first merged them into a single olympic.csv file. We then created individual extracted datasets per visualisation topic (see website/data folder) to make our website run smoother.

Project Structure

├── data/                 # Datasets and data processing files
├── milestones/           # Milestone submissions
└── website/              # Website source files
    ├── data/             # Processed data files
    ├── img/              # Images and icons
    ├── js/               # JavaScript files for the interactive visualisations
    └── models/           # 3D athlete models

Running the Project Locally

To clone the repository:

git clone https://github.com/com-480-data-visualization/DataRizz.git

To run the website locally:

cd DataRizz/website
python -m http.server 8080

Authors

Student's name	SCIPER
France Lu	345769
Laura Taghizad	346469
Hana Salvetova	339644

Milestones

• Milestone 1 report.
• Milestone 2 report.
• Final process book.