📊 GovHack '24: Socioeconomic Insights Dashboard

A production-ready data storytelling platform visualising the factors influencing youth education, employment, and mental health choices in Australia.

Features • Quick Start • Tech Stack • Architecture

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📖 About The Project

This project transforms open government data (ABS, AIHW) into an immersive, interactive experience. It moves beyond static spreadsheets to provide a living dashboard where policymakers and the public can explore the correlations between income, education, crime, and mental health.

🎯 Key Features

• ✨ Modern Bento Grid Interface: A responsive, high-density layout inspired by modern design trends.
• 🌙 Dark Mode: Fully supported dark/light themes with accessible high-contrast modes.
• 📊 Interactive Storytelling:
  • Consolidated Home View: See the big picture with cross-correlated charts.
  • Deep Dives: Dedicated tabs for Income, Education, Crime, and Mental Health.
  • Zoom & Pan: Powered by Plotly.js for detailed data exploration.
• 🗺️ Geospatial & Demographics: Interactive visualisations of data distribution across Australian states.
• 📑 Resource Centre:
  • Smart Print: Generate clean, full-page PDF reports of the dashboard.
  • Downloads: Access original research papers (PDF) and high-res charts (PNG).
• 🏗️ Robust Data Pipeline: Automated ETL process converting raw CSVs to optimised Parquet files.

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⚡ Quick Start

Get the dashboard running in minutes.

🐳 Option 1: Docker (Recommended)

The easiest way to run the full stack (App + Data Processing).

# 1. Clone the repository
git clone https://github.com/lagnadlinus/open_gov_data_visualisation.git
cd open_gov_data_visualisation

# 2. Build and Run
docker-compose up --build

Access: Open your browser to http://localhost:8000

🐍 Option 2: Local Python

For developers wanting to modify the code.

1. Install Dependencies:

   pip install .

2. Run ETL (Data Processing):

   # Transforms raw CSV data into optimised Parquet files
   python -m etl.loaddata

3. Run Server:

   export DEBUG=True
   export SECRET_KEY=dev_secret_key
   python career_visualizer/manage.py runserver

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🛠️ Tech Stack

Built with a focus on performance, scalability, and maintainability.

Layer	Technology	Description
Backend		Robust web framework serving JSON APIs and HTML.
Frontend		Semantic HTML + Vanilla JS for lightweight interactivity.
Viz		High-performance interactive charting library.
Data		ETL processing and optimised columnar storage.
Ops		Containerised deployment environment.

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🏗 Architecture

graph LR
    A["Raw Data (CSV)"] -->|ETL Script| B("Processed Parquet")
    B -->|Pandas| C[Django Views]
    C -->|JSON API| D["Frontend (Plotly.js)"]
    
    subgraph Data Layer
    A
    B
    end
    
    subgraph Application
    C
    D
    end

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🔒 Security

We take data security seriously.

• Secrets Management: No hardcoded secrets; environment variables used for configuration.
• Data Hygiene: automated cleanup of raw sensitive files.
• See SECURITY.md for our full policy.

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Made with ❤️ for GovHack '24