EcoGardenHealth

EcoGardenHealth is a specialized web application I developed for my Master's dissertation in partnership with Swansea University's Biosciences Department. This project demonstrates my ability to collaborate across disciplines and create technical solutions for scientific research workflows.

About the Project

Research Challenge: The Biosciences Department needed a streamlined digital platform to collect and analyze soil testing data from citizen science participants. Their existing manual processes created barriers to participation and made data analysis inefficient for researchers.

Solution Approach: I designed and built a full-stack web application that automates data collection, provides interactive data visualization, and enables researchers to efficiently analyze geographic patterns in soil health data. The platform bridges the gap between citizen participants and scientific research requirements.

Key Features:

• Geographic Data Visualization: Interactive maps using MapBox for spatial analysis of soil testing results
• Data Collection Interface: User-friendly forms for citizen scientists to submit soil testing data
• Research Analytics: Pandas-powered data processing and visualization tools for researchers
• Responsive Design: Bootstrap-based interface optimized for field use on mobile devices
• Database Architecture: PostgreSQL database designed for complex geographic and scientific data relationships

Cross-Disciplinary Collaboration: This project required extensive stakeholder management, working closely with biosciences faculty to understand research requirements while translating scientific needs into technical specifications. The final solution balanced usability for citizen participants with analytical depth for researchers.

Academic Impact: The platform successfully streamlined the data collection process and provided researchers with tools for geographic analysis of soil health patterns. While the live site currently runs without database connectivity due to hosting costs, the project demonstrates full-stack development capabilities and scientific application design.

Technologies Used

• Django - Python web framework for robust backend development and data management
• PostgreSQL - Relational database optimized for complex geographic and scientific data
• Bootstrap - Responsive CSS framework for mobile-friendly field research interface
• Docker - Containerization for consistent development and deployment environments
• MapBox - Interactive mapping and geographic data visualization platform
• Pandas - Python data analysis library for scientific data processing and analytics