Role: Researcher, Coder, Designer
Tools: R (data cleaning + analysis), p5.js (visualization), HTML/CSS/JS
Audience: General public, local community, environmental data stakeholders

This interactive data visualization explores how rainfall impacts microbial contamination in the Charles and Mystic Rivers. Using public water quality data from 2018 to 2022, I focused on Enterococcus bacteria—an indicator of fecal contamination—and cross-referenced it with daily rainfall levels recorded at Logan Airport.

I performed data cleaning, filtering, and statistical analysis using R, confirming a moderate, statistically significant correlation between rainfall and bacterial concentration. The findings suggest that even moderate rain events can elevate contamination levels, likely due to urban runoff and combined sewer overflows.

To visualize these relationships, I designed and coded a radial plot in p5.js, combining time, contamination intensity, and rainfall into a cyclical, seasonally mapped form. The interactive version was embedded into a collaborative sustainability site, created as part of Northeastern’s Expressive Visualization course.

The visualization supports environmental storytelling through:

• Clear encoding of three variables: time, contamination level, and rainfall

• Expressive form reflecting seasonal cycles

• Interactive controls (in the web version) to filter data by year or station

• A narrative designed to prompt awareness around water safety, climate resilience, and public health

Seasonal Patterns of Microbial Contamination
This radial plot maps Enterococcus bacteria levels across the year, with each dot representing a sampling date. Red intensity reflects bacterial concentration, and dot size corresponds to rainfall. Warmer months show denser contamination events, revealing seasonal and weather-driven patterns in river health.

Tools Used

• p5.js (visualization and interaction)

• R (data processing and correlation analysis)

• HTML/CSS/JavaScript (integration into website)