Swimming Through Data

Abstract

Tracking aquatic animal movements, such as those of the Atlantic sturgeon (Acipenser oxyrinchus), presents significant challenges due to sparse data from acoustic sensors and a lack of accessible visualization methods. This project addresses these issues by developing “Swimming Through Data”, an open-source, interactive tool for visualizing geo-spatial tracking data. The primary aim was to create a system that generates clear, accurate heatmaps for both popular science audiences and scientific researchers, without misrepresenting the underlying data. Key objectives included refining raw sensor data, building a durable and extensible software architecture, enabling pedagogical data representation, and ensuring the tool’s public availability and reusability.

The methodology involved developing a backend architecture with a RESTful API and a data management pipeline for processing sensor data. The frontend was built using React, with Leaflet and Leaflet.heat for interactive map displays. A usercentered design process, incorporating the Triple Diamond approach and MoSCoW analysis, guided development. The tool’s effectiveness and usability were evaluated through qualitative user tests and heuristic evaluations, focusing on learnability, efficiency, memorability, error handling, and user satisfaction.

The project successfully produced a functional tool capable of data uploading, processing, and interactive heatmap visualization. User testing revealed high overall satisfaction and good learnability, alongside feedback for UI enhancements. The visualization approach was found to be clear and effective in representing sparse data.