Rivulet: Python Notebook Tools for Educational Data Retrieval
The Rivulet project provides teachers, curriculum designers, and educational researchers with Python notebooks and CODAP plugins that streamline querying and fetching environmental datasets from public API endpoints. These notebooks act as automated wrangling pipelines, translating complex database APIs into clean, structured data that highlight “signature” scientific patterns.
Intended Audience & Use Case: Designed for science educators and curriculum developers. It simplifies the data acquisition process, allowing designers to easily extract environmental time-series datasets (including local air, oceanographic, water quality, and other data) to build custom, region-specific investigations without writing code from scratch or drowning in sparse or ambiguously useful data.
Available Jupyter Notebook Resources
- EPA AQS Air Quality Notebook: Fetches local criteria pollutants and AQI data.
- NOAA CoastWatch Ocean Explorer Notebook: Pulls ocean temperature and sea level telemetry.
- USGS/EPA WQX Water Quality Notebook: Extracts water chemistry and biological markers.
- NASA POWER Surface Albedo Notebook: Extracts surface albedo levels anywhere globally for the last 25 years.
Next Generation Tools in CODAP
- Rivulet Next CODAP Plugins: Experimental browser-based data exploration tools that load data directly into CODAP without requiring Jupyter runtimes.
Associated Publications The motivation and approach to developing Rivulet tools is described in: Wilkerson, M. H., Eloy, A., & Fitzmaurice, H. L. (2026). Rivulet: A framework and tools for fetching custom, pedagogically generative scientific datasets. Proceedings of the 20th International Conference of the Learning Sciences (ICLS ’26).