Environmental Monitoring Data Collection
6 weeks · 0 milestones
Collect real environmental monitoring data from a specific named location using a documented methodology: air quality (PM2.5, NO₂, CO₂), water quality (pH, dissolved oxygen, turbidity, conductivity), biodiversity count, temperature, or equivalent environmental parameter. Document location coordinates, measurement dates and times, equipment or method used, and any data quality flags. For students without field access or equipment, monitoring data from named open government or citizen science networks is accepted: NOAA monitoring stations, EPA Air Quality System (free), OpenAQ (free), iNaturalist (for biodiversity), or Copernicus atmospheric data — but the provenance (station name, coordinates, data version) must be fully documented. The proof is a real documented dataset with full provenance — not a description of what you would measure, but actual data from an actual named location. Reviewed by an environmental scientist who examines the methodology for sampling bias and asks how the monitoring protocol would need to change to answer a specific environmental question.
Milestone map
Milestone map
3 milestones
Design a rigorous environmental monitoring protocol for a specific variable (air quality, water quality, biodiversity, climate, or soil chemistry). Define: the variable, spatial and temporal sampling design, measurement method, detection limits and uncertainty, and data management plan. Collect data either through original field measurements or — equally valid — by accessing and downloading an appropriate publicly available dataset using the protocol's spatial and temporal criteria. Using public data sources is explicitly encouraged and equivalent in rigor to original collection when properly documented.
Proof required
Submit: (a) your monitoring protocol document (minimum 800 words) covering all five elements: variable, sampling design, measurement method, detection limits/uncertainty, and data management plan, (b) the collected dataset with clear labelling of source, spatial coverage, temporal coverage, measurement method, and any quality control applied — if using public data, include the download URL and the specific query or filter used, and (c) a data quality assessment confirming the dataset meets the protocol's criteria (completeness, accuracy, consistency). Free public sources: NOAA CDO, EPA AQS, OpenAQ, NASA Earthdata.
What gets checked
- Protocol is specific and reproducible — another scientist reading it should be able to replicate your data collection exactly
- Dataset is clearly attributed — source, download date, and any subset/filter criteria are documented
- Data quality assessment addresses completeness, accuracy, and consistency — not just 'data looks good'