Summary
Exploring how community‑driven data collection can enhance water quality monitoring and inform decision‑making by identifying the “sweet spot” between Citizen Science (CS) data and authoritative sampling.
The Challenge
Citizen Science generates a wide range of data, but the variability of methods, metrics and quality makes it difficult to integrate with authoritative sampling. This challenge focuses on identifying and standardising the key elements required to align Citizen Science data with authoritative datasets, including:
- Minimum data coverage and quality that is useful
- Augmentation with other data sources (additional layers)
- Collation of data from mutliple sources with contextual information
- Automated data retrieval
- Integrating existing methods and applications
- Ensuring quality and confidence through standardisation
Risks identified
- Reduced control over data quality
- Reduced feedback to citizens and data collectors
- Less opportunity to direct sampling regime
Call to Action
Members are encouraged to:
- Submit ideas on how to define and standardise the “sweet spot” between CS and authoritative sampling
- Share examples of useful metrics, methods, or data‑quality approaches
- Endorse promising ideas contributed by others
- Comment with practical insights on risks, automation, augmentation layers, or contextual data needs
- Form a project team to co‑develop shared standards and cross‑catchment methods