The engagement of volunteer scientists in understandingenvironmentalhealth and using data at local, state, and regional levels has numerous benefits. These programs benefit from systems of technical support within the scientific process of monitoring, including study design, standard operating procedures development, methodology training, quality assurance, and data storage. A key step within this process is facilitated data interpretation.
Not only do volunteers add spatial and temporal variation to data collection efforts, but they also become local experts of their sites and can provide valuable insights about their data. Many datacollectorsvisit sites routinely and can track changes that data alone might not reveal, including land use changes andenvironmentalappearance. When volunteers participate in facilitated investigations of their own data, they identify stories hidden behind the trends and develop the confidence to share thesedatanarratives with diverse stakeholders. This increases the volunteer buy-into the program, but also ownership over their data and impact they can have on local waterways.
This session aims to provide a collaborative space to share about different approaches to data interpretation in volunteer and community-based monitoring programs.Participants will explorebest practices when engaging communities with data, methods for establishing technical background, effective and efficient data visualization strategies, challenges, and success stories.
Presenters
Stephanie Letourneau, Alliance for Aquatic Resource Monitoring at Dickinson College
Phoebe Galione, Alliance for Aquatic Resource Monitoring at Dickinson College