Analysing the value of environmental citizen-generated data: Complementarity and cost per observation

Area of Science:

• Environmental Science
• Data Science
• Community Engagement

Background:

• Citizen Science (CS) initiatives are increasingly used for environmental data generation, raising expectations for applications in design, analysis, management, and research.
• While CS projects often yield societal benefits like improved natural resource governance, concerns persist regarding data quality and cost-effectiveness.
• The Ground Truth 2.0 project provided a platform to evaluate the actual value and cost of citizen-generated environmental data.

Purpose of the Study:

• To develop and apply a methodology for assessing the value of citizen-generated data.
• To analyze the cost-effectiveness of Citizen Science data generation, considering complementarity with existing data and temporal cost evolution.
• To examine the impact of co-design and tool development on the overall cost of Citizen Science initiatives.

Main Methods:

• A novel methodology was proposed to quantify the value of citizen observations based on their complementarity to existing environmental data and their cost over time.
• The methodology was applied to case studies established through a co-design approach.
• Data collection costs, including those for co-design events and tool development, were analyzed in relation to observation campaign costs.

Main Results:

• The study found that the cost of obtaining Citizen Science data is often higher than commonly perceived in literature.
• Significant costs are associated with co-design processes for community building and the functional/technical design of data collection tools, outweighing rollout expenses.
• An increase in preparatory events did not consistently lead to an immediate rise in collected observations across the studied cases.

Conclusions:

• Citizen Science data holds significant value, particularly in regions lacking in-situ environmental monitoring infrastructure.
• The perceived cost-effectiveness of Citizen Science is moderated by substantial upfront investments in community engagement and tool development.
• Future initiatives should carefully consider these co-design and development costs when planning for environmental data generation.