Earlier this year, my first journal publication as faculty at UMD, “Surveying the citizen science landscape”, reported on results of a survey of citizen science projects that I conducted as a PhD student.
The most important take-away is that citizen science is incredibly diverse. Just like in the early days of studying open source software, research and media often call attention to a few outliers that don’t really represent the full richness of the broader community of practice.
In addition to a few such large-scale projects, our survey results primarily describe small-to-medium sized citizen science projects, mostly in North America, and largely focused on collecting ecological data. There are a few common strategies, characteristics, and feature sets that describe most of these projects for any given variable of interest, such as funding sources, data quality strategies, and the kinds of task-oriented and social activities available to volunteers.
But these variables were all uniquely combined for each project, as the design of the entire enterprise has to work within the constraints imposed by resources, scientific standards, and project goals. There was no obvious cookie-cutter pattern of “right answers” to address common questions in project design. Like any other research, doing science with the involvement of volunteers requires designing within specific limitations in order to achieve specific outcomes, and the constraints each project faces are unique.
There’s no magic formula to identify which combination of characteristics will create the right conditions for a particular project, of course. However, by describing the range of project characteristics and strategies for key operational considerations, we hope to help practitioners make important decisions about citizen science project design by showing the range of practices currently in use.