**This blog entry orginally appeared on the website oceanspaces.org.**/p>
There are all sorts of citizen science programs, from a small group of intense volunteers in one small community to thousands of people snapping pictures of wildlife all over the world. Since it’s difficult for one term, citizen science, to cover the spectrum of program types, it is helpful to categorize the types of citizen science programs into smaller subsets that are each easier to characterize. Several scientists have attempted at establishing a classification scheme, and each focuses on different aspects of variation. Each is also a celebration of diversity through recognizing multiple valid ways of engaging the public in science. However, it’s important to note that each typology also says as much about the people that created them as about the programs they describe: they fit a research goal and set of personal interests. Photo: We classify pretty much everything in the natural world, it’s human nature.
The most well-known of these typologies emerges from a Center for the Advancement of Informal Science Education working group. Bonney et al’s (2009) report breaks citizen science into 3 categories based on how many stages of the scientific process are participatory:
– contributory: Citizens participate largely in data and sample collection but leave project design and data analysis to the professional scientists. This is the most common form.
– collaborative: Citizens have input in method development and help analyze and distribute results. This often emerges from volunteers in collaborative projects who want to be more involved.
– co-created: Scientists and citizens have equal contributions to the project, negotiating each step of the scientific process from the first idea for the project through deciding what comes next.
Bonney’s typology based on what stage of the research process includes collaboration.
Shirk et al (2012) expand on this typology by adding 2 more categories that describe even more agency in community participants:
– contractual: Community members identify a research need and hire a scientist to investigate it
– collegial: Entirely community – led science with no professional scientists on hand
These categories become particularly useful when designing a program around how intensely community members want to participate. Each community member will have different expectations and capabilities, time limitations, and interests, so tailoring the program to the types of involvement desired is important for participant retention. Keeping a program running requires hitting the fine balance of not overwhelming volunteers with responsibility but giving them enough agency to demonstrate and grow their expertise.
Through a more empirical of 80 program traits, Wiggins and Crowston described 5 types of citizen science based largely on their program goals:
– Action: Initiated by concerned community members, science in support of civic agendas. These projects most often have participatory action research methodology and only sometimes employ professional scientist advisors.
– Conservation: Strongly rooted in place, projects engage citizens in data collection as a means of education and to create a stewardship ethic. These projects often have a large network of collaborators, including scientific institutions and state and federal agencies.
– Investigation: Focuses on data collection from the physical environment, often with education as an explicit goal. Projects have a wide range of scales, but can reach international in scope with thousands of volunteers.
– Virtual: With no physical element, participants often focus on data analysis. Websites offer means of sorting, classifying, and interpreting data for crowd-sourced effort on a large scientific question.
– Education: Structured around educational goals like school curriculum or museum plans. Data collection or interpretation is, to a certain degree, an added bonus or motivation for the program but not a priority.
The authors of this typology stress that different governance and infrastructure are needed for each type of program. For example, virtual and investigation often require large investments in cyberinfrastructure for data management and analysis, while conservation and action programs might invest those resources in outreach and media support. Stressing program goals also provides a constant reminder of the motivation of program leaders and volunteers moving forward, as well as a conversation starter for other groups wanting to collaborate. like Ocean Science Trust as we reach out to groups active in the Central Coast.
Specifically for monitoring data, which applies to the California Citizen Science Initiative as well as a majority of citizen science data in existence, Danielsen et al (2009) have a pretty helpful classification that describes who is responsible for what activities (and the titles are self-explanatory):
– externally driven, professionally executed monitoring
– externally driven monitoring with local data collectors
– collaborative monitoring with external data interpretation
– collaborative monitoring with local data interpretation
– autonomous local monitoring
These categories are meant to describe involvement of participants in the program, but they also have implications for data credibility. Any collaboration (as opposed to autonomous local monitoring or professional monitoring) lends credibility to the data, as it is viewed by the public and managers as vetted and approved by local stakeholders and professional experts.
These are not the only typologies out there, but they give an idea of how one can group projects While it is human nature to sort and categorize, these typologies are sometimes viewed as an academic exercise. Importantly, though the utility of a typology also lies in practical aid for program design. They also provide a language to describe the diversity within citizen science, providing a reminder that the needs and considerations of each program are different. Stay tuned as we document this diversity operating within one region, Central Coast of California.