Citizen Science Phenotypes
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Presentation for iDigBio workshop on Public Participation in Digitization.
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Citizen Science Phenotypes
- 1. Citizen Science Phenotypes Typologies & Implications of Project Design Andrea Wiggins Postdoctoral Fellow DataONE & Cornell Lab of Ornithology 28 September, 2012 iDigBio Workshop on Public Participation in Digitization US NSF Grant #OCI-0830944
- 2. What is citizen science? Members of the public engaging in real-world scientific research • Crowdsourcing • Collaboration • Community 2
- 3. By any other name... 3
- 4. What’s in a name? Label Research Domain Key Features Civic science Science communication Public participation in decisions about science People’s science Political science Social movements for people-centered science Citizen science Ecology Public participation in scientific research Volunteer/community- Natural resource Long-term monitoring and intervention based monitoring management Participatory action Behavioral science Researcher & community participation & action research Action science Behavioral science Participatory, emphasizes tacit theories-in-use Community science Psychology Participatory community-centered social science Living Labs Management Public-private partnership for innovation 2
- 5. A few typologies Consultative, functional & collaborative • Lawrence, 2006 Contributory, collaborative, & co-created • CAISE report, 2009 Action, conservation, investigation, virtual, & education • Wiggins & Crowston, 2011 Typologies based on goals & tasks • Wiggins & Crowston, 2012 4
- 6. Participation in scientific tasks 6
- 7. Types of participation tasks Data collection • Most common • Observations & measurements Data processing • On the rise • Entirely virtual • Image recognition & puzzle solving Data transcription • On the rise • Mostly virtual 6
- 8. Framing participation tasks Sharing my data/experiences • Fits into daily life • People like to share their passions Working on their/our tasks • New, often unfamiliar tasks • Can reinforce us/them divisions Playing games & solving puzzles • Fits into daily life • Explicit symbolic rewards, entertaining 6
- 10. (Relative) pros & cons Contributory Collaborative Co-Created Scalability High Varies Low Technology High Varies Low dependency Volunteer Low Varies High management Task complexity Low Varies High Data quality Varies Varies Varies Sustainability Varies Varies Varies 9
- 11. Implications for design 10
- 12. Implications for design Honestly evaluate project resources & goals, work backwards 11
- 13. Implications for design Honestly evaluate project resources & goals, work backwards Recognize tradeoffs and make choices accordingly 12
- 14. Implications for design Honestly evaluate project resources & goals, work backwards Recognize tradeoffs and make choices accordingly Design to address resource constraints 13
- 15. Implications for design Honestly evaluate project resources & goals, work backwards Recognize tradeoffs and make choices accordingly Design to address resource constraints There’s more than one right answer 14
- 16. Thanks! andrea.wiggins@cornell.edu @AndreaWiggins dataone.org citizenscience.org andreawiggins.com 15
- 17. Typologies • Lawrence, A. (2006). “No Personal Motive?” Volunteers, Biodiversity, and the False Dichotomies of Participation. Ethics, Place & Environment, 9(3), 279-298. • Bonney, R., Ballard, H., Jordan, R., McCallie, E., Phillips, T., Shirk, J., et al. (2009). Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report (Tech. Rep.). • Danielsen, F., Burgess, N., Balmford, A., Donald, P., Funder, M., Jones, J., et al. (2009). Local participation in natural resource monitoring: a characterization of approaches. Conservation Biology, 23(1), 31–42. • Cooper, C. B., Dickinson, J., Phillips, T., & Bonney, R. (2007). Citizen Science as a Tool for Conservation in Residential Ecosystems. Ecology and Society, 12(2). • Wilderman, C. C. (2007). Models of community science: design lessons from the field. Proceedings of Citizen Science Toolkit Conference. • Wiggins, A. & Crowston, K. (2011). From Conservation to Crowdsourcing: A Typology of Citizen Science. Proceedings of the 44th Annual Hawaii International Conference on System Sciences. • Wiggins, A. & Crowston, K. (2012). Goals and Tasks: Two Typologies of Citizen Science Projects. Proceedings of the 45th Annual Hawaii International Conference on Systems Sciences. 16
Hinweis der Redaktion
- Thanks for having me! I ’ m currently a postdoc with D1 at UNM and CLO at Cornell, and my work focuses on data management and technologies for citizen science. I ’ m kicking off the discussion of citizen science engagement by talking about the many flavors of citizen science.
- So just what is citizen science? It ’ s a way of doing research by engaging members of the public in at least some of the scientific work. It ’ s an interesting blend of crowdsourcing, scientific collaboration, and communities of practice.
- Citizen science isn ’ t new. The current form dates back at least 100 years to the Audubon Christmas Bird Count, which started in 1901. However, I ’ ve been informed that this type of public participation in science goes back to the classical Greeks. The modern version, however, has changed quite a bit from its predecessors, and has also undergone a number of identity changes over time. To some degree, the variety of names that are assigned to citizen science have more to do with the diversity of the people involved than anything else. As you can see from some of the titles that it has been given over the years, a lot of the current practices are rooted in observational ecological research.
- Many labels for PPSR have emerged over time, often in different fields that do not communicate with one another. There are also a variety of related research practices with similarities to citizen science. So what are we really talking about here?
- Lawrence - Power, knowledge, & participation from literature in STS, looking at roles CAISE - participation tasks from case studies in ISE Wiggins - Explicit goals based on landscape sample, follow-up survey analyzed on participation tasks and protocols But let ’ s go a little deeper into three lenses on participation for a little more clarification.
- This is one of the most commonly used typologies of citizen science, based on several prior similar models. It ’ s from the 2009 report for CAISE. Classifies projects according to who does which scientific tasks in the project. Most apparent point of differentiation between many projects, and easy to assess. This is really one of the more useful ways to divide citizen science projects up into categories.
- Another way to think about these tasks - and this also isn ’ t from any particular typology - is whether volunteers are Sharing, Working, or Playing when they participate. This view also focuses on the tasks, but instead looks at them from the perspective of participant experience and how well participation fits into what people are already familiar and engaged with.
- Another way to think about these tasks - and this also isn ’ t from any particular typology - is whether volunteers are Sharing, Working, or Playing when they participate. This view also focuses on the tasks, but instead looks at them from the perspective of participant experience and how well participation fits into what people are already familiar and engaged with.
- But when we think about engaging people in citizen science, especially from a project design standpoint, there are a number of other important factors that we can ’ t ignore, and they all vary based on the project goals and tasks. There are certainly additional relevant points of comparison, but these are the ones I hear brought up over and over.
- So taking that easy-to-use typology from the CAISE report, let ’ s look at the relative pros and cons for each of those models of participation based on implications for those critical factors. Contributory: most scalable but needs IT & numbers to succeed; low complexity tasks reduces training, improves data quality; greatest potential spatiotemporal spread Co-created: least scalable but also least IT-dependent; higher complexity increases training needs; most localized, needs most organizer time as ratio to participants Collaborative: freedom to negotiate more tradeoffs; more unknowns For all projects, data quality and sustainability vary across the board. Data quality varies because it ’ s a function of the intersection of all of the design factors, while sustainability varies based primarily on project resources.
- So what I want you to take away from this talk are four simple points. They may seem obvious because they are essentially common-sense, but they are important to deliberately consider when designing or even just comparing citizen science projects. [READ OFF]
- And here are the references for some of the typologies, for anyone who is interested in looking them up...