Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Free as in Puppies: Compensating for ICT Constraints in Citizen Science
1. Free As In Puppies:
Compensating for ICT
Constraints in Citizen Science
Andrea Wiggins
University of New Mexico & Cornell University
andrea.wiggins@cornell.edu @AndreaWiggins
4. Related Work
✦ Participant-focused
✦ Individual learning Trumbull et al., 2000
(many more in Informal Science Education)
✦ Motivation Nov et al., 2011; Rotman et al., 2012;
Raddick et al., 2009
5. Related Work
✦ Project-focused
✦ Typologies Cooper et al., 2007; Bonney et al., 2009;
Wiggins & Crowston, 2010
✦ Data quality Sheppard & Terveen, 2011; Wiggins et
al., 2011; Wiggins et al., 2012
6. Assumptions
More
people
Cool Miracle More Better
$$$ new occurs data science
ICT
Better
data
7. Reality
✦ There is no money
✦ Free ICT are “free as in puppies”
✦ ICT is just one part of a complex
sociotechnical system
8. Research Question
✦ RQ: How do citizen science project
organizers address key issues related
to participation & data quality when
resource constraints limit ICT options?
9. Research Question
✦ RQ: How do citizen science project
organizers address key issues related
to participation & data quality when
resource constraints limit ICT options?
✦ Answer: Creatively!
✦ Improving participation processes
✦ Expanding participation options
✦ Investing money & time strategically
10. Research Design
✦ Comparative case study
✦ Theoretical sampling
✦ Project-level focus
12. Case Selection
✦ Same core tasks
✦ Go outside, look at stuff, submit
data
✦ Similar purpose
✦ Conservation, education, research
✦ Contrasting resources
✦ eBird: 4.5 FTE, ~$300K/yr
✦ GSP & MW: 0.5/1.5 FTE, ~$15K/yr
13.
14.
15.
16. Recruitment
✦ #1 strategy: direct in-person contact
✦ ICT solution
✦ Effortless social recommendation
via existing community practices:
“This report was generated
automatically by eBird v3”
✦ Alternate solution
✦ Data collected on paper
✦ Saturation marketing
17. Retention
✦ ICT solution
✦ Mind-blowing data visualizations
21. Data Quality
✦ ICT solution
✦ Algorithmically flag outliers for
review by small army of experts
✦ Alternate solutions
✦ Hone protocols
✦ Invest in good data
entry forms
✦ Use complementary
data sources
22. Implications for Practice
✦ Good ICT is awesome - when you can
afford it
✦ When you can’t...
✦ Combine available ICT with other
(human, organizational) resources
✦ Unique resources often
taken for granted
✦ Beware of free puppies
23. Implications for Policy
✦ Citizen science is growing up
✦ Valid to fund on scientific merit
✦ Need better means of evaluating
scientific merit of citizen science
✦ Consider ROI of research
✦ 1 week on oceanographic research
vessel for a handful of researchers
✦ 1 year of eBird & 60M global data
points used by 120K people/day
24. Implications for CSCW
✦ When ICT options are limited, look for
complementary resources &
compensatory strategies
✦ Opportunity for cross-context
comparisons
✦ Online communities
✦ Distributed scientific work
✦ Peer production
25. Questions?
✦ Research made
possible by...
✦ U.S. NSF
✦ eBird
VOSS-0943049,
✦ The Great Sunf SOCS-0968470, &
OCI-0830944
✦ Awesome CSCW
✦ reviewers
✦ Mydissertation
committee