Guest lecture for Cornell University Department of Information Science course on Online Communities (3460).

1. Online Communities in
Citizen Science
Andrea Wiggins
Postdoctoral Fellow
University of New Mexico & Cornell University
8 November, 2012

2. What is citizen science?
Members of the public engaging in real-world
scientific research
Crowdsourcing
Collaboration
Community

3. What is citizen science?
public
participation
in science
cro r
so w d - ee g
nt in
urc
ing olu itor
v n
mo
online
communities
*
infrastructure
cyber-
scientific
collaboration
= citizen science

4. What is citizen science?
intelligent
mobile sensor
net work
?
crowdsourcing science
human
computation Public Participation
in Scientific Research

5. Typ(ologi)es of citizen science
Goals and place
Participation in scientific tasks
Contribution types
Participant experiences
and more...

6. Participation in scientific tasks
PPSR$models: Contributory* Collabora1ve* CoACreated*
Define*a*ques1on/issue*
Gather*informa1on*
Develop*explana1ons*
Design*data*collec1on*methods*
Collect*samples*
Analyze*samples*
Analyze*data*
Interpret*data/conclude*
Disseminate*conclusions*
Discuss*results/inquire*further*
CAISE Report, 2009

7. Goals and the role of place
Type Primary Goals Physicality
Action &
Action ✓
Intervention
Conservation &
Conservation ✓
Stewardship
Investigation Science ✓
Virtual Science
Education &
Education ✓
Outreach
Wiggins & Crowston, 2011

8. Contribution types
Data collection
• Most common
• Observations & measurements
Data processing
• On the rise
• Entirely virtual
• Image recognition & puzzle solving
Data transcription
• On the rise
• Mostly virtual

9. Participant experience
Sharing my data/experiences
• Fits into daily life
• People like to share their passions
Working on their/our tasks
• Novel tasks
• Can reinforce hierarchy
Playing games & solving puzzles
• Fits into daily life
• Explicit symbolic rewards, entertaining

10. What does it accomplish?
engage%cri)cal%thinking%
(Trumbull%et%al%2000)%
science%learning,%bonding%
(Kountoupes%and%Oberhauser%2008)%
environmental%ac)on;%social%networks%
(Overdevest%et%al.%2004)%
social%capital%
(Ballard%2008)%
improved%policy%
(Wing%et%al.%2008)%

11. What does it accomplish?
documen(ng*range*shi0s*
(Bonter*et*al.*unpublished*data)*
iden(fying*poten(al*mismatches*
(Batalden*et*al.*2007)*
iden(fying*vulnerable*species*
(Crimmins*et*al*2008,*2009)*
health*planning*
(Leve(n*and*Van*de*Water*2008)*
an(cipa(ng*effects*on*water*sources*
(e.g.,*CoCoRaHS)*
processing
large
image
data
sets
(e.g.,
Zooniverse
projects)
applying
human
computa:on
skills
(e.g.,
Foldit)

12. Galaxy Zoo
Classifying images of galaxies
Participation involves:
Looking at pictures of galaxies online
Answering a few questions about them
Started in 2007 by a team of academic astronomers
Instant success and exciting new discoveries
Galaxy Zoo 1, Year 1: 50M classifications, 150K volunteers
Galaxy Zoo 2, Year 2: 60M classifications in 14 months
Hanny’s Voorwerp
Green Pea galaxies

13. eBird
Collecting bird abundance and distribution data
Participation involves:
Choosing observation methods
Recording bird observations (analog or digital)
Entering observations and metadata online
Launched in 2002 by Cornell Lab of Ornithology
(with National Audubon Society)
World’s largest biodiversity data set: 100M records
Currently receives about 3M observations/month
Data used in research and decision-making for land
management, policy (and recreation)

14. Crowds vs Communities
Is citizen science crowdsourcing?
When is it crowdsourcing, and when is it not?
What separates a crowd from a community?
Crowdsourcing versus communitysourcing?

15. Motivations
Galaxy Zoo
Motivations: similar to other participant surveys
Forums: evidence of shared interests & practices
Alice
Reader to Leader...
...to Scientist!
http://blog.galaxyzoo.org/2009/07/01/shes-an-astronomer-alice-sheppard/

16. More than just motivation
Motivations
Intrinsic (altruism)
Extrinsic (money)
Dynamic
Personal Values (domain, science)
Individual Goals (contributing)
http://www.flickr.com/photos/verbeeldingskr8/4875710270/

17. Implications for Design
Who will participate?
Why will they
participate?
How will they be
rewarded?
How can experiences be
expanded?
http://www.flickr.com/photos/andymangold/4335799638/

18. Which Came First?
Science-first project design
Tech focuses on data entry
Experiences are usually
simplified science
Citizen-first project design
Tech focuses on ease of use
Experience adapts existing leisure practices
Self-rewarded & socially rewarded
http://www.flickr.com/photos/hammer51012/495218105/

19. ICTs for Citizen Science
Web-based data entry & social tools
“Vanilla” website
CMS
Custom platform
Mobile
Games
CitizenSort image courtesy
of Eric Graham

20. Images courtesy of Nathan Prestopnik and the
CitizenSort team at Syracuse University
US NSF Grant # 09-68470

21. Online Communities
We don’t know much!
Primary social & communication tool in virtual (place-
independent) projects
But what about...
Place-dependent projects
Pre-existing communities
Scale of participation
Cohesive systems vs system assemblages

22. What makes it a community?
How did you judge whether a citizen science
project you reviewed has an online
community or not?
Blogs + forums + social media
Leaderboards, visibility of others’ data, “shared
checklists”
Were there signs of offline community?
What are the implications of that?

23. Communities in Citizen Science
Primary recruitment method (in place-based)
Not feasible for entirely virtual projects
Important for retention
Come for the coffee, stay for the conversation
Main community engagement strategies
Traditional: tapping into existing communities
Virtual: creating a new community

24. Unrealized potential value
Retention tool
Recruitment tool
Capture serendipity
Promote inquiry
Gather evaluation data
More...

25. Challenges
Strategic implementation required with
existing communities
$$$
Active management
Technical resources
Zooniverse research underway to learn more
Yay, Sloan Foundation!

26. Thanks!
andrea.wiggins@cornell.edu
@AndreaWiggins
dataone.org
citizenscience.org
andreawiggins.com

27. 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. Conserva4on
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.
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