- Biocollections contain critical data on biodiversity but 3-5 billion specimens remain undigitized. - Crowdsourcing and citizen science can help digitize these collections to document changes in biodiversity over time. However, building good crowdsourcing applications requires infrastructure, metadata standards, articulation work, and efforts to foster collaboration among volunteers. - Past examples show that crowdsourcing can produce peer-reviewed research publications and new scientific discoveries when best practices are followed. With proper support, crowdsourcing has the potential to generate large volumes of reusable, semantically enriched data.

1. Or, Why Crowdsourcing and Citizen Science Will
NOT Create Nightmare Zombies That Will Destroy
Us All
Andrea Thomer, University of Illinois at Urbana-Champaign
Robert Guralnick, University of Colorado, Boulder

2.
- Biocollections contain critical data for documenting
biodiversity, reconstructing how it has changed over time,
and investigating the causes of changes.
- 3-5 billion undigitized specimens , at least.
IN A WORLD... dominated by anthropogenic
change....

3.
the robots are sad about this too...

4. “Many Americans cannot provide
correct answers about basic factual
knowledge of science or the scientific
inquiry process.”
2010 National Science Foundation (NSF)
Science and Engineering Indicators
Report

5. - Provides us with the workforce we need
- Gives back to the community
- Could be highly scalable
- With a "centralized" web interface, it's easy to
imagine all benefiting

6. - Crowdsourcing & citizen science =/= apocalypse
- Galaxy Zoo Green Peas: Discovery of a Class of Compact Extremely
Star-Forming Galaxies
- eBird results in 75 peer reviewed pubs a year (Kelling, 2011)

7. - We've relied on volunteers and amateurs for centuries
- Amateurs have time, passion and a different perspective;
this leads to discovery.
Annie Alexander didn't just fund the MVZ, but helped
collect specimens for it as well
"gentleman scholar" = not actually employed as a
scientist

8. - Data quality concerns, e.g. esoteric species
names.
- What are the real costs/benefits of this
approach vs. others?
- Need data about incentives
- How to foster community and collaboration?

9. - We can track
volunteers’ expertise
levels
- There are already
success stories in dorkier
fields
- Research in related
domains shows how
communication creates
better data, knowledge

10. Percent correct answer on “clicker”
question when initially asked (Q1),
% correct after class dicussion (Q1ad),
and % correct on related but different
question (Q2)

11. - More engaged
community by
enabling interaction
- Positive feedback
loops
- Better data for us!

12. Crowdsourcing forces articulation work:
“ ‘Articulation work’ names the continuous
efforts required in order to bring together
discontinuous elements -- of organizations, of
professional practices, of technologies -- into
working configurations”
Suchman, 1995

13. Articulation activities required by crowdsourcing:
-The development of stable cyberinfastructure
-The development, maintenance, and deployment of
good metadata standards
-Clear explanation of best practices in using those
metadata standards

14. Often in digitization projects we forget about the
human cost - the humans involved in the workflow
(Mak, 2011)

15. We've been relying on
volunteers for centuries.

16. Working with volunteers
online: it's a new medium,
not a new method

17. Collaborative work leads to
better data.

18. We need to build
applications that foster
collaboration.

19. Building good
crowdsourcing applications
forces articulation work.

20. Good crowdsourcing
=
Infrastructure &
good metadata
=
reusable, semantically
enriched, linkable data!*
*provided we do the work.

21. References:
Kelling, Steve (2011). "How to identify birds in flight." Keynote address at the
2011 meeting of the Association of Information Science and Technology. New
Orleans, LA.
Mak, Bonnie (2011). "The Database and Its Discontents." Paper read at the
Graduate School of Library and Information Science at the University of Illinois
at Urbana-Champaign's monthly History Salon.
Smith, Arfon (2011). Presentation at the Illinois Research Data Initiative
Opening Symposium.
Suchman, Lucy. (1995). "Supporting Articulation Work" In Computerization
and Controversy: value conflicts and social choices.
Acknowledgements:
Thanks to the CIRSS Student Research Group, Dean, Aaron and John W. for
awesome and much-needed feedback on this talk, and pretty much anyone who
has read/commented/not mocked our blog