Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Biotracker: Melding Human and Machine Capabilities to Document the World's Living Organisms
1. Melding human and machine
capabilities to document the
world’s living organisms
University of Maryland TMSP series
March 7, 2011
2. Project Team
Arijit Biswas (CS, Doctoral student); Anne Bowser (iSchool, Masters student); Jen Hammock (EOL);
Derek Hansen (iSchool); David Jacobs (CS, UMIACS); Darcy Lewis (iSchool, doctoral student);
Cyndy Parr (EOL); Jenny Preece (iSchool); Dana Rotman (iSchool, Doctoral student); Erin Stewart
(iSchool Masters student); Eric (CS, Undergrad student)
3. What we will talk about…
• Research aims
• Encyclopedia of Life (EOL)
• Scientists, citizen scientists, enthusiasts
• Identifying leaves:
– Machine vision approach
– Odd Leaf Out
– Field Mission Games
• Questions and Discussion
4. BioTracker system architecture
Community
Portal
Profiles, groups,
and species pages
Images,
Identifications, Maps,
Threaded discussion
information collection, clarification questions
upload
image
answers
Mobile Devices
with BioTracker app
Camera
Internet connection
Match recommendations
Q&A component
Biotracks map
Photos,
Biocaching
and
commentary
Enthusiasts
Computational
Tools
Image database
Shape descriptors
Image segmentation algorithm
Image recognition algorithm
Inference system
user
input
Possible
new
species
accuracy
estimate
Scientists
identification
and upload
5. First research question
• What are the most effective strategies for motivating
enthusiasts and experts to voluntarily contribute and
collaborate?
15. • 100+ partner databases
700 curators/1000s contributors/46,000 members
• 2.8 million pages
500 thousand pages with Creative Commons content
• Over 2 million data objects and >1 million pages with
links to research literature
• Traffic in past year: 1.7 million unique users, 6.2
million page views
EOL statistics
16. Scientists and volunteers
"Scientists often have an aversion to what nonscientists
say about science” (Salk, 1986)
Collaboration is based on several factors:
• Shared vocabulary, practices, and meanings
• Mutual recognition of knowledge, competency, and
prestige
• Motivation to collaborate
17. Motivations for participation
Participation in social activities stems from personal
and collective reasons
Egoism
Collectivism
Altruism
Principalism
Batson, Ahmad, Tsang, 2002
18. Pilot study – scientists’ motivational
factors
0
1
2
3
4
5
Egoism Collectivism Altruism Principalism
Senior
Junior
Other
Faculty/
research
position
19. Pilot study – volunteers’ motivational
factors
0
1
2
3
4
5
Egoism Collectivism Altruism Primcipallism
1-3
4-5
Egoism Collectivism Altruism Principalism
Years of
experience
20. Second research question
• How can a socially intelligent system be used
to direct human effort and expertise to the
most valuable collection and classification
tasks?
21. Mobile devices for plant species ID
• Build new digital collections
• Image-based search to assist in identification
• Make this available on mobile devices
• Use this platform to build user communities
• Collaboration with dozens of people at Columbia
University, the Smithsonian NMNH, and UMD.
22. New images
For Botanists: digitize
90,000+ Type Specimens
at Smithsonian
For EOL, people using mobile devices, highest
quality images of live specimens.
And for machines, images that capture leaf diversity
23. Computer Vision for species ID
Use a photo to search a
data set of known
species.
Goal is to assist the user,
not make identification
fully automatic.
1. Take a photo of a leaf
on a plain
background.
24. 2. Automatic segmentation and
stem removal
Segmentation relies on value and saturation of
pixels, EM algorithm, domain knowledge.
29. Incorporating games
into the Biotracker platform
Using games to direct human effort and computational
resources towards species identification and
classification
• Data Validation Games
• Field Data Collection Games
30. Odd Leaf Out
Using computer games for data validation and
algorithm refinement
31. Odd Leaf Out
Research Questions
• What will make this game more fun?
• What motivates users to play when the data is imperfect?
• How can the game assist with algorithm improvement?
32. Odd Leaf Out
Next Steps
• Continue User Testing
• Analyze Game Play Logs and Surveys
• Preferred version
• What aspects give most accurate data
• Does this provide useful feedback into LeafSnap algorithm
• Place game on Mechanical Turk for additional data
The United Nations has declared 2010 the International Year of Biodiversity in recognition of the importance of biological diversity and the looming biodiversity crisis. Biological diversity provides ecosystem services critical to our planet. As much as 90% of the needs of the world’s poorest people depend directly on biodiversity for food, fuel, medicine, etc. [1]. Each species represents a volume in a “living library,” as each has evolved solutions to nature’s challenges, solutions that can benefit human society. For example, the genomics revolution and half of our synthetic drugs were made possible by understanding the characteristics of particular species [2]. Yet the rate of species loss is currently 100 to 1,000 times estimates of historical extinction rates, and these rates are increasing with climate change [2]. Recent assessments indicate that, for example, nearly 25% of mammals and one-third of amphibians are endangered or threatened [3].
Scientists alone cannot end the biodiversity crisis. Progress in the conservation and sustainable use of biodiversity will depend on the interface of science with both policy and the public. This is not only because the public must appreciate and understand biodiversity in order to be motivated to conserve it. There are nearly 2 million known species and potentially millions more are still undocumented. Without help, professional biologists will be unable to describe many of these species before they disappear from the planet, especially those in biodiversity-rich but economically poorer countries [4].
Public participation can address the biodiversity crisis in several areas. One area is assembling existing knowledge on the 1.9 million species known to science. Doing so can accelerate the pace of research and new species description by making freely available, searchable, and re-usable the information currently in libraries or in local databases inaccessible to most of the world’s scientists. Addressing this need is the primary mission of the Encyclopedia of Life (EOL, http://www.eol.org), an international project headquartered at the Smithsonian’s National Museum of Natural History. In addition to mash-ups of existing scientific databases, we are combining a crowd-sourcing approach with expert review to achieve a high-quality central clearinghouse for species information.
Most citizen science . . .
Is driven by scientists
Is analyzed by scientists
Works best for charismatic species
Works best for simple observations or classification
Requires training – so sustained engagement desirable
Bioblitz is a 24-hour inventory of species in a particular location
So, the approach of EOL is rather different than many other sites. EOL is a giant mashup that creates pages, that are then available for curators (mostly credentialed scientists) to assess and rate, or for anybody to provide comments or tags.
Research Questions
How can we motivate users to continue to play when we are dealing with imperfect data that will sometimes provide two “correct” answers?
What useful data for algorithm refinement can a game of tagging the least-similar image provide?
How can data provided by novices users be employed to enhance the work of experts?
Implications
Improving machine vision algorithms based on human performance.
Minimizing the number of data sets that must be hand-verified by scientists and experts
Providing insight on what image factors provide for the best human identification of leaves
Providing information on the extent that other game motivation techniques1 work for scientific identification games