e bird-bio diversity

1. eBird: A Human/Computer Learning
Network for
Biodiversity Conservation and Research
R.VINOTHKUMAR, MCA.,
Computer Literacy Programmer
Periyar Arts College, Cuddalore- 1

2. What is eBird?
• eBird is a global, internet based platform for gathering observation
of birds, and for birders to maintain records of their sightings. It is
launched in 2002 by Cornell University Laboratory and National
Audubon Society.
• eBird an online database of bird observations providing scientist,
researchers and armature naturalists with real-time data about bird
distributions and abundance.
• eBird has been described as an ambitious example of enlisting
armatures to gather data on biodiversity for use in science.
• eBird, a citizen science project that takes advantage of human
observational capacity and machine learning methods to explore
the synergies between human computation and mechanical
computation.

3. call this model a Human/Computer Learning Network,
whose core is an active learning feedback loop between
humans and machines that dramatically improves the quality
of both, and thereby continually improves the effectiveness
of the network as a whole.
Human/Computer Learning Networks leverage the
contributions of a broad recruitment of human observers and
processes their contributed data with Artificial Intelligence
algorithms leading to a computational power that far exceeds
the sum of the individual parts.

4. Why eBird?
• By gathering and storing bird sightings, eBird
complies baseline data on bird distribution and
abundance, and disseminates this information for
public and scientific use.
• The transformational power of todays computing,
together with information and communication
technologies, are providing new opportunities to
engage the public to participate in and contribute
to a myriad of scientific, business and technical
challenges.

5. • For example,
citizen-science projects such as
Galaxy Zoo, eBird, and Foldit demonstrate the power of
crowd sourcing for investigating large-scale scientific problems.
These and similar projects leverage emerging techniques
that integrate the speed and scalability of mechanical
computation, using advances in Artificial Intelligence (AI), with
the real intelligence of human computation to solve
computational problems that are beyond the scope of existing
algorithms
Human computational systems use the innate abilities of
humans to solve certain problems that computers cannot solve.
Now the World Wide Web provides the opportunity to engage
large numbers of humans to solve these problems.

6. eBird Platform
The eBird platform is gradually being tailored to
make it more friendly and useful for Indian birders.
Various bird events and projects in India use eBird
as a platform for gathering and managing data.
 The Web can be used to engage large numbers of
participants to actively collect data and submit it to
central data repositories. Projects such as eBird,
engage a global network of volunteers to report
bird observations that are used to generate
extremely accurate estimates of species
distributions.

7. • Now systems are being developed that employ
both human and mechanical computation to
solve complex problems through active learning
and feedback. These Human/Computer Learning
Networks (HCLN) can leverage the contributions
of broad recruitment of human observers and
process their contributed data with AI algorithms
for a resulting total computational power far
• exceeding the sum of their individual parts.

8. Figure 1. An HCLN example. Human observers and AI processes synergistically
improve the overall quality of the entire system. Additionally, AI is used to
generate analyses that improve as the quality of the incoming data improves.

9. eBird goal
eBird’s goal is to maximize the utility and
accessibility of the vast numbers of bird
observation made each year by recreational and
professional bird watchers.
The observation of each participant joint
those of others in an International network.
The data is then available via internet queries
in a variety of formats.

10. Geographical Map

11. • Hundreds of thousands of birders use eBird,
which now has a repository of 200 million
records, with 250, 000+ from India.
• As of July 2013, over 100,000 unique user
have submitted ten thousand of checklists
more than 100,000,000 observations, and
data for over 10,240 species to the program.
• http://www.birdcount.in/ebird/
eBird-World Report

13. Checklists Submitted:
144,109
Total Species Observed:
4,296
Total Individual Birds Counted:
17,748,756
Statistics last updated on February 28, 2014

14. Features
eBird documents the presence or absence of
species, as well as bird abundance through checklist
data. A web interface allows participants to submit
their observations or view results via interactive
queries of the database.
Internet tools maintain personal bird records and
enable user to visualize data with interactive maps,
graphs, and bar charts.
All these features are available in English, Spanish,
French and Portuguese.

15. • It is a free service. Data stored in a secure facility and
archived daily, and accessible to anyone via the eBird
website and other applications developed by the global
biodiversity information community.
• Ex: AKN(Avian Knowledge Network) which integrates
observational data on bird populations across the western
hemisphere and is a data source for the digital
ornithological reference Birds of North America.
• It turn, the AKN feeds eBird data to international
biodiversity data systems, such as the Global Biodiversity
Information Facility.

16. eBird Challanges
• Challenge 1: Species Identification
• Challenge 2: Maximizing Participation
• Challenge 3: Identifying the Synergies
Between Humans and Machines
• Challenge 4: Species Distribution Models

17. Conclusion
• If you are interest to save birds you will become a
citizen scientist.
• To share this information to your friends and relatives..
• By guiding the observers with immediate feedback on
observation accuracy, the Artificial Intelligence
processes contribute to advancing expertise of the
observers, while simultaneously improving the quality
of the training data on which the Artificial Intelligence.
• processes make their decisions. The outcome is
improved data quality that can be used for research
and analysis.

18. References
• www.ebird.com
• www.wikipedia.com/ebird
• www.uyiri.wordpress.com
• www.birdcount.in/ebird/‎

19. I can't imagine anything more
important than air, water, soil, energy
and biodiversity. These are the things
that keep us alive.
Queries?