David Baker Sid Banerjee David Cooper Ashish Goel Elizabeth Lorns Sandeep Neema Andrew Sallans The Need Social networks and Internet communications have revolutionized many other collaborative tasks ID: 554207
Download Presentation The PPT/PDF document "New Approaches and Tools for Doing Netwo..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
Slide1
New Approaches and Tools for Doing Networked Science
David Baker, Sid Banerjee, David Cooper,
Ashish
Goel
, Elizabeth
Lorns
,
Sandeep
Neema
, Andrew
SallansSlide2Slide3
The Need
Social networks and Internet communications have revolutionized many other collaborative tasks
Spectacular success from early experiments (
PolyMath
/
FoldIt
)
Opt-In science: anyone can choose to participate if they have the right expertise
Growing number of collaborators in scientific work
Data sources are growing exponentially
Automated tools for discovering scientific information (
eg
.
DeepDive
) show early promise.
The time seems ripe for DARPA investment in a program.Slide4
Automated Knowledge Assistant
Exploring or learning a new field
What are key papers and concepts in a new field?
Unsolved problems and experts
Concept Maps and Visualization Tools
Augmented search, where searching reveals related concepts, key research results, other communities which have studied the same concept
Using humans to direct the creation of this map
Identifying research that needs reproductionSlide5
Incentives and Mechanisms for Opt-In Collaborations
A formal understanding of incentives in collaborative research
vs
competition, and innovative funding mechanisms
Understanding the nature of rewards: intellectual credit, intellectual property, funding
Endogenous creation of
rewards
Team formation
How to encourage confirmatory as well as exploratory research?
Understanding and designing large-scale
crowdsourced
research frameworks — drawing lessons from Fold-It, etc.
Incentivizing diversity/exploration in research
Theoretical models? Connections with bandit problems?
Team formation
Experiments in Fold-It/
Topcoder
competitionsSlide6
Platforms and Experimentation
Existing Examples
The Science Exchange Network
Topcoder
/
FoldIt
Polymath/K Base
A platform for collaborative opt-in research among experts
A platform for opt-in research among the general public
Eg
. Expanding the
FoldIt
paradigm to drug discovery and
neuro
-degenerative disease
Collaborative design and visualization
Experiments with different incentive mechanisms
Common standards and web APIs for data access and preparationSlide7
Validation and integrity of research
Goal: Improving reproducibility of biological research
How
R
eplication studies
Experiment with separation of experiment creator and conductor
Characterization of biological protocols in terms of reproducibility
Automating Reproducibility
Tools for capturing workflowSlide8
Some Potential Participants
Astronomy community (
eg
. Chris
Lintott
–
Zooniverse
)
David Baker and collaborators (
FoldIt
/
eteRNA
)
Michael Bernstein (Stanford -- Crowdsourcing platforms.
Eg
. Collaborative writing)
Center for Open
Science
Distributed Biology Team
Yiling
Chen (Harvard – User Generated Content)
Ashish
Goel
(Stanford – markets and social algorithms)
Arpita
Ghosh
(Cornell – User Generated Content)
Karim
Lakhani
(Harvard –
Topcoder
experiments)
Sandeep
Neema
(Vanderbilt – collaborative visualization)
Chris Re (
DeepDive
)
SETI@ home and Rosetta@ home and
Folding@home
The Science Exchange network
Terry Tao (UCLA), Tim
Gowers
(Polymath)
Luis von
Ahn
(CMU – Crowdsourcing platforms,
eg
. Human Computation)