Scott Poole, UIUC; Noshir Contractor, Northwestern;
Mark Hasegawa-Johnson, UIUC; Feniosky Pena-Mora,
Columbia; David Forsyth, UIUC; Kenton McHenry,
UIUC; Dorothy Espelage, UIUC; Margaret Fleck, UIUC;
Alex Yahja, National Center for Supercomputing Apps

 Socio-cultural consequences of group decisions
 Inability to collect, analyze, and manage
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High resolution,
High quality,
 High volume interaction network data
 Effective computer-aided collaboration among
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Scholars
Scientists
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Students
Volunteers
 Stakeholders

 We understand small teams co-located (1-6 persons) and we think we understand large aggregations of
1000s
 We don’t understand large teams: 8-25, 25-70, 50-300,
350-500, 400-1000—the sweet spot of scholarly collaborations and conferences
 Current studies are surveys and case studies, not direct observation, the gold standard
 No tech to study these even though we coalesce in natural groups of size 2, 5, 15,…
 Spatial dispersion and movement make big difference

 Many critical groups are of this size:
 Design Teams
 Scholarly Collaborations
 Cultural Studies
 Legislative Bodies
 Disaster Response Teams
 Archaeology Teams
 Medical Teams
 Military Units

 Cyber-enabled Discovery and Innovation (CDI) program, National Science Foundation
 Two Million Dollars Grant
 National Center for Supercomputing Apps
 Office of the Vice Chancellor for Research, University of Illinois
 Year 2 of Five Year Project
 Project “GroupScope”

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End-to-end system from data capture to analysis to user and team engagement
Video cameras to capture video and audio, of
 Study subjects such as children on playground
 Scholars and researchers executing the study—in team and individually
Synchronization of video and audio data
Annotation of video and audio
Coding of video and audio
Management of video and audio data
Analysis of video and audio; scenario simulation and machine learning
Community involvement

Data
Acquisition
(cameras,
Kinect, audio recorders, GPS, iPhones, iPads)
First-order Data (audios, photos, videos, sensor data)
Data
Management
(Medici content management,
ELAN transcription)
What-if
Scenario
Simulation and
Machine
Learning
Network analysis, Group identification,
Interaction categorization
Second-order Data (visual, audio and text annotations, coding and metadata)

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Professors and graduate students as primary research participants
Students help annotate videos and audios of
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 study objects and artifacts research activities of professors and research assistants
Interested folks help transcribe, translate, and annotate videos and annotate
 Multi-lingual collaboration enabled
Scenario “what-if” analyses of interactions and events
Annotated videos will “live” across time and place
 Insights, inspirations, and moments are recorded and not lost to time and place

 “GroupScope” tool is designed to provide
 Computer-assisted collaboration among human teams
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Natural and native human and professional socialnetworking—synergistic human machine effort
Scholarly collaboration tool with native domain-specific design and interfaces
Natural collaboration space
 By your consent, putting up video cameras to get PNC
2017 networking?
 Will put up video cameras for NSF Radical Innovation
Summit 2013