if we build it will they come? creating the right cyberinfrastructure for dispersed collaboration
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If we build it will they come? Creating the right cyberinfrastructure for dispersed collaboration. Thomas A. Finholt School of Information University of Michigan. Outline. The field of dreams Recommendations of the NSF panel Challenges Group Cultural Prospects. - PowerPoint PPT PresentationTRANSCRIPT
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If we build it will they come? Creating the right cyberinfrastructure for
dispersed collaboration
Thomas A. FinholtSchool of InformationUniversity of Michigan
SCHOOL OF INFORMATION UNIVERSITY OF MICHIGANwww.si.umich.edu
Outline The field of dreams Recommendations of the
NSF panel Challenges
– Group– Cultural
Prospects
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If we build it, they will collaborate
Data and access to data represent fundamental barriers to dispersed collaboration
Efficient movement of vast amounts of data is a prime rationale for cyberinfrastructure
Federating, visualizing and mining data are principle challenges
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Researchers
DataFacilities
Synchronized dataSynchronized data and imagesData discovery
Automatic archivingSimulation codesHybrid experiments
TeleoperationTeleobservation
Synchronous communicationAsynchronous communication
The collaboratory concept
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NEESgrid
The collaboratory component of the George E. Brown, Jr. Network
for Earthquake Engineering Simulation (NEES)
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Bhuj, India. One of the towers of this apartment complex totally collapsed,and the central stairway leaned on another building of the complex.
Photo courtesy of Dr. J.P. Bardet, University of Southern Californiahttp://geoinfo.usc.edu/gees/RecentEQ/India_Gujarat/Report/Damage/Bhuj/Bardet_Feb18.html
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Shake table: Nevada, Reno
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Reaction wall: Minnesota
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Centrifuge: UC Davis
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Wave basin: Oregon State
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Field structural: UCLA
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Field geotechnical: Texas
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NEESgird interface
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NEESgrid: Simulation and observational data
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NEESgrid: Simulation
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Cultural challenges
NEES– “earthquake engineers” vs. “IT specialists”
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Earthquake engineers – in Hofstede’s scheme Power distance
– Hierarchical– Bias toward seniority
Individualist– “My lab is my empire”– Solo PI model
Masculine– Adversarial– Competitive
Uncertainty avoidance– Highly skeptical of new technologies– Extremely risk adverse
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IT specialists – in Hofstede’s scheme Power distance
– Egalitarian– Bias toward talent
Collectivist– Use the Internet to create worldwide communities– Project model
Masculine– Adversarial– Competitive
Uncertainty avoidance– Extremely open to new technologies– Extremely risk seeking
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Agreeing on termsTerm What grid specialists
heard What earthquake engineers heard
“user” HPC users
earthquake engineers
“community” NEES awardees broad array of earthquake engineers, including researchers and practitioners, in the diverse settings where earthquake engineering occurs (centers, under-represented institutions, under-resourced institutions)
“requirements” Description of high level system architecture
Description of detailed user requirements and their relationship to functional specifications
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Building it so they will come…
Dispersed teams performed poorly relative to collocated teams
Performance suffered due to coordination overhead
More successful dispersed teams adopted explicit coordination mechanisms
The ideas on this slide are from an NSF report by Cummings and Kiesler (2003), available at:
http://netvis.mit.edu/papers/NSF_KDI_report.pdf
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NEES MCU Usage
0
100
200
300
400
Jan
Feb
Ma
rch
Ap
ril
Ma
y
Jun
e
July
Au
gu
st
Se
pte
mb
er
Oct
ob
er
No
vem
be
r
De
cem
be
r
Jan
ua
ry
Feb
rua
ry
Ma
rch
Ap
ril
Ma
y
Jun
e (
est
)
Month
Po
rt H
ou
rs Commons
Michigan / USC
Total
Use of H.323 videoconferencing
UNR Demob c d
a = initial ES-TF meeting; b = ES-TF meeting time changed; c = succession to new ES-TF chair; d = change to biweekly ES-TF meetings
a NSF LAN meetings
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Prospects How important is data federation?
– Some earthquake engineers use data from others…but they all have remote collaborators
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Some use data from others…
0% 20% 40% 60% 80% 100%
Do you use data you collect? (2001)
Do you use data you collect? (2002)
Do you use data collected by othersworking with you? (2001)
Do you use data collected by othersworking with you? (2002)
Do you use data collected by othersindependent of you? (2001)
Do you use data collected by othersindependent of you? (2002)
Not usually or never
sometimes
usually or always
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…but everyone has remote collaborators
2001 2002
Item Mean SD Mean SD
Number of collaborations you are currently involved with
2.5 6.1 2.3 4.7
Number of collaborations with remote participants
1.4 3.2 1.3 3.6
Number of collaborators on your primary collaboration
5.7 7.1 6.1 7.3
Number of collaborators from prior collaborations in primary collaboration
1.6 3.1 1.7 3.0
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Conclusions The cyberinfrastructure vision places great emphasis
on collaboration primed by access to data Evidence suggests that communication and
coordination may be stronger determinants of collaboration success
Observation of dispersed teams shows great energy expended on ad hoc coordination
Transformation of scientific and engineering work via cyberinfrastructure may be more easily achieved by solving problems of coordination and communication