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Where Do We Come From? What Are We? Where Are We Going?
Thomas FinholtSchool of InformationUniversity of Michigan
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Where Do We Come From? What Are We? Where Are We Going?, 1897, oil on canvas, Museum of Fine Arts, Boston
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Data as the instrument
“by-products as products”
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Examples
Past– public health reporting
Present– virtual observatory
Future?– car versus deer
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Network as the instrument
“sensors, everywhere, joined”
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Examples
Past– Bell system
Present– GPS and TEC plots
Future?– computational and data grids
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Global GPS Network (November 1996): Coverage at Ionospheric Heights
10 degree elevation mask. Intersection height of 400 km.
Source: http://iono.jpl.nasa.gov/sitemap.html
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Source: http://iono.jpl.nasa.gov/latest_rti_global.html
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Simulation as the instrument
“seeing beyond the field-of-view”
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Examples
Past– physical models
Present– theory/data closure
Future?– multi-scale
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UARC: Simulation and observational data
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Source: http://sparc-1.si.umich.edu/sparc/central/page/TomsTINGvsObserved
SPARC: Simulation and observational data
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Challenges
Source: American Automobile Manufacturers Association, http://www.automuseum.com/carhistory.html
Attempts to apply new technology are often framed in terms of familiar technology
First efforts are often awkward hybrids
It is hard to know where the seeds of greatness might lie...
Charles King’s “horseless carriage” (1896) Detroit, Michigan
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The culture of simulation
Concrete
Exploratory
Improvisational
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Derive a simulation design aesthetic
What makes a design good?– Mutability
Who does the designing?– “just plain folks”
What is a signature design achievement?– the Sims
Source: http://www.ea.com/eagames/official/thesimsonline/home/index.jsp?
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Tinkerers as change agents
They make sense of the world in light of experience
They need to play with applications to appreciate their function
True requirements may only become apparent after false starts
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Tinkering skills
Empathy -- can you see things through the user’s eyes?
Flexibility -- can you experiment?
Plagiarism -- can you find and assimilate successful innovations from other systems and services?
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Human-centered tinkering
Define requirements in terms of observed models
Test hypotheses in actual communities Use feedback to improve systems and
services
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Build:Intervene
Conceptualize:Observe models
Observe, Build
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Build:Intervene
Trials: Deploy, use, evaluate
Conceptualize:Observe models
Observe, Build, Test
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Observe, Build, Test, Modify
Build:Intervene
Trials: Deploy, use, evaluate
Modify:extend design,evolution
Conceptualize:Observe models
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Wired VS reality
More
Time
Performance
Less
hype
raw performance of technology
“real performance”
“reality gap”