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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Where Do We Come From? What Are We? Where Are We Going? Thomas Finholt School of Information University of Michigan
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu n 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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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Data as the instrument “by-products as products”
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Examples n Past –public health reporting n Present –virtual observatory n Future? –car versus deer
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Source: http://www.ph.ucla.edu/epi/snow.html
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Network as the instrument “sensors, everywhere, joined”
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Examples n Past –Bell system n Present –GPS and TEC plots n Future? –computational and data grids
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu 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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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Source: http://iono.jpl.nasa.gov/latest_rti_global.html
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Simulation as the instrument “seeing beyond the field-of-view”
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Examples n Past –physical models n Present –theory/data closure n Future? –multi-scale
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC: Simulation and observational data
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Source: http://sparc-1.si.umich.edu/sparc/central/page/TomsTINGvsObserved SPARC: Simulation and observational data
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Challenges Source: American Automobile Manufacturers Association, http://www.automuseum.com/carhistory.html n Attempts to apply new technology are often framed in terms of familiar technology n First efforts are often awkward hybrids n It is hard to know where the seeds of greatness might lie... Charles King’s “horseless carriage” (1896) Detroit, Michigan
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu The culture of simulation n Concrete n Exploratory n Improvisational
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Derive a simulation design aesthetic n What makes a design good? –Mutability n Who does the designing? –“just plain folks” n What is a signature design achievement? –the Sims Source: http://www.ea.com/eagames/official/thesimsonline/home/index.jsp?
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How to tinker Source: http://www.tam.cornell.edu/~ruina/hplab/
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Tinkerers as change agents n They make sense of the world in light of experience n They need to play with applications to appreciate their function n True requirements may only become apparent after false starts
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Tinkering skills n Empathy -- can you see things through the user’s eyes? n Flexibility -- can you experiment? n Plagiarism -- can you find and assimilate successful innovations from other systems and services?
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Human-centered tinkering n Define requirements in terms of observed models n Test hypotheses in actual communities n Use feedback to improve systems and services
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Conceptualize: Observe models Observe
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Build: Intervene Conceptualize: Observe models Observe, Build
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Build: Intervene Trials: Deploy, use, evaluate Conceptualize: Observe models Observe, Build, Test
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Observe, Build, Test, Modify Build: Intervene Trials: Deploy, use, evaluate Modify: extend design, evolution Conceptualize: Observe models
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC 5.0 interface
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC 6.0 interface
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu SPARC interface
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu NEESgrid interface
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu NEESgrid interface
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Wired VS reality More Time Performance Less hype raw performance of technology “real performance” “reality gap”
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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu What keeps designers honest? n Give users objects to think with (scenarios, mock-ups, prototypes) n Be patient…let users convince themselves n Know where you’ve been (collect baseline data) and what’s changed (collect data as you go along)
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