1. 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

2. 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

3. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Data as the instrument “by-products as products”

4. 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

5. Source: http://www.ph.ucla.edu/epi/snow.html

6. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Network as the instrument “sensors, everywhere, joined”

7. 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

8. 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

9. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Source: http://iono.jpl.nasa.gov/latest_rti_global.html

10. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Simulation as the instrument “seeing beyond the field-of-view”

11. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Examples n Past –physical models n Present –theory/data closure n Future? –multi-scale

12. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC: Simulation and observational data

13. 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

14. 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

15. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu The culture of simulation n Concrete n Exploratory n Improvisational

16. 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?

17. How to tinker Source: http://www.tam.cornell.edu/~ruina/hplab/

18. 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

19. 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?

20. 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

21. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Conceptualize: Observe models Observe

22. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Build: Intervene Conceptualize: Observe models Observe, Build

23. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu Build: Intervene Trials: Deploy, use, evaluate Conceptualize: Observe models Observe, Build, Test

24. 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

25. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC 5.0 interface

26. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu UARC 6.0 interface

27. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu SPARC interface

28. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu NEESgrid interface

29. SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN www.si.umich.edu NEESgrid interface

30. 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”

31. 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)