Data Driven Societies Digital & Computational Studies Bowdoin College March 26, 2014 Professor Gieseking Lecture Slides "Code/Spaced"

1. Data Driven Societies:
Code/Spaced
Professors Gaze & Gieseking

2. Multiple
Intelligences Theory
✦ Musical–rhythmic and
harmonic
✦ Visual–spatial
✦ Verbal–linguistic
✦ Logical–mathematical
✦ Bodily–kinesthetic
✦ Interpersonal
✦ Intrapersonal
✦ Naturalistic

3. Cognitive
Mapping
Tolman 1948

4. Mental
Mapping
Lynch 1960

5. Mental
Mapping
Milgram & Jodelet 1970

6. Create a map of your Bowdoin experience. Map whatever you think
pertinent to explain your time at Bowdoin.
!
Create a legend.
!
Groups:
First-years
Sophomores
Juniors
Seniors (three groups)

7. What does code have to do with space?

8. Code/Space:
Software-Sorting
The term software-sorting captures the crucial and
often ignored role of code in directly, automatically and
continuously allocating social or geographical access
to all sorts of critical goods, services, life chances or
mobility opportunities to certain social groups or
geographical areas, often at the direct expense of
others.
-Graham (2005, 3)

9. ✦ Over half the world’s population lives in cities
✦ Little attention is paid to the billions of lines of code that run
our cities — why is code invisible?
✦ Why does visualization take off at this moment?
✦ Examples: mobilities, GIS, CCTV
✦ Calls for a “spatial politics of code”
Code/Space

10. Code/Space:
Mobilities
NYTimes & scoop.it
✦ 171 LED lights at Newark Airport (top)
recognize long lines *and* suspicious
activity and alert staff
✦ Issues: airport security, pay-per-
journey roads, packet switching by
class and corporation, call center
rankings
✦ Outcomes: reproduces data rich vs.
data poor
✦ Possible solutions: regulate the
Internet through FCC like a utility

11. Code/Space:
GIS
Baltimore land use 1986 v2000 - NASA
✦ NASA “SLEUTH” urban land
use remote sensing satellite
—> predict & design city
development
✦ Issues: predictive GIS
assumes data is only reality,
neighborhoods overtake
Internet presence
✦ Outcomes: reproduces data
rich vs. data poor, modeling
via predictive algorithms only
leaves little room for change

12. Code is…
GIS Layers
✦ Points
✦ Lines
✦ Polygons
!
!
!
✦ Layers
!
✦ Geographic Information Systems (GIS)
!

13. Code/Space:
CCTV
✦ 4.2 million CCTV in the UK (1
for every 14 people)
✦ Issues: algorithmically driven
biometrics (facial recognition,
micro-expressions) with little
accuracy yet great trust
✦ Outcomes: invisibility behind
the cameras and algorithms
behind them, normalize those
who tend to be excluded,
decontextualize observations
wealthwire.com

14. How can visualization make more
transparent uses of and better the
experience of different spaces?

15. Shifting Maps in
Code/Space

16. Shifting Maps in
Code/Space

17. Shifting Maps in
Code/Space

18. Shifting Maps in
Code/Space

19. Jabbour on
Map Design
✦ Prioritize your aim(s) & audience
✦ Include the essentials & leave out the clutter
✦ Use families of color and related shapes to create relational
notions of time and space
✦ Select the scale your users should relate to the visualization
✦ Test out your visualizations on the right audience
✦ Work through the trade-offs for visualization outcome

20. Guess: which of these maps is the most
popular NYC subway map among
young New Yorkers right now?

21. The
Weekender

22. Lab: Social
Explorer

23. Next Class: Mar. 31
✦ Today: code/spaced
!
✦ Readings: Lingel, Nakamura
!
✦ Lecture: 3/31 @ 7pm
Lancaster “Fb is Anti-Drag”
!
✦ Blog post: due Wed the 2nd -
reflect on maps
!
(Rejoice: soon this snow image and the
snow itself will be gone, gone, gone)