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Visual Conversations with Data

              Tony Hirst
   Dept of Communication and Systems,
           The Open University
Figure 1 Sensor Traces

is a chart that’s designed to be read
IT TELLS A STORY
IT TELLS THE
ROBOT’S STORY
http://www.musik-therapie.at/PederHill/Structure&Plot.htm
Data
conversations
Conversations
around what’s not
     there…
Presentation Graphics
         vs.
   Visual Analysis
Explanatory visualization
Data visualizations that are used to
transmit information or a point of
view from the designer to the
reader. Explanatory visualizations
typically have a specific “story” or
information that they are intended
to transmit.

Exploratory visualization
Data visualizations that are used by
the designer for self-informative
purposes to discover patterns,
trends, or sub-problems in a
dataset. Exploratory visualizations
typically don’t have an already-
known story.
Visual Analysis
      or
 Presentation
  Graphics?
Algorithmic
Visualisation
ggplot2 (R)

d3.js (Javascript)
ggplot() +
geom_linerange(data = d1,aes(x= car, ymin = ymin,ymax = ymax)) +
geom_point(data = d2,aes(x= car, y= value,shape = variable),size = 2) +
opts(title="F1 2011 Korea nRace Summary
Chart",axis.text.x=theme_text(angle=-90, hjust=0)) +
labs(x = NULL, y = "Position", shape = "")
http://eagereyes.org/blog/2011/you-only-see-colors-you-can-name
Exploiting
Structure
Hierarchical data and treemaps - medals




Pivot tables
Macroscopes
aka “seasonal subseries”
Show me the difference…




        Let me see the difference…
Can I see the difference..?
Where exactly..?
Emergent views
 of structural
  properties
[ Freemind ]
Have you had a visual
conversation with any
 of YOUR data lately?
blog.ouseful.info

@psychemedia

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Visual Conversations

Editor's Notes

  1. Visual Conversations with Data Datasets often contain amyriad number of stories,but how can we best make sense of them? Maybe avisual conversation can help? 30 mins
  2. Example of data powered storytelling in YXR175/TXR120 robotics activity
  3. Brief explanation of chart and what the labels are.
  4. Wheel diameter, actual distance travelled
  5. Livescribes, process of creation of the rich picture… the diagramming is an active storytelling process that builds on itself amd has potentially many narrative threads
  6. Also how you position marks on a canvas in relation to each other
  7. Collaborative commentary
  8. The top, blue strip shows the gear (1 to 7); the green strip shows the throttle pedal depression (0-100%), and the red strip shows the brake (0-100%). The light blue strip is a composite of the previous three strips. The whiter the pixel, the closer it is to 100% throttle in 7th gear with no braking.The bottom two traces show the longitudinal and lateral g-force respectively. For the longitudinal trace, red shows braking – being forced into the steering wheel; green shows acceleration – being forced back into your seat. You’ll see the greatest g-force under braking occurs when the brakes are slapped full on… (the red bits in the third and fifth traces line up). For the latitudinal g-force, the red shows the driving being flung to the left (i.e. right hand corner), the green shows them being pushed out to the right.
  9. Emergent Social Positioning: origins: 1.5 degree egonet (how followers follow each other, how hashtaggers follow each other)- projection maps from followers to folk they commonly follow;-- projection maps from hashtaggers to folk they commonly follow- projection maps from friends to folk who commonly follow them