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Outline

• Background (Joy Mountford)
• Data Visualisation (Java Processing movies of
  working applications)

• Ubiquity is here (where is the interface?)
About Joy...

• Current: Osher Fellow at Exploratorium
• Recent :Yahoo,VP of Design Innovation and UED
• Properties: Y! Mail, Messenger, Front Page, My
  Yahoo, Groups, Photos

• 21 years of international University Design Expo:
  touched 4000 students world-wide
Honeywell - An interface (Dreyfus)
Space Shuttle (1990s)
Featuritis leads to poor consumer use (still!)




                                         6
Apple: QuickTime controller (1988)
Designing Interaction Bill Modridge (06)
Lego Music Composer ’03
9
LinkMark 00




              10
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Yahoo front page 2005
Personal Information Manager 2006




                                13
Y! personal information manager




                                  14
Y local offers relevant information




                                      15
Opportunity....

• We can start ‘understanding’ real time data to show
  what ‘we’ do/are

• Opportunity now is huge to actually use
  information data corporations gather

• Uses are both consumer facing, and for internal
  diagnostics, and to deliver useful content and
  personalised services
McKinsey report 2009

• In next decades the ability to take data, to be
  able to understand it, to process it, extract value,
  to visualise and communication it, is going to be
  an important skill in next decade.

• Not just at professional level, but all levels
• We have essentially free and ubiquitous data
• Scarce resource is ability to understand and
  extract value
Statistics and graphs

• Long history of graphical communication
• “How to lie with statistics” etc....
• Selection of data parameters/styles depends on
  task and who is asking for the answer

• Understanding of data displays is very individual
• What is a billion? (US/UK differ)
Data Numbers/Freq                          Visual Format

                     Data                Visual    Presentation      User
Raw Data
                   Streams               Style         form          Task

           Data                Visual                            View
     Transformations         Encodings                      Transformations
Accuracy of visual
   techniques
   Position
      Slope
              Angle
     Area

              Volume
    Colour
Moore’s Law ‘65
Sun position over time
         1626
Belousav-Z reaction
     over time
1856: Mortality causes:
 Florence Nightingale
XBox Tableau tool (MS)
Cone Tree (Xerox)
Sense.us
work force professions
             Flouride starts around here?


Dentistry




     1880   1965 2000
Consumers Q +
  comment
Group comments
   collected
Two styles data
              (Wattenberg)
• Voyager - focuses on visualised
  data.

• Actively involved with data to
  understand

• Voyeur - focuses on comment
  listings

• Investigates others explorations
Sense.us: % Dentists
  and technicians



         Dentist


  1850      1940   2000
New England report
• Framingham study data, 1948
• 1948 10% obese
• 1985 18% obese
• 2009 40% obese
• Fast food started and then network took over
• Spouse obese increased risk by 37%
• Friend obese increased risk by 171%
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Understanding Data

• Attraction of charts starts initial interest, but aim
  to increase consumer engagement and exploration

• Goal to build user interfaces to support and
  encourage involvement

• Visual sense making can be social - as well as
  collaborative
Exploratorium SF




                   36
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Slime on peat: diatom
 5,000 magnification
Fungal arms:
500 magnification
Book source: debate
  over techniques
Chris Jordan

• 32,000 Barbies 60x80 inch
• Number of elective breast augmentation
• Performed monthly in US 2006
• Graduation gift
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Art can Educate


• Different visual style hepls understanding
• Different visual styles appeal to folks
• Accidental discovery has big impact
Design Innovation Y! team

 
 
 
 Ben Clemens
   
 
 Aaron Koblin
   
 
 Michael Chang
   
 
 Doug Fritz


 
 
   
   S. Joy Mountford
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Ben Clemens, Aaron
Koblin, Michael Chang
Approach for Data Viz

• Data can attract
• Data can be ‘useful’
• Data can now be real time ‘dynamic’
• Put data around people to change POV
• Present in various forms
US flight paths (Koblin)
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Y! Answers
• Use community to answer Qs
• Created vibrant on-line community pulse of ‘what is
  happening’

• System created for accreditation of quality answers
• Potential for bloggers
Y!Answers cloud (Chang)
Traffic


• Use to replan your driving routes
• Use to dispatch ambulances etc
• Use to architect plan cities
Y! Local (Koblin)
J.Yamashita ‘07
Personalized DNA Art
Multi touch Table
    (MOTO)
FlickR

• Built custom multi-user multi-touch surface
• Gesture connects us to the data
• GeoTagged photos showing what else is happening live
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
FlickR: multi-user touch table
         (Chang 07)
SMS traffic New Years (NL)


Koblin ’08
Mail activity

• 2 hour increments of world-wide market traffic
• Shows relative sizes very clearly
• Showed Ham and Spam
• Located a server data loss from a pulse
• Aggregate view shows things otherwise ‘lost’
•Y
NYTE data

• Globe encounters show volumes of internet data
  between NY and world over 24 hours

• Real time continuous update
• Larger glow implies greater IP flow
• Collaboration: Sensible cities MIT, ATT ,Y!
• MOMA New York show of live data, Feb 08
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Search query bursts
• Active key word searches (rate of change)
• Use reverse IP look up for geo location-data
  address locations

• Activity plotted as a particle system
• Time-lapse queries from geo-locations plotted
• Feasible in ‘real time’ for particular users’
  interests
Y! search box
Real time editorial ‘clicks’
           on
Data information

• Search moves to discovery (decision)
• Opportunity now to use real time data
• Internet business is about personal delivery of
  useful, relevant content/ads dynamically to
  consumers
Ambient Interfaces
Internet Archive (Kaehle)


• Machine readable versions of all out of print books - free
• Tool for librarians, museums and consumers
• Bookscape for image browsing
• Dynamic resampling of image data inside 1 zoomable space
3D interactive Internet Archive
 bookscape browser (Chang)
Multi-user multi-touch
    found poetry
Personal tools

• Tagging of limited use with large info sets
• Find all related information
• Search anonymously across those with similar
  habits/interests

• Surface want I might want
Clustering on content
    (D. Fritz ’08)
Technical approach
• Tag co-occurrence defines distance algorithm
• Hierarchical clustering algorithm defines
  dendrogram

• Recursively search dendrogram to find clusters of
  optimal cohesion, while selecting a meaningful
  human size

• Hierarchical clustering slower, but gives better
  results with smaller data sets
Y!Haus lessons from
           Data Viz

• Information can be provided in ambient personal
  widgets

• Displays can be continuous, both in foreground as
  well as background

• Animation gets initial interest, but goal is to
  encourage understanding
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Crowd potential

• Crowd sourcing powerful - not directly social
• Isolated but part of an anonymous group
• Little payment or reinforcement
• People want to contribute to the whole: with and
  without anonymity

• Used Mechanical Turk (Amazon)
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Draw sheep facing left for .02 cents
 40 days for 10000 sheep (Koblin)
10,000 sheep on poster
10,000 Cents (Koblin)
created unique $100 bills
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Consumers

• People want to extend their fame
• Hunger to understand themselves relative to others
• Some happy to participate anonymously, others
  publically

• All of us becoming curators of own presence(s)
What and where is the
       interface
• Ubiquitous computing is here
• Interface transparency arrived
• Art and maker community is forging ahead
• Technologists need to create safe ways of
  convincing people to allow access to their
  personal data for benefit

• Personal need for selective cloaking
Examples of user
          ‘inclusion’
• Unaware
• Partially shown with no choice
• Shown with choice
• Unclear effects
• Confusion
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
eCloud San Jose airport (Koblin)




            Text
95
Screens at IAC

• 6-8 15ft high wall interactive displays
• NYU ITP graduate play space, some curated
• IAC headquarters, New York
• Web properties and media and newspaper taking lead
  with new media
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Moeller San Jose airport ’10:
pins on sheets over parking lot




                                  99
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
103
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
105
106
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
Fire Fly Dress (Orth)
Music Perfume bottles
      (MIT ‘01)
NYU: moving brooch
NYU worn printer
CCA: Light sensors cooked into lollipops
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
CCA: Real grass moves video:
 grown in sensor filaments




            Text
Bar scene
IR light color changing
      Coke bottles
• Good Guide (mobile)
• iPhone app

• 70000 products
• Health, enviornmental, social
• Text message
   – UPC, Product name, type




                                  117
USC Cinematic Arts:
Million story building
BarCode Stories (UCLA)




                         119
Barcode phone access (UCLA)
EKG Ball games




                 121
Mattel MindFlex 09




                     122
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
124
Sensors everywhere
Joy Mountford at BayCHI: Visualizations of Our Collective Lives
User confusion
• How do I know what is being sensed?
• How do I know what I can use?
• How do I know what I am ‘in’ or ‘part of?’
• How do I stop being part of it? sometimes?
• Privacy crucial
• Cloak/veils to hide
Cloaks or veils?
 Privacy

 Partially
‘available’
We are all in the Design
• Interfaces are transparent and everywhere in the
  physical world

• We are our own curators and reporters
• Data is pervasive, but difficult to know how best to
  enhance understanding

• Issue: how do I know what I am part of, or not part
  of, and then stop being part of it?
Reality? = Vegas




                   130

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