Joy Mountford at BayCHI: Visualizations of Our Collective Lives

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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!)

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Apple: QuickTime controller (1988)Designing Interaction Bill Modridge (06)

Lego Music Composer ’03

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LinkMark 00

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Yahoo front page 2005

Personal Information Manager 2006

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Y! personal information manager

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Y local offers relevant information

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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)

Raw DataData

StreamsVisualStyle

Presentation form

Data Numbers/Freq Visual Format

User Task

DataTransformations

VisualEncodings

ViewTransformations

Accuracy of visual techniquesPosition

Slope

Area

Angle

Volume

Colour

Moore’s Law ‘65

Schneiner 1626: 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

1880 1965 2000

Flouride starts around here?

Dentistry

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%

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

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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

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

Ray McClure

S. Joy Mountford

http://farm1.static.flickr.com/174/413236455_c9404407a3_o.jpg

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)

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

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

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

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)

Draw sheep facing left for .02 cents40 days for 10000 sheep (Koblin)

10,000 sheep on poster

10,000 Cents (Koblin)created unique $100 bills

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

Text

eCloud San Jose airport (Koblin)

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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

Moeller San Jose airport ’10:pins on sheets over parking lot

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Fire Fly Dress (Orth)

Music Perfume bottles (MIT ‘01)

NYU: moving brooch

NYU worn printer

CCA: Light sensors cooked into lollipops

Text

CCA: Real grass moves video: grown in sensor filaments

Bar scene

IR light color changing Coke bottles

• Good Guide (mobile)• iPhone app

• 70000 products• Health, enviornmental, social• Text message

–UPC, Product name, type

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USC Cinematic Arts: Million story building

BarCode Stories (UCLA)

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Barcode phone access (UCLA)

EKG Ball games

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Mattel MindFlex 09

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Sensors everywhere

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

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