information visualization for knowledge discovery
DESCRIPTION
Talk at Chulalongkorn Business School (CBS), Bangkok, Thailand Sep 18, 2012TRANSCRIPT
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INFORMATION VISUALIZATION
@kristwongz
For knowledge discovery
Krist wongsuphasawat
Computer Engineering, Chulalongkorn University (Intania87, CP30) Dept. of Computer Science & Human-Computer Interaction Lab, Univ. of Maryland Data Visualization Scientist, Twitter
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data
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INFORMATION VISUALIZATION INFO. VIS. Data visualization visualization
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A picture is worth a thousand words.
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INFORMATION VISUALIZATION
Data picture!
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INFORMATION VISUALIZATION INFO. VIS.
Using visual representations and interaction techniques, which take advantage of the human eye’s broad bandwidth pathway into the mind, to allow users to see, explore, and understand large amounts of information at once.”
“ [Wikipedia]
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INFORMATION VISUALIZATION
Visual representation
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X Y
10.0 8.04
8.0 6.95
13.0 7.58
9.0 8.81
11.0 8.33
14.0 9.96
6.0 7.24
4.0 4.26
12.0 10.84
7.0 4.82
5.0 5.68
X Y
10.0 9.14
8.0 8.14
13.0 8.74
9.0 8.77
11.0 9.26
14.0 8.10
6.0 6.13
4.0 3.10
12.0 9.13
7.0 7.26
5.0 4.74
X Y
10.0 7.46
8.0 6.77
13.0 12.74
9.0 7.11
11.0 7.81
14.0 8.84
6.0 6.08
4.0 5.39
12.0 8.15
7.0 6.42
5.0 5.73
X Y
8.0 6.58
8.0 5.76
8.0 7.71
8.0 8.84
8.0 8.47
8.0 7.04
8.0 5.25
19.0 12.50
8.0 5.56
8.0 7.91
8.0 6.89
#1 #2 #3 #4
Anscombe�s quartet
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Property Value
Mean of X 11.0
Variance of X 10.0
Mean of Y 7.5
Variance of Y 3.75
Correlation between X and Y 0.816
Linear regression y = 3.0 +0.5x
#1 #2 #3 #4
Identical statistics
Anscombe�s quartet
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Anscombe�s quartet
#1 #2 #3 #4
0!
2!
4!
6!
8!
10!
12!
0! 5! 10! 15!0!1!2!3!4!5!6!7!8!9!
10!
0! 5! 10! 15!0!
2!
4!
6!
8!
10!
12!
14!
0! 5! 10! 15!0!
2!
4!
6!
8!
10!
12!
14!
0! 10! 20!
But very different
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map of napoleon’s march minard, 1812
• geography • time • temperature
• course • direction • quantity of troops
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London Cholera
Outbreak john Snow, 1854
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London Cholera
Outbreak john Snow, 1854
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crayons
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toys
boys girls
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INFORMATION VISUALIZATION
Visual representation
User interactions +
click, drag, zoom, select, change color, etc.!!
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INFORMATION VISUALIZATION
=Mantra=
Overview first Zoom and filter
Details on demand
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Map of the market Stock market
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Stock A
size = market cap
Stock B
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color = price change
size = market cap
Stock A Stock B
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Map of the Market
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Market!falls!steeply!Feb!27,!2007,!!with!one!excep:on!
Market falls 311 points July 26, 2007, with a few exceptions
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Market falls 311 points July 26, 2007, with a few exceptions
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Market mixed, October 22, 2007
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http://www.smartmoney.com/map-of-the-market/
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http://www.smartmoney.com/map-of-the-market/
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http://newsmap.jp/
newsmap
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http://www.derlien.com/
Disk inventory x
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relationships Social network
http://www.cs.umd.edu/hcil/socialaction
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Person A Person B
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Has a relationship
Person A Person B
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Strong relationship
Person A Person B
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Strong relationship
Person A Person B
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Person A Person B
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Video demo SocialAction
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h;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!How people are connected on facebook by country
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h;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!How people are connected on facebook by country
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Geographic New york taxi
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h;p://www.ny:mes.com/interac:ve/2010/04/02/nyregion/taxiKmap.html!
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Interactive charts Baby name voyager
http://www.babynamewizard.com/voyager
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temporal Data time time time
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LIFE event!
event!event!
event!event!
event!event!event!
event!
event!
event!
event!
event!
event! event!event!
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( 7:00 am, Wake up )
LIFE event!
event!event!
event!event!
event!event!event!
event!
event!
event!
event!
event!
event! event!event!
Time Event type!
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LIFE event!
event!event!
event!event!
event!event!event!
event!
event!
event!
event!
event!
event! event!event!
“Event Sequence”
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( 7:00 am, Wake up ) ( 7:10 am, Shower ) ( 7:30 am, Breakfast )
Electronic health records
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( 8:50 am, ER) ( 9:15 am, ICU ) ( 8:40 am, Arrival )
Electronic health records
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Event Sequences
and more…
Medical Transportation
Education
Web logs
Sports
Logistics
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ARRIVAL Arrive the hospital
EMERGENCY Emergency room
ICU Intensive Care Unit
FLOOR Normal room
EXIT-ALIVE Leave the hospital alive
EXIT-DEAD Leave the hospital dead
Patient transfers
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Save more lives!
Emergency Department Pa:ent!ID:!45851733 !!
12/02/2008!14:26 !Arrival!12/02/2008!14:26 !Emergency!12/02/2008!22:44 !ICU!12/05/2008!05:07 !Floor!12/08/2008!10:02 !Floor!12/14/2008!06:19 !Discharge!!
Pa:ent!ID:!45851732 !!12/02/2008!14:26 !Arrival!12/02/2008!14:26 !Emergency!12/02/2008!22:44 !ICU!12/05/2008!05:07 !Floor!12/08/2008!10:02 !Floor!12/14/2008!06:19 !Discharge!!
Pa:ent!ID:!45851731 !!12/02/2008!14:26 !Arrival!12/02/2008!14:26 !Emergency!12/02/2008!22:44 !ICU!12/05/2008!05:07 !Floor!12/08/2008!10:02 !Floor!12/14/2008!06:19 !Discharge!!
6,000+ patients per month
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What happened to the patients?
Arrival
ICU
?
? ?
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Video demo Creating LifeFlow
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LifeFlow
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Video demo Data Analysis with LifeFlow
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INFORMATION VISUALIZATION
Visual representation
User interactions +
click, drag, zoom, select, change color, etc.!!
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INFORMATION VISUALIZATION
Data types classified by
1D: Linear
2D: Map
3D: Molecules, Biology Multi dimensional (4+ D)
Temporal
Tree
Network
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INFORMATION VISUALIZATION
DATA ANALYSIS PRESENTATION Detect pattern, trend, outliers! Communicate!
Benefits of
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DATA ANALYSIS
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presentation
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presentation
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Drawbacks: misleading
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Drawbacks: misleading (2)
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INFORMATION VISUALIZATION
Visual representation User interactions +
DATA ANALYSIS Detect pattern, trend, outliers!
PRESENTATION Communicate!
@kristwongz Krist wongsuphasawat
DATA
[email protected] http://kristw.yellowpigz.com
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http://services.alphaworks.ibm.com/manyeyes/app
Many eyes
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INFORMATION VISUALIZATION
Visual representation User interactions +
DATA ANALYSIS Detect pattern, trend, outliers!
PRESENTATION Communicate!
@kristwongz Krist wongsuphasawat
DATA
[email protected] http://kristw.yellowpigz.com