Information Visualization for Knowledge Discovery

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

data

INFORMATION VISUALIZATION INFO. VIS. Data visualization visualization

A picture is worth a thousand words.


Data picture!

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]


Visual representation

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

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



#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

map of napoleon’s march minard, 1812

•  geography •  time •  temperature

•  course •  direction •  quantity of troops

London Cholera

Outbreak john Snow, 1854

London Cholera

Outbreak john Snow, 1854

crayons

toys

boys girls



User interactions +

click, drag, zoom, select, change color, etc.!!


=Mantra=

Overview first Zoom and filter

Details on demand

Map of the market Stock market

Stock A

size = market cap

Stock B

color = price change

size = market cap

Stock A Stock B

Map of the Market

Market!falls!steeply!Feb!27,!2007,!!with!one!excep:on!

Market falls 311 points July 26, 2007, with a few exceptions

Market falls 311 points July 26, 2007, with a few exceptions

Market mixed, October 22, 2007

http://www.smartmoney.com/map-of-the-market/

http://www.smartmoney.com/map-of-the-market/

http://newsmap.jp/

newsmap

http://www.derlien.com/

Disk inventory x

relationships Social network

http://www.cs.umd.edu/hcil/socialaction

Person A Person B

Has a relationship

Person A Person B

Strong relationship

Person A Person B

Strong relationship

Person A Person B

Person A Person B

Video demo SocialAction

h;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!How people are connected on facebook by country

h;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!How people are connected on facebook by country

Geographic New york taxi

h;p://www.ny:mes.com/interac:ve/2010/04/02/nyregion/taxiKmap.html!

Interactive charts Baby name voyager

http://www.babynamewizard.com/voyager

temporal Data time time time

LIFE event!

event!event!

event!event!

event!event!event!

event!

event!

event!

event!

event!

event! event!event!

( 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!

LIFE event!

event!event!

event!event!

event!event!event!

event!

event!

event!

event!

event!

event! event!event!

“Event Sequence”

( 7:00 am, Wake up ) ( 7:10 am, Shower ) ( 7:30 am, Breakfast )

Electronic health records

( 8:50 am, ER) ( 9:15 am, ICU ) ( 8:40 am, Arrival )

Electronic health records

Event Sequences

and more…

Medical Transportation

Education

Web logs

Sports

Logistics

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

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

What happened to the patients?

Arrival

ICU

?

? ?

Video demo Creating LifeFlow

LifeFlow

Video demo Data Analysis with LifeFlow



User interactions +

click, drag, zoom, select, change color, etc.!!


Data types classified by

1D: Linear

2D: Map

3D: Molecules, Biology Multi dimensional (4+ D)

Temporal

Tree

Network


DATA ANALYSIS PRESENTATION Detect pattern, trend, outliers! Communicate!

Benefits of

DATA ANALYSIS

presentation

presentation

Drawbacks: misleading

Drawbacks: misleading (2)


Visual representation User interactions +

DATA ANALYSIS Detect pattern, trend, outliers!

PRESENTATION Communicate!

@kristwongz Krist wongsuphasawat

DATA

[email protected] http://kristw.yellowpigz.com

http://services.alphaworks.ibm.com/manyeyes/app

Many eyes


Visual representation User interactions +

DATA ANALYSIS Detect pattern, trend, outliers!

PRESENTATION Communicate!

@kristwongz Krist wongsuphasawat

DATA

[email protected] http://kristw.yellowpigz.com

Technology

Information Visualization for Knowledge Discovery