0
Information visualization lecture 3

representation
Katrien Verbert
Department of Computer Science
Faculty of Science
Vrij...
Anscombe's quartet

Property	
  

Value	
  	
  

Mean	
  of	
  x	
  	
  

9	
  	
  

Variance	
  of	
  x	
  	
  

11	
  	
...
Ben	
  Shneiderman	
  	
  
hIp://www.youtube.com/watch?v=og7bzN0DhpI	
  
(watch	
  12:20	
  –	
  15:49	
  )	
  
06/03/14

...
Anscombe's quartet

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pag. 4
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Relations

30

MPG

Price £k

10 - 12

35

12 14
12 -- 14

40

16 - 18

Part of this car purchase interface identifies a r...
Relations

Interaction to identify a doctor highlights the hospital beds under his or her
care, and vice versa: an example...
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
A single number

The	
  original	
  aircraX	
  al8meter,	
  responsible	
  for	
  many	
  accidents	
  
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pag. 9
Representation of the view of an altimeter

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pag. 10
An altimeter representation easily assumed to be
the same as shown on the previous slide

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pag. 11
Change blindness

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Change blindness

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Change blindness

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pag. 14
A modern aircraft altimeter

2200

2000

1820
00
1600
1400

stop
1200

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pag. 15
Single number: second example

Source:	
  Image	
  by	
  kind	
  permission	
  of	
  Marcus	
  Watson	
  

06/03/14

pag. ...
A collection of numbers

Each	
  dot	
  represents	
  the	
  price	
  of	
  a	
  car	
  

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pag. 17
Box plot
60

50
Price
(£K)
40

30

20

10

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pag. 18
Box plot

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pag. 19
histogram
8

6

4

2

1 –20

20–30

30–40

40–50

50–60

Price (£K)
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pag. 20
bargram

Price £k

10 - 12

12 - 14

16 - 18

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pag. 21
Bargram of categorical data

Nissan

Ford

Ferrari

MG

Cadillac

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pag. 22
histogram of ordinal data

£200k	
  

£100k	
  

Monday	
  

Tuesday	
  

Wednesday	
   Thursday	
  

Friday	
  
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...
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Anscombe's quartet

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pag. 25
Scatterplot

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pag. 26
Time series

	
  
	
  
Android	
  Ac8va8ons	
  per	
  day,	
  measured	
  on	
  the	
  first	
  of	
  each	
  month	
  
06/...
Time series

	
  
	
  
Android	
  Ac8va8ons	
  per	
  day,	
  measured	
  on	
  the	
  first	
  of	
  each	
  month	
  
06/...
Stock data

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pag. 29
time series

(a)	
  

(b)	
  

(c)	
  

(d)	
  

Four	
  views	
  of	
  a	
  8me-­‐series	
  query	
  tool.	
  (a)	
  An	
...
Overview of the entire data set

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pag. 31
time-box limits the display to items with prices
between $70 an $250 during days 1 to 4

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pag. 32
additional constraint selects items with prices
between $70 and $95 during days 7 to 12

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pag. 33
yet another constraint concerns prices
between $90 and $115 for days 15 to 18

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pag. 34
Student activity meter

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pag. 35
Time series

Representa8on	
  of	
  the	
  level	
  
of	
  ozone	
  concentra8on	
  
above	
  Los	
  Angeles	
  over	
  a	...
Linked histogram

(a)

(b)

the price and
number of
bedrooms
associated with a
collection of houses
are represented by
sep...
Linked histogram

upper and lower
limits placed on
Price define a subset
of houses which are
coded red on both
histograms
...
Linked histogram

Interpretation is
enhanced by
‘ranging down’ the
colour-coded
houses, especially if
exploration involves...
Semantic zoom reveals data about a
second attribute
	
  

60

	
  
	
  

	
  

50

Price
	
  (£K)

40	
  
	
  

Ford	
  
N...
Qualitative understanding of data

A	
  representa8on	
  of	
  Australia	
  and	
  New	
  Zealand	
  on	
  a	
  conven8ona...
Qualitative understanding of data

Australia

New
Zealand
A	
  representa8on	
  of	
  Australia	
  and	
  New	
  Zealand	
...
In	
  the	
  State	
  of	
  the	
  World	
  Atlas,	
  magnifica8on	
  encoding	
  is	
  used	
  to	
  give	
  a	
  first	
  ...
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Does house A cost more than C?

D

Price

C
B

Bedrooms

A

Time

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pag. 45
Scatterplot matrix

Bedrooms

D

A
B

Interac8on	
  can	
  offer	
  solu8on	
  
	
  
A	
  projec8on	
  of	
  the	
  data,	
...
Scatterplot matrix

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pag. 47
Cognitive overload? Interaction solution

The	
  highligh8ng	
  of	
  
houses	
  in	
  one	
  plane	
  is	
  
brushed	
  i...
Trivariate data
July ʻ97

Sept ʻ97

Nov ʻ97

Month
Jan ʻ98
of
Production
(MOP)
Mar ʻ98
May ʻ98

2

4
6
8
10
Months in serv...
Trivariate data
Treble

Bass
	
  
Circles	
  indicate	
  the	
  extent	
  of	
  the	
  effect	
  of	
  a	
  component	
  on...
Maps to represent trivariate data

A	
  representa8on	
  of	
  the	
  popula8on	
  of	
  major	
  ci8es	
  in	
  England,	...
Also non-static representations of data

1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000

Circles	
  change	
  in	
...
hIp://www.youtube.com/watch?v=hVimVzgtD6w	
  
	
  
06/03/14

pag. 53
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Simple scatterplot of bivariate data

Number
of
bedrooms

A
B
Price

	
  

A	
  simple	
  scaIerplot	
  represen8ng	
  the...
Price

Number
of
bedrooms

An	
  alterna8ve	
  representa8on	
  to	
  the	
  scaIerplot	
  in	
  which	
  the	
  two	
  aI...
Labels

B
A
Price

Number
of
bedrooms

To	
  avoid	
  ambiguity	
  the	
  pair	
  of	
  points	
  represen8ng	
  a	
  hous...
Parallel coordinates

A

B

C

D

E

F

G

A	
  parallel	
  coordinate	
  plot	
  for	
  six	
  objects,	
  each	
  charac...
Parallel coordinates

A	
  parallel	
  coordinate	
  plot	
  representa8on	
  of	
  a	
  collec8on	
  of	
  cars,	
  in	
 ...
Student activity meter

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pag. 60
Star plot
Mathematics
Sport

Chemistry

Physics

Literature

History
Art
Geography

06/03/14

pag. 61
Star plot for comparison

Bob’s	
  performance	
  

Tony’s	
  performance	
  
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pag. 62
A	
  scaIerplot	
  enhanced	
  by	
  addi8onal	
  and	
  selec8ve	
  encoding,	
  allowing	
  the	
  selec8on	
  of	
  a	
...
The	
  automa8c	
  display	
  of	
  addi8onal	
  detail	
  following	
  the	
  selec8on	
  of	
  narrower	
  limits	
  on	...
Histogram

	
  
	
  
A	
  histogram	
  represen8ng	
  the	
  prices	
  of	
  a	
  collec8on	
  of	
  houses.	
  The	
  con...
Limits on Price identify a subset of
houses, coded green

06/03/14

pag. 66
Linked histograms

Houses	
  defined	
  by	
  the	
  limits	
  on	
  Price	
  are	
  coded	
  green	
  in	
  other	
  aIrib...
Linked histograms

	
  Green	
  coding	
  applies	
  only	
  to	
  houses	
  which	
  sa8sfy	
  all	
  aIribute	
  limits....
Linked histograms

Even	
  if	
  no	
  houses	
  sa8sfy	
  all	
  aIribute	
  limits,	
  black	
  houses,	
  which	
  fail...
Linked histograms

	
  
An	
  AIribute	
  Explorer	
  representa8on	
  of	
  three	
  dimensions	
  of	
  communica8on	
  ...
Linked histogram

Details	
  in	
  lecture	
  6:	
  case	
  studies	
  

06/03/14

pag. 71
Details of the Titanic disaster

Class
Survived

No
Yes
No
Yes
No
Yes
No
Yes

Age

Gender

Adult

Male

Child
Adult
Child
...
Steps	
  to	
  create	
  
mosaic	
  plot	
  
325 285

706

885

First Second

2201

Third

Crew

(a)

(b)

Survived

Femal...
Mosaic plot

06/03/14

pag. 74
Friendly’s webslte

hIp://www.datavis.ca/gallery/	
  
	
  
pag. 75
06/03/14
Icons

Chernoff	
  Faces	
  allow	
  aIribute	
  values	
  to	
  be	
  encoded	
  in	
  the	
  features	
  of	
  cartoon	
 ...
Michael	
  Porath	
  
Example
Some criticism

No evidence for pre-attentive nature
[Morris et al. 1999]

Src:	
  hIp://joshualedwell.typepad.com/usabili...
Multidimensional icons representing eight
attributes of a dwelling

house
£400,000
garage
central heating
four bedrooms
go...
Object visibility: each object is represented
as a single and coherent visual entity

Representa8ons	
  suppor8ve	
  
of	
...
Infocanvas

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pag. 83
Representa8ons	
  of	
  mul8-­‐aIribute	
  objects	
  suppor8ve	
  of	
  aIribute	
  visibility	
  06/03/14

pag. 84
Attribute correlation

06/03/14

pag. 85
Object correlation

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pag. 86
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Relation

Relation (n): a logical or natural association between two or
more things; relevance of one to another; connecti...
A simple symbol indicates the relationship
of marriage

John
Smith

Mary
Robinson

06/03/14

pag. 89
Social networks

06/03/14

pag. 90
Lines indicate relationship

John

Stingy Bank

1930 Bentley

06/03/14

pag. 91
Arrows indicate unique unilateral
functional relations

X1
Y

X2
X3
y=f(x)	
  	
  

06/03/14

pag. 92
Colour indicates a relation

06/03/14

pag. 93
Picts
Northumbria
Mercia
West Saxon
South Saxon
Isle of Wight
Kent
Britons

550

600

650

700

Years AD

The	
  incidence...
Lines
B

Originator

Receiver

A
C
I
B
F
G
I
B
K
G
K
C
D

H
L
M
E
H
I
B
M
B
B
E
J
C

B

A

K

M

E

G

C

I

D

L

E

K

F...
Useful?	
  

(b)	
  

(a)	
  
A	
  representa8on	
  of	
  mortgage	
  ac8vity:	
  (a)	
  
lenders,	
  proper8es	
  (houses...
A	
  threshold	
  has	
  been	
  
imposed	
  to	
  suppress	
  the	
  
display	
  of	
  normal	
  behaviour.	
  
As	
  a	
...
hIp://seekshreyas.com/beerviz/	
  
	
  
06/03/14

pag. 98
hIp://visualiza8on.geblogs.com/visualiza8on/network/	
  
	
  
06/03/14

pag. 99
Chord diagram

06/03/14

pag. 100
06/03/14

pag. 101
An ‘association’ style chart depicting the African
bombings

06/03/14

pag. 102
Part of a ‘timeline’ style chart depicting the
Kennedy assassination

	
  Source:	
  Courtesy	
  i2	
  Ltd.	
  
06/03/14

...
Sankey diagram

hIp://bost.ocks.org/mike/sankey/	
  
	
  
06/03/14

pag. 104
Remember this one?

06/03/14

pag. 105
Flow map diagram

Migration from Colorado, migration from Norway and Latvia, whisky exports from Scotland.

	
  
Verbeek,	...
Most familiar use of lines?

Harry	
  Beck’s	
  original	
  London	
  Underground	
  map	
  
Source:	
  ©	
  Transport	
  ...
The Underground map in use prior to the
introduction of Harry Beck’s map

Differences?	
  
Easier	
  to	
  use?	
  

Source...
Journey time?

06/03/14

pag. 109
hIp://www.london-­‐tubemap.com/journey_8mes.php	
  
	
  
06/03/14

pag. 110
hIp://www.tom-­‐carden.co.uk/p5/tube_map_travel_8mes/applet/	
  
	
  
06/03/14

pag. 111
Social networks

	
  
The	
  social	
  choices	
  of	
  fourth	
  grade	
  students	
  (aXer	
  Moreno,	
  1934)	
  
	
  
...
(a)	
  Social	
  choices	
  among	
  department	
  store	
  employees	
  (b)	
  Social	
  choices	
  among	
  department	
...
Overview
•  Encoding of value
–  Univariate data
–  Bivariate data
–  Trivariate data
–  Hypervariate data
•  Encoding of ...
Maps and diagrams
Swimming
Pool

Hotels

Golf
Course

Restaurant

A
B
C
D
E
F
G
Facili8es	
  offered	
  by	
  eight	
  hote...
Venn diagram

Swimming
pool

B

D

Golf

F
A

C

E
G
Restaurant

06/03/14

pag. 116
A Venn diagram representation of the
attributes of 24 hotels

Swimming
pool

Figure	
  3.83	
  

Golf

Restaurant
06/03/14...
InfoCrystal

Price

*
Number of
bedrooms

Garden
size

The	
  development	
  leading	
  from	
  a	
  Venn	
  diagram	
  to...
An Infocrystal representation of the
hotel data
Swimming
Pool

Golf

5

2
0

4

4
1

8
Restaurant
06/03/14

pag. 119
Cluster map

06/03/14

pag. 120
Cluster map

A	
  cluster	
  map	
  representa8on	
  of	
  	
  24	
  hotels,	
  each	
  described	
  by	
  four	
  aIribut...
TalkExplorer

Details	
  in	
  lecture	
  6:	
  case	
  studies	
  

06/03/14

pag. 122
Tree representations
designated root node
parent of A

sibling of A

A
leaf nodes
child of A

leaf nodes
06/03/14

pag. 12...
Tree visualizations
hIp://www.informa8k.uni-­‐koeln.de/
ls_juenger/research/vbctool/	
  

	
  

Problems?	
  
06/03/14

pa...
Alternative: cone trees

(a)
(b)

(a)	
  A	
  tree	
  	
  (b)	
  The	
  corresponding	
  cone	
  tree	
  

06/03/14

pag. ...
Cam tree:
horizontal orientation of cone tree

06/03/14

pag. 126
Construction of a Tree Map
The	
  Tree	
  

Forma8on	
  of	
  the	
  
Tree	
  Map	
  
The	
  Tree	
  Map	
  

06/03/14

pa...
Slide and dice construction

Tree

Tree Map

The	
  ‘slice-­‐and-­‐dice’	
  construc8on	
  of	
  a	
  Tree	
  Map	
  to	
 ...
Tree map display of an author’s collection
of reports

Source:	
  Courtesy	
  of	
  Ben	
  Shneiderman	
  

06/03/14

pag....
Map of the market

hIp://www.marketwatch.com/tools/stockresearch/marketmap	
  
	
  

06/03/14

pag. 130
hIp://www.hivegroup.com/solu8ons/demos/usda.html	
  
	
  
06/03/14

pag. 131
hIp://www.ny8mes.com/interac8ve/2008/05/03/business/20080403_SPENDING_GRAPHIC.html?_r=0	
  
Ben Sheiderman on tree maps

	
  
	
  
hIp://www.youtube.com/watch?v=og7bzN0DhpI	
  

06/03/14

pag. 133
Tree map
pros and cons
Pros?

Cons?

06/03/14

pag. 134
Tree map
pros and cons
Pros

Cons

Color + Area
(2 attributes)

Hierarchy/Structure
hard to convey
aspect ratios

Slide	
 ...
Aspect ratios

Which	
  one	
  is	
  bigger?	
  

Slide	
  adapted	
  from	
  Michael	
  Porath	
  	
  

06/03/14

pag. 13...
Aspect ratios

Which	
  one	
  is	
  bigger?	
  

Slide	
  adapted	
  from	
  Michael	
  Porath	
  	
  

06/03/14

pag. 13...
Aspect ratios

Which	
  one	
  is	
  bigger?	
  

make	
  the	
  segments	
  more	
  square!	
  
	
  
Slide	
  adapted	
  ...
Layout Strategies / Algorithms

Cluster	
  

Squarified	
  

Pivot	
  By	
  Middle	
  

StripTreemap	
  

Pivot	
  By	
  Si...
Sunburst

hIp://bl.ocks.org/mbostock/4063423	
  
06/03/14
	
  

pag. 140
 

hIp://www.theguardian.com/news/datablog/2012/oct/05/beatles-­‐charts-­‐infographics	
  
hIp://hci.stanford.edu/jheer/files/zoo/	
  
	
  
06/03/14

pag. 142
Hyperbolic tree

	
  
A	
  sketch	
  illustra8on	
  of	
  the	
  hyperbolic	
  browser	
  representa8on	
  of	
  a	
  tree...
Nodes can typically be moved into center
position

	
  
(a)  The	
  repor8ng	
  structure	
  of	
  the	
  employees	
  of	...
Representa8on	
  of	
  the	
  Library	
  of	
  Congress	
  by	
  the	
  hyperbolic	
  browser	
  
hIp://philogb.github.io/jit/sta8c/v20/Jit/
Examples/Hypertree/example1.html	
  
	
  
hIp://www.autodeskresearch.com/projects/orgorgchart	
  
	
  
Readings
Chapter 3

06/03/14

pag. 148
Questions?

06/03/14

pag. 149
References
•  Christopher J. Morris, David S. Ebert, Penny Rheingans,
An Experimental Analysis of the Pre-Attentiveness of...
project

06/03/14

pag. 151
Team project milestones
1. 
2. 
3. 
4. 
5. 

due	
  27	
  Feb.	
  
Form teams
due	
  13	
  March	
  
Project proposal
due	...
Project proposal
1 page description of your intended project:

–  mo8va8on	
  
–  which	
  datasets	
  you	
  will	
  use	...
Data collection
•  https://docs.google.com/forms/d/
1gHwVWHZLzWdSz1F37jA1Gungrl56bT215M6FYW3YqGY/
viewform
Or
•  bit.ly/N6...
Information visualization: representation
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Transcript of "Information visualization: representation"

  1. 1. Information visualization lecture 3 representation Katrien Verbert Department of Computer Science Faculty of Science Vrije Universiteit Brussel katrien.verbert@vub.ac.be 06/03/14 pag. 1
  2. 2. Anscombe's quartet Property   Value     Mean  of  x     9     Variance  of  x     11     Mean  of  y     7.50     Variance  of  y     4.122  or  4.127   Correla8on  between   x  and  y   0.816   Linear  regression  line   y  =  3.00  +  0.500x   for  each  data  set     06/03/14 pag. 2
  3. 3. Ben  Shneiderman     hIp://www.youtube.com/watch?v=og7bzN0DhpI   (watch  12:20  –  15:49  )   06/03/14 pag. 3
  4. 4. Anscombe's quartet 06/03/14 pag. 4
  5. 5. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 5
  6. 6. Relations 30 MPG Price £k 10 - 12 35 12 14 12 -- 14 40 16 - 18 Part of this car purchase interface identifies a relation 06/03/14 pag. 6
  7. 7. Relations Interaction to identify a doctor highlights the hospital beds under his or her care, and vice versa: an example of brushing     06/03/14 pag. 7
  8. 8. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 8
  9. 9. A single number The  original  aircraX  al8meter,  responsible  for  many  accidents   06/03/14 pag. 9
  10. 10. Representation of the view of an altimeter 06/03/14 pag. 10
  11. 11. An altimeter representation easily assumed to be the same as shown on the previous slide 06/03/14 pag. 11
  12. 12. Change blindness 06/03/14 pag. 12
  13. 13. Change blindness 06/03/14 pag. 13
  14. 14. Change blindness 06/03/14 pag. 14
  15. 15. A modern aircraft altimeter 2200 2000 1820 00 1600 1400 stop 1200 06/03/14 pag. 15
  16. 16. Single number: second example Source:  Image  by  kind  permission  of  Marcus  Watson   06/03/14 pag. 16
  17. 17. A collection of numbers Each  dot  represents  the  price  of  a  car   06/03/14 pag. 17
  18. 18. Box plot 60 50 Price (£K) 40 30 20 10 06/03/14 pag. 18
  19. 19. Box plot 06/03/14 pag. 19
  20. 20. histogram 8 6 4 2 1 –20 20–30 30–40 40–50 50–60 Price (£K) 06/03/14 pag. 20
  21. 21. bargram Price £k 10 - 12 12 - 14 16 - 18 06/03/14 pag. 21
  22. 22. Bargram of categorical data Nissan Ford Ferrari MG Cadillac 06/03/14 pag. 22
  23. 23. histogram of ordinal data £200k   £100k   Monday   Tuesday   Wednesday   Thursday   Friday   06/03/14 pag. 23
  24. 24. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 24
  25. 25. Anscombe's quartet 06/03/14 pag. 25
  26. 26. Scatterplot 06/03/14 pag. 26
  27. 27. Time series     Android  Ac8va8ons  per  day,  measured  on  the  first  of  each  month   06/03/14   pag. 27
  28. 28. Time series     Android  Ac8va8ons  per  day,  measured  on  the  first  of  each  month   06/03/14   pag. 28
  29. 29. Stock data 06/03/14 pag. 29
  30. 30. time series (a)   (b)   (c)   (d)   Four  views  of  a  8me-­‐series  query  tool.  (a)  An  overview  of  the  en8re  data  set;  (b)  a  single  8me-­‐ box  limits  the  display  to  items  with  prices  between  $70  an  $250  during  days  1  to  4;  (c)  an   addi8onal  constraint  selects  items  with  prices  between  $70  and  $95  during  days  7  to  12;  (d)  yet   another  constraint  concerns  prices  between  $90  and  $115  for  days  15  to  18   pag. 30 Source:  Courtesy  of  Harry  Hochheiser   06/03/14
  31. 31. Overview of the entire data set 06/03/14 pag. 31
  32. 32. time-box limits the display to items with prices between $70 an $250 during days 1 to 4 06/03/14 pag. 32
  33. 33. additional constraint selects items with prices between $70 and $95 during days 7 to 12 06/03/14 pag. 33
  34. 34. yet another constraint concerns prices between $90 and $115 for days 15 to 18 06/03/14 pag. 34
  35. 35. Student activity meter 06/03/14 pag. 35
  36. 36. Time series Representa8on  of  the  level   of  ozone  concentra8on   above  Los  Angeles  over  a   period  of  ten  years   06/03/14 pag. 36
  37. 37. Linked histogram (a) (b) the price and number of bedrooms associated with a collection of houses are represented by separate histograms a single house is represented once on each histogram; 06/03/14 pag. 37
  38. 38. Linked histogram upper and lower limits placed on Price define a subset of houses which are coded red on both histograms 06/03/14 pag. 38
  39. 39. Linked histogram Interpretation is enhanced by ‘ranging down’ the colour-coded houses, especially if exploration involves the dynamic alteration of limits 06/03/14 pag. 39
  40. 40. Semantic zoom reveals data about a second attribute   60       50 Price  (£K) 40     Ford   Nissan   VW   40 35     Merc   Jag   Jag   30 3  0   Ford   SEAT     20   10 06/03/14 pag. 40
  41. 41. Qualitative understanding of data A  representa8on  of  Australia  and  New  Zealand  on  a  conven8onal  map   06/03/14 pag. 41
  42. 42. Qualitative understanding of data Australia New Zealand A  representa8on  of  Australia  and  New  Zealand  indica8ng  that  some  aIribute  of  New   pag. 42 Zealand  is  ten  8mes  its  value  for  Australia   06/03/14
  43. 43. In  the  State  of  the  World  Atlas,  magnifica8on  encoding  is  used  to  give  a  first  impression  of   popula8on  densi8es.  Note  the  reduced  ‘size’  of  Canada  and  Australia  when  compared  with  a   conven8onal  map  Source:  Smith  (1999)  
  44. 44. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 44
  45. 45. Does house A cost more than C? D Price C B Bedrooms A Time 06/03/14 pag. 45
  46. 46. Scatterplot matrix Bedrooms D A B Interac8on  can  offer  solu8on     A  projec8on  of  the  data,   allowing  comparison  of  Price   and  Bedrooms  values   C Price 06/03/14 pag. 46
  47. 47. Scatterplot matrix 06/03/14 pag. 47
  48. 48. Cognitive overload? Interaction solution The  highligh8ng  of   houses  in  one  plane  is   brushed  into  the   remaining  planes   06/03/14 pag. 48
  49. 49. Trivariate data July ʻ97 Sept ʻ97 Nov ʻ97 Month Jan ʻ98 of Production (MOP) Mar ʻ98 May ʻ98 2 4 6 8 10 Months in service (MIS) 12 A  representa8on  of  reported  product  failure,  based  on  month  of  produc8on  (MOP)  of  the  failed   product,  and  total  months  in  service  (MIS)  before  the  fault  occurred.  The  radius  of  each  circle   pag. 49 06/03/14 indicates  the  number  of  faults  reported  for  a  given  MOP  and  MIS  
  50. 50. Trivariate data Treble Bass   Circles  indicate  the  extent  of  the  effect  of  a  component  on  some  property  of  the  circuit,  and   change  in  size  as  the  frequency  cycles  up  and  down  the  range  from  bass  to  treble  06/03/14 pag. 50
  51. 51. Maps to represent trivariate data A  representa8on  of  the  popula8on  of  major  ci8es  in  England,  Wales  and  Scotland.  Circle  area  is   propor8onal  to  popula8on   pag. 51 06/03/14  
  52. 52. Also non-static representations of data 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Circles  change  in  size  as  the  decades   are  animated,  so  that  sudden  changes   in  popula8on  ‘pop  out’     06/03/14 pag. 52
  53. 53. hIp://www.youtube.com/watch?v=hVimVzgtD6w     06/03/14 pag. 53
  54. 54. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 54
  55. 55. Simple scatterplot of bivariate data Number of bedrooms A B Price   A  simple  scaIerplot  represen8ng  the  price  and  number  of  bedrooms  associated  with  two  houses     06/03/14 pag. 55
  56. 56. Price Number of bedrooms An  alterna8ve  representa8on  to  the  scaIerplot  in  which  the  two  aIribute  scales  are  presented   in  parallel,  thereby  requiring  two  points  to  represent  each  house   pag. 56   06/03/14
  57. 57. Labels B A Price Number of bedrooms To  avoid  ambiguity  the  pair  of  points  represen8ng  a  house  are  joined  and  labelled   pag. 57 06/03/14  
  58. 58. Parallel coordinates A B C D E F G A  parallel  coordinate  plot  for  six  objects,  each  characterised  by  seven  aIributes.  The  trade-­‐off   between  A  and  B,  and  the  correla8on  between  B  and  C,  are  immediately  apparent.  The  trade-­‐off   pag. 58 06/03/14 between  B  and  E,  and  the  correla8on  between  C  and  G,  are  not  
  59. 59. Parallel coordinates A  parallel  coordinate  plot  representa8on  of  a  collec8on  of  cars,  in  which  a  range  of  the  aIribute   Year  has  been  selected  to  cause  all  those  cars  manufactured  during  that  period  to  be   highlighted   pag. 59 Source:  Harri  Siirtola   06/03/14
  60. 60. Student activity meter 06/03/14 pag. 60
  61. 61. Star plot Mathematics Sport Chemistry Physics Literature History Art Geography 06/03/14 pag. 61
  62. 62. Star plot for comparison Bob’s  performance   Tony’s  performance   06/03/14 pag. 62
  63. 63. A  scaIerplot  enhanced  by  addi8onal  and  selec8ve  encoding,  allowing  the  selec8on  of  a  film   on  the  basis  of  type,  dura8on,  year  of  produc8on  and  other  aIributes  
  64. 64. The  automa8c  display  of  addi8onal  detail  following  the  selec8on  of  narrower  limits  on   years  of  produc8on  and  film  length  
  65. 65. Histogram     A  histogram  represen8ng  the  prices  of  a  collec8on  of  houses.  The  contribu8on  of  one  house  is   pag. 65 06/03/14 shown  in  yellow  
  66. 66. Limits on Price identify a subset of houses, coded green 06/03/14 pag. 66
  67. 67. Linked histograms Houses  defined  by  the  limits  on  Price  are  coded  green  in  other  aIribute  histograms   06/03/14 pag. 67
  68. 68. Linked histograms  Green  coding  applies  only  to  houses  which  sa8sfy  all  aIribute  limits.    Houses  which  fail   one  limit  are  coded  black,  so  if  a  black  house  is  posi8oned  outside  a  limit  it  will  turn   pag. 68 06/03/14 green  if  the  the  limit  is  extended  to  include  it  
  69. 69. Linked histograms Even  if  no  houses  sa8sfy  all  aIribute  limits,  black  houses,  which  fail  only  one  limit,  provide   pag. 69 06/03/14 guidance  as  to  the  effect  of  relaxing  limits  
  70. 70. Linked histograms   An  AIribute  Explorer  representa8on  of  three  dimensions  of  communica8on  data  captured  during pag. 70 an  emergency  services  exercise,  suppor8ng  interac8ve  explora8on  by  an  analyst   06/03/14
  71. 71. Linked histogram Details  in  lecture  6:  case  studies   06/03/14 pag. 71
  72. 72. Details of the Titanic disaster Class Survived No Yes No Yes No Yes No Yes Age Gender Adult Male Child Adult Child Female 1st 2nd 3rd Crew 118 57 0 5 4 140 0 1 154 14 0 11 13 80 0 13 387 75 35 13 89 76 17 14 670 192 0 0 3 20 0 0 06/03/14 pag. 72
  73. 73. Steps  to  create   mosaic  plot   325 285 706 885 First Second 2201 Third Crew (a) (b) Survived Female Female Died Survived Male Male Died Adult [Friendly,  2000]   Child First Second Third (d) Crew First Second Third (c) Crew
  74. 74. Mosaic plot 06/03/14 pag. 74
  75. 75. Friendly’s webslte hIp://www.datavis.ca/gallery/     pag. 75 06/03/14
  76. 76. Icons Chernoff  Faces  allow  aIribute  values  to  be  encoded  in  the  features  of  cartoon  faces   06/03/14 (Chernoff  1973)   pag. 76
  77. 77. Michael  Porath  
  78. 78. Example
  79. 79. Some criticism No evidence for pre-attentive nature [Morris et al. 1999] Src:  hIp://joshualedwell.typepad.com/usability_blog/files/final_vizualiza8on.pdf     06/03/14 pag. 80
  80. 80. Multidimensional icons representing eight attributes of a dwelling house £400,000 garage central heating four bedrooms good repair large garden Victoria 15 mins flat £300,000 no garage central heating two bedrooms poor repair small garden Victoria 20 mins houseboat £200,000 no garage no central heating three bedrooms good repair no garden Victoria 15 mins 06/03/14 pag. 81
  81. 81. Object visibility: each object is represented as a single and coherent visual entity Representa8ons  suppor8ve   of  object  visibility   06/03/14 pag. 82
  82. 82. Infocanvas 06/03/14 pag. 83
  83. 83. Representa8ons  of  mul8-­‐aIribute  objects  suppor8ve  of  aIribute  visibility  06/03/14 pag. 84
  84. 84. Attribute correlation 06/03/14 pag. 85
  85. 85. Object correlation 06/03/14 pag. 86
  86. 86. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 87
  87. 87. Relation Relation (n): a logical or natural association between two or more things; relevance of one to another; connection. 06/03/14 pag. 88
  88. 88. A simple symbol indicates the relationship of marriage John Smith Mary Robinson 06/03/14 pag. 89
  89. 89. Social networks 06/03/14 pag. 90
  90. 90. Lines indicate relationship John Stingy Bank 1930 Bentley 06/03/14 pag. 91
  91. 91. Arrows indicate unique unilateral functional relations X1 Y X2 X3 y=f(x)     06/03/14 pag. 92
  92. 92. Colour indicates a relation 06/03/14 pag. 93
  93. 93. Picts Northumbria Mercia West Saxon South Saxon Isle of Wight Kent Britons 550 600 650 700 Years AD The  incidence  of  warfare  in  early  Anglo-­‐Saxon  England  between  550  AD  and  700  AD.  Red   indicates  the  aggressor,  green  the  aIacked   06/03/14 pag. 94
  94. 94. Lines B Originator Receiver A C I B F G I B K G K C D H L M E H I B M B B E J C B A K M E G C I D L E K F J G M A H F (a) J C L I D H (b) (c) Insight  into  even  a  short  list  of  telephone  calls  (a)  is  enhanced  by   their  node-­‐link  representa8on  (b),  especially  if  disconnected  subsets  can  be  iden8fied  (c)   06/03/14 pag. 95
  95. 95. Useful?   (b)   (a)   A  representa8on  of  mortgage  ac8vity:  (a)   lenders,  proper8es  (houses),  buyers,  etc.  are   represented  by  small  radial  segments  of  an   annulus  as  shown  in  (b),  and  their   rela8onships  denoted  by  straight  lines   06/03/14 pag. 96
  96. 96. A  threshold  has  been   imposed  to  suppress  the   display  of  normal  behaviour.   As  a  result,  unusual   behaviour  is  revealed  by  the   paIerns  formed  by  the  lines    
  97. 97. hIp://seekshreyas.com/beerviz/     06/03/14 pag. 98
  98. 98. hIp://visualiza8on.geblogs.com/visualiza8on/network/     06/03/14 pag. 99
  99. 99. Chord diagram 06/03/14 pag. 100
  100. 100. 06/03/14 pag. 101
  101. 101. An ‘association’ style chart depicting the African bombings 06/03/14 pag. 102
  102. 102. Part of a ‘timeline’ style chart depicting the Kennedy assassination  Source:  Courtesy  i2  Ltd.   06/03/14 pag. 103
  103. 103. Sankey diagram hIp://bost.ocks.org/mike/sankey/     06/03/14 pag. 104
  104. 104. Remember this one? 06/03/14 pag. 105
  105. 105. Flow map diagram Migration from Colorado, migration from Norway and Latvia, whisky exports from Scotland.   Verbeek,  K.,  Buchin,  K.,  &  Speckmann,  B.  (2011).  Flow  map  layout  via  spiral  trees.  IEEE   06/03/14 transac8ons  on  visualiza8on  and  computer  graphics,  17(12),  2536-­‐2544.   pag. 106
  106. 106. Most familiar use of lines? Harry  Beck’s  original  London  Underground  map   Source:  ©  Transport  for  London   06/03/14 pag. 107
  107. 107. The Underground map in use prior to the introduction of Harry Beck’s map Differences?   Easier  to  use?   Source:  ©  Transport  for  London   06/03/14 pag. 108
  108. 108. Journey time? 06/03/14 pag. 109
  109. 109. hIp://www.london-­‐tubemap.com/journey_8mes.php     06/03/14 pag. 110
  110. 110. hIp://www.tom-­‐carden.co.uk/p5/tube_map_travel_8mes/applet/     06/03/14 pag. 111
  111. 111. Social networks   The  social  choices  of  fourth  grade  students  (aXer  Moreno,  1934)     06/03/14 pag. 112
  112. 112. (a)  Social  choices  among  department  store  employees  (b)  Social  choices  among  department   store  employees,  with  marital  status  encoded  (c)  Social  choices  among  department  store   employees,  with  age  range  encoded  (blue  <30,  30  <yellow  <40,  red  >40)   Source:  L.C.  Freeman  
  113. 113. Overview •  Encoding of value –  Univariate data –  Bivariate data –  Trivariate data –  Hypervariate data •  Encoding of relation –  Lines –  Maps and diagrams 06/03/14 pag. 114
  114. 114. Maps and diagrams Swimming Pool Hotels Golf Course Restaurant A B C D E F G Facili8es  offered  by  eight  hotels   06/03/14 pag. 115
  115. 115. Venn diagram Swimming pool B D Golf F A C E G Restaurant 06/03/14 pag. 116
  116. 116. A Venn diagram representation of the attributes of 24 hotels Swimming pool Figure  3.83   Golf Restaurant 06/03/14 pag. 117
  117. 117. InfoCrystal Price * Number of bedrooms Garden size The  development  leading  from  a  Venn  diagram  to  an  InfoCrystal.  The  InfoCrystal   illustrated  allows  visual  queries  to  be  made  concerning  price,  garden  size  and  number  of   bedrooms.  The  asterisk  represents  houses  sa8sfying  criteria  on  Price  and  garden  size  but   06/03/14 pag. 118 not  number  of  bedrooms    
  118. 118. An Infocrystal representation of the hotel data Swimming Pool Golf 5 2 0 4 4 1 8 Restaurant 06/03/14 pag. 119
  119. 119. Cluster map 06/03/14 pag. 120
  120. 120. Cluster map A  cluster  map  representa8on  of    24  hotels,  each  described  by  four  aIributes   Source:  Courtesy  ChrisLaan  Fluit,  Aduna   06/03/14 pag. 121
  121. 121. TalkExplorer Details  in  lecture  6:  case  studies   06/03/14 pag. 122
  122. 122. Tree representations designated root node parent of A sibling of A A leaf nodes child of A leaf nodes 06/03/14 pag. 123
  123. 123. Tree visualizations hIp://www.informa8k.uni-­‐koeln.de/ ls_juenger/research/vbctool/     Problems?   06/03/14 pag. 124
  124. 124. Alternative: cone trees (a) (b) (a)  A  tree    (b)  The  corresponding  cone  tree   06/03/14 pag. 125
  125. 125. Cam tree: horizontal orientation of cone tree 06/03/14 pag. 126
  126. 126. Construction of a Tree Map The  Tree   Forma8on  of  the   Tree  Map   The  Tree  Map   06/03/14 pag. 127
  127. 127. Slide and dice construction Tree Tree Map The  ‘slice-­‐and-­‐dice’  construc8on  of  a  Tree  Map  to  obtain  leaf  nodes  represented  by  rectangles   more  suited  to  the  inclusion  of  text  and  images     06/03/14 pag. 128  
  128. 128. Tree map display of an author’s collection of reports Source:  Courtesy  of  Ben  Shneiderman   06/03/14 pag. 129
  129. 129. Map of the market hIp://www.marketwatch.com/tools/stockresearch/marketmap     06/03/14 pag. 130
  130. 130. hIp://www.hivegroup.com/solu8ons/demos/usda.html     06/03/14 pag. 131
  131. 131. hIp://www.ny8mes.com/interac8ve/2008/05/03/business/20080403_SPENDING_GRAPHIC.html?_r=0  
  132. 132. Ben Sheiderman on tree maps     hIp://www.youtube.com/watch?v=og7bzN0DhpI   06/03/14 pag. 133
  133. 133. Tree map pros and cons Pros? Cons? 06/03/14 pag. 134
  134. 134. Tree map pros and cons Pros Cons Color + Area (2 attributes) Hierarchy/Structure hard to convey aspect ratios Slide  adapted  from  Michael  Porath     06/03/14 pag. 135
  135. 135. Aspect ratios Which  one  is  bigger?   Slide  adapted  from  Michael  Porath     06/03/14 pag. 136
  136. 136. Aspect ratios Which  one  is  bigger?   Slide  adapted  from  Michael  Porath     06/03/14 pag. 137
  137. 137. Aspect ratios Which  one  is  bigger?   make  the  segments  more  square!     Slide  adapted  from  Michael  Porath     06/03/14 pag. 138
  138. 138. Layout Strategies / Algorithms Cluster   Squarified   Pivot  By  Middle   StripTreemap   Pivot  By  Size   hIp://hcil2.cs.umd.edu/trs/2001-­‐06/2001-­‐06.html   Slide  adapted  from  Michael  Porath       06/03/14 pag. 139
  139. 139. Sunburst hIp://bl.ocks.org/mbostock/4063423   06/03/14   pag. 140
  140. 140.   hIp://www.theguardian.com/news/datablog/2012/oct/05/beatles-­‐charts-­‐infographics  
  141. 141. hIp://hci.stanford.edu/jheer/files/zoo/     06/03/14 pag. 142
  142. 142. Hyperbolic tree   A  sketch  illustra8on  of  the  hyperbolic  browser  representa8on  of  a  tree.  The  further  away  a  node  is  from  the   06/03/14 pag. 143 root  node,  the  closer  it  is  to  its  superordinate  node,  and  the  area  it  occupies  decreases  
  143. 143. Nodes can typically be moved into center position   (a)  The  repor8ng  structure  of  the  employees  of  a  company.  (b)  One  employee  of  interest,   Rachel  Anderson,  has  been  moved  towards  the  centre,  revealing  her  subordinates   06/03/14 pag. 144  
  144. 144. Representa8on  of  the  Library  of  Congress  by  the  hyperbolic  browser  
  145. 145. hIp://philogb.github.io/jit/sta8c/v20/Jit/ Examples/Hypertree/example1.html    
  146. 146. hIp://www.autodeskresearch.com/projects/orgorgchart    
  147. 147. Readings Chapter 3 06/03/14 pag. 148
  148. 148. Questions? 06/03/14 pag. 149
  149. 149. References •  Christopher J. Morris, David S. Ebert, Penny Rheingans, An Experimental Analysis of the Pre-Attentiveness of Features in Chernoff Faces, Proceedings Applied Imagery Pattern Recognition, pp. 12–17, 1999. •  Friendly, Michael. Visualizing categorical data. SAS Institute, 2000. •  Chernoff, H. (1973). The use of faces to represent points in kdimensional space graphically. Journal of the American Statistical Association, 68(342), 361-368. 06/03/14 pag. 150
  150. 150. project 06/03/14 pag. 151
  151. 151. Team project milestones 1.  2.  3.  4.  5.  due  27  Feb.   Form teams due  13  March   Project proposal due  3  April   Intermediate presentation Final presentation Short report 22  May   due  29  May   06/03/14 pag. 152
  152. 152. Project proposal 1 page description of your intended project: –  mo8va8on   –  which  datasets  you  will  use   –  current  status.  If  available,  first  designs.   –  problems/ques8ons   due 13 March If you want earlier feedback, send us your proposal earlier ;-) 06/03/14 pag. 153
  153. 153. Data collection •  https://docs.google.com/forms/d/ 1gHwVWHZLzWdSz1F37jA1Gungrl56bT215M6FYW3YqGY/ viewform Or •  bit.ly/N6JTyD Anonymous! Choose your own ID. •  Please report your data ;-) 06/03/14 pag. 154
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