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Dr Will Stahl-Timmins
The Farr Institute 16 May 2016
INFORMATION GRAPHICS in context
information graphics
(dataviz) (infographics)
(data journalism)
charts / graphs
7%8%
10%
11%
29%
35%0
25
50
75
100
2007 2008 2009 2010
0
25
50
75
100
2007 2008 2009 2010
charts / graphs
charts / graphs
William Playfair (1759–1823)
charts / graphs
maps / data maps
maps / data maps
ISOTYPE – Otto and Marie Neurath
ISOTYPE – Otto and Marie Neurath
maps / data maps
wayfinding
tower graphics
tower graphics
http://www.angelamorelli.com/water/Angela Morelli
diagrams
diagrams
diagrams
diagrams
Sankey diagrams
Sankey diagrams
motion graphicsRöysopp - Remind Me (Music video)
and other things?http://infosthetics.com http://www.informationisbeautiful.net
http://www.visualcomplexity.com/vc/ http://www.densitydesign.org/blog/
why visualise data?
efficient communication?
engagement with audience?
emotive connection?
to explain complex
information?condensing into a small space?
enabling comparisons?
quick overview?
selective focussing?
exploration
explanation
production methods
1. Use standard graph tools
2. Use existing specialist data visualisation tools
3. Do it by hand
4. Develop new specialist data visualisation tools
1. Use standard graph tools
Open Office / Microsoft Excel / Apple Numbers
SPSS / Stata / R
2. Use existing specialist data visualisation tools
Inco
me
per P
erso
n of
the
Wor
ld
Life Expectancy of the World
Liechtenstein
Antigua&Barbuda
Dominica
Palau
NauruTuvalu
Seychelles
St. Kitts& Nevis
AndorraSan Marino
Monaco
Andorra
St.LuciaPanama
Sao Tomeand Principe
Tonga
Samoa
Grenada
Brunei
Comoros
Djibouti
Equatorial Guinea
Gabon
Luxembourg
Namibia
Swaziland
Timor-Leste
Micronesia
Trinidad and Tobago
Albania
Bhutan
Kiribati
Kosovo
Cyprus
Maldives
Slovenia
Suriname
Belize
Mauritius
Bahamas
Malta
Vanuatu
Montenegro
Estonia
Gambia
Guinea-BissauLesotho
Botswana
Mongolia
Oman
Qatar
Iceland
Barbados
BahrainCapeVerde
Latvia
SolomonIslands
Macedonia
Fiji
Guyana
Jamaica
St.Vincentand G.
Armenia
Lithuania
Uruguay
Mauritania
Moldova
Kuwait
Congo, Rep.Liberia
Bosnia and H. Croatia
Lebanon
Israel
Costa Rica
Puerto Rico
New Zealand
Georgia
Central African Rep.
SwedenSingapore
Norway
Ireland
Finland
Austria
Turkmenistan
Slovak Rep.
Kyrgyzstan
Eritrea
DenmarkTaiwan
Papua New Guinea
Hong Kong
United Arab Emirates
South Sudan
Switzerland
Hungary
BelarusAzerbaijan
Dom.R.
Bulgaria
Serbia
Burundi
LibyaNicaragua
Palestine
Sierra Leone
Laos
Benin
Guinea
Somalia
Tajikistan
Togo
El Salvador
Honduras ParaguayJordan
Poland
Bolivia
Haiti
Czech Rep.
Portugal
Tunisia
Rwanda
GreeceBelgiumCuba
Chad
Senegal
Zimbabwe
Zambia
Cambodia
Ecuador
Guatemala
BurkinaFaso
MalawiNiger
Mali
Kazakhstan
Netherlands
Chile
Romania
Cameroon
Sri Lanka
Cote d'Ivoire
Angola
Madagascar
Syria
Australia
Mozambique
Yemen
North Korea
Afghanistan
Ghana
Nepal
Sudan
SaudiArabia
PeruVenezuela
Malaysia
Morocco
Uzbekistan
Italy
Spain
UK Germany
Canada
France
South Korea
Philippines
Vietnam
Ethiopia
Egypt
IranTurkey
Dem. Rep. Congo
Thailand
South Africa
Myanmar
Colombia
Ukraine
Tanzania
Kenya
Argentina
Algeria
Iraq
Uganda
ChinaBangladesh
Indonesia
Pakistan
USA
Russia
Brazil
Nigeria
Japan
Mexico
India
2011 data for all 193 UN Members and for Hong Kong, Kosovo, Palestine, Puerto Rico and Taiwan.
Documentation andpdf version for print at:
3 orless
10100 1000
millions
Colour by region
Size by population
If you want to see more data visit:
www.gapminder.org
Free to copy, share and remix, but attribute to
Gapminder Foundation.
Version 11 September 2012
map
layo
ut b
y Pao
lo Fa
uson
e
gapminder.org/downloads/world-pdf
GAPMINDER WORLD 2012Mapping the Wealth and Health of Nations
Healthy
Poor Rich
Sick
50
500 1 000 2 000 20 0005 000 10 000 50 000
60
70
80
55
65
75
income per person in US Dollars (GDP/capita, PPP$ inflation adjusted, log scale)
life
exp
ecta
ncy
in ye
ars
Gapminder - Hans Rosling
3. Do it by hand
(or work with a specialist)
Software:
Presentation software Illustrator InDesign
Premiere After effects Animate
Processing / D3 HTML5 / Javascript Other programming languages
Stills {Motion}
Interactive {
4. Develop new specialist data visualisation tools
55 75 95
ADAS
-cog
MM
SE SIB
othe
rAD
CS-A
DL
DAD PDS
othe
rNPI
othe
rCI
BIC
GD
SCD
RAD
CS-C
GIC
QoLauthor ageslocation
design, size & follow-up
studyquality
cog
0yr 1 2
no. ofcentres
0 10 20 30
baselineMMSE sex
outcome measures usedfunc be glo
55 75 95
ADAS
-cog
MM
SESIB
othe
rAD
CS-A
DL
DAD
PDS
othe
rNPI
othe
rCI
BIC
GD
SCD
RAD
CS-C
GIC
QoL
0yr 1 2 0 10 20 30 cog func be glo
N = 161
Donepezil 1mg N = 42 M FRandCharBlindAnaly
N = 473
M F
M F
RandCharBlindAnaly
M F
M F
RandCharBlindAnaly
Rogers et al.
1998 (B)
Rogers &
1996? Donepezil 3mg N = 40
Donepezil 5mg N = 39Placebo N = 40
Donepezil 5mg N = 154
Placebo N = 162
N = 468
Donepezil 5mg N = 157
Placebo N = 153
M FM FM F
Rogers et al.
1998 (A)Donepezil 10mg N = 157
M F
Donepezil 10mg N = 158M F
M F
M F
RandCharBlindAnaly
M FM F
RandCharBlindAnaly
M F
M F
RandCharBlindAnaly
M F
M F
RandCharBlindAnaly
N = 818
Donepezil 5mg N = 271
Placebo N = 274
N = 60
Donepezil 5mg (D)
Placebo (p)
N = 268
Donepezil 5mg N = 134
Placebo N = 129
N = 431
Donepezil 10mg N = 214
Placebo N = 217
Burns et al.
1999
Greenberg et al.
2000
Homma et al.
2000
Mohs et al.
2001
Donepezil 10mg N = 273M F
group 1 (p-D-p-p) N=30group 2 (p-p-D-p) N=30
1mg3mg5mg
5mg
10mg
5mg10mg
5mg10mg
Title
Able Baker et al. 2010
Dogg's Hamlet 2009
Echo Bazaar 2006
Gender
M F
M F
M F
M F
Ages Sites
?
Features Outcomes
N=50
N=150
N=25
Design
Control N=28
500mg N=22
Programming / scripting languages
Processing d3
javascript python etc...
1. Use standard graph tools
2. Use existing specialist data visualisation tools
3. Do it by hand
4. Develop new specialist data visualisation tools
make physical graphics
secret no. 5.
sugarstacks.com
Dr Will Stahl-Timmins
blog.willstahl.com
www.bmj.com/infographics
Twitter: @will_s_t
www.bmj.com/infographics
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