Information Visualisation - Lecture 1

@wassxILV Informationsvisualisierungen
Information
Visualisation
#viz_lnz
Information
Visualisation
Lecture 1 - Foundations

ILV Informationsvisualisierungen #viz_lnz @wassx 2
Why Visualize?
"The ﬁrst and main goal of any graphic and
visualization is to be a tool for your eyes and brain to
perceive what lies beyond their natural reach".
Alberto Cairo in "the functional art"

Knowledge transfer
www.nickmilton.com

Knowledge transfer
http://imgur.com/gallery/S83PHzp

Analysis and exploration
http://xkcd.com/552/

Analysis and exploration
https://en.wikipedia.org/wiki/Correlation_and_dependence

Planning and decision making
© The New Yorker Collection. 2002. Leo Cullum from cartoonbank.com.

Planning and decision making
http://wol.iza.org/articles/redesigning-pension-systems/long

Why Visualize?
• Visualisation leverages the incredible capabilities and bandwidth of the
visual system to move a huge amount of information into the brain
very quickly.
Designing Data Visualizations, Noah Iliinsky & Julie Steele, O'Reilly 2011

Why Visualize?
very quickly.
• Visualisation takes advantage of our brains built-in "software" to
identify patterns and communicate relationships and meaning.

Why Visualize?
very quickly.
• Visualisation can inspire new questions and further exploration.

Why Visualize?
very quickly.
• Visualisation helps identify sub-problems.

Why Visualize?
very quickly.
• Visualisation helps identify sub-problems.
• Visualisation is really good for identifying trends and outliers,
discovering or searching for interesting or speciﬁc data points in a
larger ﬁeld.

Why Visualize?
Move information from point A to B.

Exploratory vs Explanatory
Exploratory
Point A is the dataset and point B is the designer's
own mind.

Exploratory
"You have a whole bunch of data and you're
not sure what's in it."
"This type of visualisation is typically part of the data
analysis phase, and is used to ﬁnd the story the data has
to tell you."

Exploratory
http://www.messenger-education.org/workshops/MLA_topography_print_labels.jpg
Water Ice Data from Mercury

Exploratory vs Explanatory
Explanatory
Point A is the designer's mind and point B is
the mind of the reader.

Explanatory
"You know what the data has to say, and you are trying to
tell that story to somebody else."
"This type of visualisation is typically part of the
presentation phase."

Explanatory
http://messenger.jhuapl.edu/news_room/presscon12_multi.html
Water Ice Data from Mercury

Explanatory
http://www.bloomberg.com/graphics/2015-whats-warming-the-world/

From Information to Wisdom

1970's Richard Saul Wurman,
Prof. of architecture in North
Carolina, predicted oncoming
information explosion needs
professionals in organising data:

1970's Richard Saul Wurman,
Prof. of architecture in North
Carolina, predicted oncoming
information explosion needs
professionals in organising data:
"Information Architects"

Information Architect's main goal:
"Fight information anxiety"
Superhero by Mordok78
www.deviantart.com

Information Architect's main goal:
"Fight information anxiety"
„The black hole between data and knowledge“
aka
Superhero by Mordok78
www.deviantart.com

Superhero by Mordok78 www.deviantart.com
• Structural design of shared information environments

• Combination of organisation, labelling, search, and
navigation systems within websites and intranets

• The art and science of shaping information products and
experiences to support usability and ﬁnd-ability

• The art and science of shaping information products and
experiences to support usability and ﬁnd-ability
• An emerging discipline and community of practice focused
on bringing principles of design and architecture to the
digital landscape

DIKW Hierarchies
Unstructured
Information
Data
Outer world
Gathering and ﬁltering
First level of encoding

DIKW Hierarchies
Unstructured
Information
Data
Structured
Information
Outer world
Second level
of encoding
Communicators

DIKW Hierarchies
Unstructured
Information
Data
Structured
Information
Knowledge
Outer world
Second level
of encoding
Audiences decode
what is presented using
memories and experiences
Communicators

DIKW Hierarchies
Unstructured
Information
Data
Structured
Information
Knowledge Wisdom
Outer world
Second level
of encoding
In-depth understanding
and memorization
Audiences decode
what is presented using
memories and experiences
Audience
Communicators

Further Literature
„Polar Bear Book“
Peter Morville & Lois Rosenfeld

Summary
• Visualisation is a tool to transfer information
• Different use cases (Exploratory vs. Explanatory)
• Consider „information consumers“ (knowledge)
• Give information the right shape -> Information Architect

Brainwork

from „the functional art“, Alberto Cairo

0
100
200
300
400
Brazil Colombia Venezuela Peru Argentina Chile Ecuador Bolivia
Discussion
vs

Absolute values

Relative values

ArmedForces(Thousandsofpeople)
0
100
200
300
400
Population (Millions of people)
0 50 100 150 200
21,6
7,1
2,6
1,2
2,14,6
0,9
0,2
million dollars per year
Brazil
Colombia
Bolivia
Ecuador
Chile
Venezuela
Argentina
Peru
check $ per year

Form follows function

Louis Sullivan
American Architect
"The Tall Ofﬁce Building Artistically Considered", 1896

"All things in nature have a shape ... an outwards
semblance, that tells us what they are ... Unfailing in
nature these shapes express the inner life, the native
quality of the animal, tree, bird, fish that they present
to us. 
It is the pervading law of all things organic and
inorganic ... that the life is recognisable in its
expression, that form ever follows function. This is
the law."
Louis Sullivan, "The Tall Office Building Artistically Considered," March, 1896
http://academics.triton.edu/faculty/fheitzman/tallofficebuilding.html

• "The form of a thing is a clue to its nature"  
(->Affordances: Spoon vs. iPod)

• Inﬂuence on 20th century architecture (Bauhaus)

• Inﬂuence on 20th century architecture (Bauhaus)
• Today's interpretation: human centred design
http://www.bethkanter.org/wp-content/uploads/130.png
Used under „Fair use“ doctrine

unidirectional relationship?

Functions constrain forms

Relationship between forms and function is
bidirectional

Brainwork

Morgan Stanley
RBS
Deutsche Bank
Crédit Agricole
Société Générale
Barclays
BNP Paribas
Unicredit
UBS
Credit Suisse
Goldman Sachs
Santander
Citigroup
JP Morgan
HBSC
0 100 200 300 400
January 2007 January 2009

Morgan Stanley
RBS
Deutsche Bank
Crédit Agricole
Barclays
BNP Paribas
Unicredit
UBS
Credit Suisse
Goldman Sachs
Santander
Citigroup
JP Morgan
HBSC
0 100 200 300 400
Value Change
Loss  
(2007 - 2009)
2009 2007
Morgan Stanley
RBS
Deutsche Bank
Crédit Agricole
Barclays
BNP Paribas
Unicredit
UBS
Credit Suisse
Goldman Sachs
Santander
Citigroup
JP Morgan
HBSC
0 100 200 300 400

Are bubbles always bad?

http://www.xocas.com/blog/en/wp-content/uploads/2012/11/map_shift_margin_big.png
Xaquín G.V.

Tufte vs. Holmes
Artist unknown
Used under the fair use doctrine

Edward Tufte Nigel Holmes
vs.
„The engineer“ „The designer“

Edward Tufte
Edward Rolf Tufte
„The engineer“
„is an American statistician and professor
emeritus of political science, statistics, and
computer science at Yale University. He is
noted for his writings on information design and
as a pioneer in the ﬁeld of data visualization.“
https://en.wikipedia.org/wiki/Edward_Tufte

Edward Tufte
Minimalism and Efﬁciency
„A visual design project is good if it
communicates a lot with little.“
Edward R. Tufte

Edward Tufte
• Graphical excellence is the well-designed presentation of
interesting data - a matter of substance, of statistics, and of design.

Edward Tufte
interesting data - a matter of substance, of statistics, and of design. 
• Graphical excellence consists of complex ideas communicated
with clarity, precision, and efﬁciency.

Edward Tufte
interesting data - a matter of substance, of statistics, and of design. 
• Graphical excellence consists of complex ideas communicated
with clarity, precision, and efﬁciency. 
• Graphical excellence is that which gives to the viewer the greatest
number of ideas in the shortest time with the least ink in the
smallest space.

Edward Tufte

Edward Tufte
Data-ink ratio
Data-ink ratio =
Ink that encodes data
Total amount of ink used to print the graphic
Replace „ink“ with „pixels“ for our usage…

Edward Tufte
Data-ink ratio
Data-ink ratio =
150px
1000px
= 0.15
The closer the data-ink ratio is to 1.0, the better the
graphic is, according to Tufte.
Data pixel
„Chartjunk“

Nigel Holmes
„The designer“
Nigel Holmes
„Is a British/American graphic designer, author,
and theorist, who focuses on information
graphics and information design…In 1977,
worked in the map and chart department of
Time magazine, where Holmes later became
graphics director.“ 
https://en.wikipedia.org/wiki/Nigel_Holmes

Nigel Holmes

Nigel Holmes
17.500
35.000
52.500
70.000
1978 1979 1980 1981 1982

Discussion

Hands-on #1
Search an information graphic for each category:
1. Exploratory
2. Explanatory 
in the internet or newspaper. Write a brief review (one
paragraph) concerning topics learned in this lesson.  
Propose and explain improvements.
~3 people present their results as a basis for discussion
next time.

Related
People:
Peter Morville
@morville
nigel holmes
@nigelblue
Edward Tufte
@EdwardTufte
Alberto Cairo
@albertocairo

Information Visualisation - Lecture 1

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