DIGH5000 class presentation on Information Visualization at Carleton University on February 24, 2014

1. Data Visualization &
Analysis
Danuta Sierhuis
MA in Art History candidate
Specialization in the Digital Humanities
Carleton University

2. Lev Manovich “What is Visualization?”
▪ “Information visualization is becoming more than a set of
tools, technologies and techniques for large data sets. It is emerging
as a medium in its own right, with a wide range of expressive
potential.” Eric Rodenbeck (Stamen Design), keynote lecture at
Emerging Technology 2008 [March 4, 2008.]

3. Lev Manovich “What is Visualization?”
▪ What is Information Visualization (Infovis)?
– Hard to make an encompassing definition
– Provisional Definition:
▪ A mapping between discrete data and a visual representation
▪ Does not cover the distinctions between static, dynamic (i.e. animated) and interactive
visualizations
▪ “Information visualization utilizes computer graphics and interaction to assist humans
in solving problems.”

4. Google Search
Infovis vs. Scientific Visualization
The majority of images returned by
searching for “information visualization”
are two dimensional and use vector
graphics - points, lines, curves, and other
simple geometric shapes.
The majority of images returned when
searching for “scientific visualization” are
three-dimensional; they use solid 3D
shapes or volumes made from 3D points.

5. Key Elements of Infovis
▪ Reduction
– Infovis uses graphical primitives, like
points, lines, curves, geometrical
shapes, to stand in for objects or
relations between them
– It reveals patterns and structures in
the data = they focus our attention
on the complex structures and
concepts that arise out the
interaction of simple elements
▪ Spatial variables
– Position, size, shape, curvature of
lines and movement = represent key
differences in the data and reveal
important patterns and relations
– “This principle can be rephrased as
follows: infovis privileges spatial
dimensions over other visual
dimensions. In other words, we map
the properties of our data that we
are most interested in into topology
and geometry. Other less important
properties of the objects are
represented through visual
dimensions – tones, shading
patterns, colors, or transparency of
the graphical elements.” (Manovich,

6. Spatial Privileging = Not New in Visual
Culture
▪ Raphael Santi, La
Disputa, fresco, St
anza della
Signatura, Vatica
n, Rome.

7. Why are spatial variables
privileged in infovis?

8. Infovis: Direct Visualization
▪ These are information visualizations that preserve the original form
of the data in the final representation
▪ They do not reduce the data to points or lines in a graph
▪ He also calls this media visualization

9. Infovis: Direct Visualization
Text as Text
Books Everyone Should
Read
http://www.informationisb
eautiful.net/visualizations/
books-everyone-shouldread/

10. Infovis: Direct Visualization
Images as Images
Jason Salavon , Every
Playboy Centerfold, The
Decades
(normalized), Digital Cprints, Ed. 5 + 2 APs. 60″
x 29.5″, 2002.
(From left to right:
1960s, 1970s, 1980s, 199
0s)

11. What are some reasons why we would want to
preserve the original form of the data in the
infovis representation? Compare and contrast
the pros-cons of infovis with reduction and
without reduction to simple graphical
elements.

12. Do infovis need to be beautiful to
provide effective results?
▪ Horoscoped
▪ http://www.in
formationisb
eautiful.net/v
isualizations/
horoscoped/

13. PROJECT: SelfieCity
http://selfiecity.net/#

14. YOUTUBE CLIP: Aaron Koblin & Visualizing
Global Texting trends in NYC
▪ http://www.youtube.com/watch?v=-SETcTrdcU4

15. In your disciplines why would you want
to use infovis? (Perhaps we could talk a
bit about the assignments from this week
at this point)

16. My experiment with NodeXL
Twitter Interactions/Reach & @lostottawa
NodeXL graph showing 50 followers of the Lost
Ottawa Twitter page and 1.5 levels of
interaction between them
NodeXL graph showing 50 followers of the Lost Ottawa
Twitter page and 2 levels of interaction between them.
This graph shows the immediate followers and a portion
of the potential reach that Lost Ottawa could achieve if
someone retweeted one their posts.

17. My experiment with Voyant
▪ “Aesthetics of Information Visualization” by Warren Sack
http://danm.ucsc.edu/~wsack/Writings/wsack-infoaesthetics.pdf
▪ http://voyeurtools.org/?corpus=1393263201539.677
▪ http://docs.voyant-tools.org/tools/

18. Tom Corby: Infovis as Art Practice
▪ There is an experiential side of information visualization
▪ Information visualization can be considered an art practice
▪ Artistic Visualization:
– Visualizations of data done by artists with the intent of making art
– Based on real data
– Not concerned with making the data beautiful in the end result

19. Artistic Visualization
▪ There is the “work-thing” and then the “aesthetic object”
▪ The work thing = the thing we can touch, preserve, etc.
▪ The aesthetic object = laid down in the collective consciousness

20. Aesthetics
▪ The field of study that examines issues of sensation and perception
and seeks to understand why something is emotionally/sensually
moving
▪ Usually aesthetics is tied to issues surrounding embodiment or
disembodiment
– Again, in relation to infovis, this begs the question of why we map information.
Why do we need to give information a body in visual form?
▪ Aesthetics of information visualization = to investigate the
judgement used to decided what about the work is
valuable, according to the senses or, in general, the body.

21. Issues of Aesthetic Interpretation
▪ There is always aesthetic noise that colors our interpretation of a
visual image
▪ Biases: education, personal experience, knowledge of the subject at
hand, and other social and historical contexts
▪ Issue of multiple meanings
– T.S. Eliot said, “No poet, no artist of any art, has his complete meaning alone.”
– QUESTION: How do we reconcile this?

22. Is it possible to accept the
results of infovis as
authoritative and truthful?
What are the issues
surrounding this?

23. Corby: Infovis as sensual and critical
art medium
Abigail
Reynolds, Mount
Fear East London
(2003)

24. Art Historical Precedents
Synthetic Cubism:
Braque, Bottle and Fishes,
Oil paint on canvas, 1910-2
Formal experiments of Russian
Constructivism
Aleksandr
Rodchenko, Composition, gouache and
pencil on paper, 1918.

25. Conclusion
▪ Lev Manovich, “The anti-sublime ideal in data art,” 2002
– If Romantic artists thought of certain phenomena and effects as unrepresentable, as something which goes beyond the limits of human senses and
reason, data visualization artists aim at precisely the opposite: to map such
phenomena into a representation whose scale is comparable to the scales of
human perception and cognition.

26. END