Data Visualisation is a key tool in a any researcher’s toolbox nowadays. But since graphic methods were first designed and then revisited with the introduction of computers, we kind of stopped questioning data visualisation in terms of the real value that’s adding to our research and our ability to produce new knowledge. Now with Big Data and the Real-Time web we are entering a whole new phase in the history of data Visualisation. New challenges lie ahead and new methods are being devised, so we felt compelled to look into it again to try and focus on how exactly data visualisation really helps us make sense of complexity. Fresh from our presentation at BigDataWeek London last night, here’s a quick intro to the 10 reasons why we like visualising data.

1. 10 Reasons Why
We Visualize Data
Francesco D’Orazio @abc3d !
CIO FACE facegroup.com

2. STATISTIK
“Analysis of Data about the State” to sustain the ”need of modern states to base policy on
demographic and economic data.” Emerges at the intersection of a revolution in
measurement and the rise of the Modern State.

3. “Whatever can be
expressed in
numbers,
may be expressed
by lines.”
William Playfair, 1805

4. We have come a long way
Spatial organization in the 17th and 18th century
Discrete comparison in the 18th and early 19th century
Continuous distribution in the 19th century
Multivariate distribution and correlation in the late 19th
and 20th century.

5. William Brinton, in his “Graphic Presentation” in 1939, explaining why data visualization has been so
tardy in being developed and widely adopted, despite being extremely useful.

7. All this still doesn’t
explain why
humans like to
visualise data.
Here’s 10 reasons.

8. “There is a magic in
graphs. The profile of a
curve reveals in a flash a
whole situation —the life
history of an epidemic, a
panic, or an era of
prosperity. The curve
informs the mind,
awakens the imagination,
convinces.” Henry D.
Hubbard, 1939

9. SPATIALISE information,
making it tangible and
allowing us to think with
eyes and hands.
We like it because our
perception and cognition
of the world is inherently
informed by space.
Who’s influencing the News of the World’s debate on Twitter?

10. Mountain Fear

11. Weavrs Emotion Map
OBJECTIFY abstract information in
shapes, surfaces, volumes and colors.

12. Social Media in Research Study
CLASSIFY and COMPARE data,
entities, distributions…

13. They act as an EXTERNAL MEMORY, “external scaffolding” of the
mind, allowing us to take into account a greater number of variables
and hypothesis and to move seamlessly between focused reasoning
and free associations.

14. Density Design – The Geopolitics of Sharing
“Our ability to identify
PATTERNS and
CORRELATIONS when
dealing with numbers is
incredibly poorer than
our ability to recognize
and compare shapes.”

15. DIRECT-OBJECT-MANIPULATION
on live data.
Dynamic Audience Mapping – Brand Graph

16. CONTINUOUS
ITERATION: play
with a wider
range of
hypothesis to
solve a problem.
A New
Epistemology?
Pulsar Social Data Mining platform
16

17. CONTINUOUS ITERATION: starting
with 0 hypothesis > finding out what I
don’t know I don’t know
17

18. CONTEXT and
NARRATIVE: data
visualization redefines
and encompasses the
entire problem field,
allowing us to grasp an
holistic understanding of
the problem, not just a
fraction of it.
Predicting the Oscars 2012 with multiple datasets

19. Represent PROCESS, not only structure.
“Condensed dynamic images” picture time
into spatial terms making any transformative
process visible and tangible.
50 Years of Space Exploration

21. The telescope
helped us
understand the
infinitely great.
The microscope
helped understand
the infinitely small.
Today we are
confronted with
another infinite: the
infinitely complex.

22. The key tool in our Macroscope toolbox,
helping us stay afloat in a sea of data that’s
getting deeper everyday.

23. Thanks
@abc3d !
francesco@facegroup.com!
www.facegroup.com