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Explore Data: Data Science + Visualization | PDF
Explore Data:
Data Science +
Visualization
Roelof Pieters
PhD candidate at KTH &
Data Science consultant. 
@graphific
(much thanks &
graph love to fellow
presenter Jay
Solomon* / Augify)
*who unfortunately
couldn't make it today
Visualizations 

are everywhere
Data Science Visualization
High friction software
Scientific Visualization
Output from Algorithms
Data Science Visualization
Data journalism
Infographic design
Visualisation tools
Data Science Visualization
Data Visualization / Why?
Title
Data journalism / Faces of Fracking
http://www.facesoffracking.org/data-visualization/
Infographics design / Nobel Prizes and laureates 1901-2012 by Accurat
http://www.accurat.it
Gephi gephi.github.io
Tableau www.tableausoftware.com
Bokeh bokeh.pydata.org/en/latest/
Processing processing.org
R-ggplot2 ggplot2.org
Visualisation tools
d3.js d3js.org
What is a
Visualization?
Visualization is data communicated visually
“with clarity, precision and efficiency” (Tufte)
Defined?
But it is more than that,
The role of visualization is to communicate
data meaning through stories
The goal of visualization is to aid our understanding of data
by leveraging the human visual system's highly-tuned
ability to see patterns, spot trends, and identify outliers.
Well-designed visual representations can replace cognitive
calculations with simple perceptual inferences and improve
comprehension, memory, and decision making.
By making data more accessible and appealing, visual
representations may also help engage more diverse
audiences in exploration and analysis.
The challenge is to create effective and engaging
visualizations that are appropriate to the data.
A Tour Through the Visualization Zoo. Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky.
The challenge is to create effective
and engaging visualizations that are
appropriate to the data.
A Tour Through the Visualization Zoo. Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky.
This is a.. ?
and don’t you forget it :)
This is a Graph This is a Chart
Some interesting books…
How do you move from data to visualization?
How do you determine the appropriate visualization
for your data?
How do you use visualizations to create meaning and
extract valuable insights?
And many questions..
What’s in a
Visualization?
Visual Storytelling Experience
1 2 3
Position
Size
Shape
Color
Metaphor
Sequence
Structure
Content
Language
Interactivity
Adaptability
Discovery
Reaction
Familiarity
Visual Storytelling Experience
1 2 3
1
How do you make data visual?
Visual
The goal of visualization is to aid our understanding of data
by leveraging the human visual system's highly-tuned
ability to see patterns, spot trends, and identify outliers.
A Tour Through the Visualization Zoo. Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky.
How would you visualize proportion?
Pie Donut Nightingale Voronoi
Stacked area chart Stacked bar Treemap
72% 68% 50% 47%
“Sneaker pickup”
videos
“First Impressions”
videos
Product “Review”
videos
“Haul” videos
Every decision counts; position, size and shape.
Growing genres of product reviews on youtube
https://www.thinkwithgoogle.com/articles/i-want-to-buy-moments.html
72% 68% 50% 47%
“Sneaker pickup”
videos
“First Impressions”
videos
Product “Review”
videos
“Haul” videos
Every decision counts; position, size and shape.
(Our version)
Find the right balance between
Accuracy , Aesthetics & Meaning
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
Color as a natural quantifier (Tufte)
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
Color as metaphor and meaning
http://demographics.coopercenter.org/DotMap/index.html
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
Color as metaphor and meaning
http://demographics.coopercenter.org/DotMap/index.html
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
From “Envisioning Information”, Tufte. General Bathymetric Chan of the Oceans,
International Hydrographic Organization (Ottawa, Canada, 5th edition, 1984), 5.06.
Color as metaphor and meaning
Title
http://drones.pitchinteractive.com
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
Shape as visual metaphor
http://drones.pitchinteractive.com
http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/
Shape as visual metaphor
http://chrisharrison.net/projects/bibleviz/BibleVizArc7.png
2
How do you tell a story with data?
Storytelling
Because stories are powerful & memorable
Stories are made of conceptually separable episodes 

or sub-goals in a chain of actions that form the story’s plot.
Stories contain microstructures via the particular details of
an event and macro-structure via the relationship of those
events to one another in the plot
A Deeper Understanding of Sequence in Narrative Visualizsation. Hullman, Drucker, Riche…
Scroll through episodes / New York Times data driven stories
http://www.nytimes.com/interactive/2014/06/12/world/middleeast/the-iraq-isis-conflict-in-maps-photos-and-video.html
Animated sequence / 2015 Measles outbreak
http://www.bloomberg.com/graphics/2015-measles-outbreaks/
Animated sequence / 2015 Measles outbreak
http://www.bloomberg.com/graphics/2015-measles-outbreaks/
Animated sequence / Bloomberg business
http://www.bloomberg.com/news/articles/2015-03-04/u-s-companies-are-stashing-2-1-trillion-overseas-to-avoid-taxes
Layering the data / Poverty Tracker, CPRC
http://povertytracker.robinhood.org
Interactive visualization / New York Times
http://www.nytimes.com/interactive/2014/upshot/buy-rent-calculator.html
3
How do you enable the user to
interact with the visualization 

& discover relevant insights?
Experience
What is the story you want to tell?
Unfocused query generates irrelevant story
#1 Query
What is the story you want to tell?
Identify appropriate data
Determine what question to ask
Guide through suggestions
=
INSIGHT
Consider the many sides to the same story
#2 Lenses
Like a novel, a narrative can be read through the
characters, the context, the events, the emotional
landscape
Enable exploration and discovery
Reveal the data at several levels of detail, from a broad
overview to the fine structure
#3 Filter
http://www.informationisbeautiful.net/visualizations/snake-oil-superfoods/
Filters
Silders to explore and see change
http://www.nytimes.com/interactive/2014/07/08/upshot/how-the-year-you-were-born-influences-your-politics.html?abt=0002&abg=0
‘What if’ scenario
http://www.nytimes.com/interactive/2014/11/04/health/visuals-ebola-model.html
http://www.nytimes.com/interactive/2014/11/04/health/visuals-ebola-model.html
‘What if’ scenario
Sometimes less is more
Think of layering and separation of the data
visualization, reduce the noise and let the content shine
#4 Options
Focused view / Connect the world cup
http://www.nytimes.com/interactive/2014/06/20/sports/worldcup/how-world-cup-players-are-connected.html
Reduce the noise / What can you discover when you reduce the noise? Outliers, focused question and
answer….
Reduce the noise / What can you discover when you reduce the noise? Outliers, focused question and
answer….
Reduce the noise / What can you discover when you reduce the noise? Outliers, focused question and
answer….
Divide the story to relevant portions.
A complex graph may not be enough. Look at the micro
vs. macro stories and how they help extract insights.
Try different metrics
#5 Insights
Small multiples / A visual guide to the crisis in Iraq and Syria.
http://www.nytimes.com/interactive/2014/06/12/world/middleeast/the-iraq-isis-conflict-in-maps-photos-and-video.html
Interactive linked small multiples / Close the gap
http://ri.id.au/closethegap
#7 Experiment & test your hypothesis…
Until you find the best visual representation
Visualization that answers a question: Who is most affected?
http://www.nytimes.com/interactive/2013/05/27/science/drunk-driving-2011.html?_r=0
What about 

graphs?
Internet as a Graph
(S. Carmi,S. Havlin, S. Kirkpatrick, Y. Shavitt, E. Shir. 

A model of Internet topology using k-shell decomposition. 

PNAS 104 (27), pp. 11150- 11154, 2007)
Internet as a Graph
Graphs / Notation
nodes edges
Graphs / Notation
Graphs / Communities
Graphs / Community Attributes
(S. Papadopoulos, Y. Kompatsiaris, A. Vakali, P. Spyridonos. “Community detection in Social Media” 2011)
Connected Network
Ego Network
Demo Time
Chinese Conversation Networks on Weibo
Topic Networks
Topic Networks for Crisis Management and
detection of interconnected topics
Conversation Networks
Design Choices
Design Choices
Design Choices
Design Choices
Design Choices
Design Choices
Design Choices
Thank you for your attention!

Explore Data: Data Science + Visualization