Nadieh Bremer
Nobody thinks in words or numbers. We think in images because we are all visual beings
More than 70% of all the sensory receptors in the body are in the eyes
Evolution has transformed our brains to identify patterns
Data is growing bigger
Computers are getting faster
Analyses are becoming more complex
The results from the insights found can no longer be explained with simple charts
Gain Chart
Parallel Coordinates
Heatmap
Streamgraph
Intuitive to comprehend the whole picture
View both simple and complex data
See abnormalities, dependencies and trends not apparent from tables
Unclear visual encodings
Too many variables
Too many data points
with
In listening to stories we tend to suspend disbelief in order to be entertained
Whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled
John Allen Paulos
Stories match the way the human brain understands information
Stories are
| emotional
Stories are
| memorable
Stories are
| impactful
Define your audience
Set the scene
Introduce the characters
Create tension
Provide resolution
Novice
Is new to the subject but doesn't want oversimplification
Manager
Seeks in-depth, actionable understanding of intricacies with access to detail
Expert
Wants more exploration and discovery and less business
Executive
Needs to know the significance and conclusions
(you already know the story)
Contextualize by giving the necessary introduction, what will the audience be looking at, before showing any data
Make it clear what to look at, especially where to start looking
Keep in mind that stories have a beginning, middle, and end
Explain gradually what each visual encoding means, e.g.
The essence of a data visualization is converting data into visual elements - bars, lines, points, colors, etc.
Colors
Shapes
Axes
(don’t just label)
Limit complexity at first by gradually exposing your data
Start by showing one interesting datapoint or insight and explain this in full detail
Inviting readers to draw their own conclusions is risky because even simple data sets can convey different messages
In the end give the audience either
Unclear visual encodings
Too many data points
Too many variables
Explicit visual encodings
Gradual introduction of data points
Independent introduction of variables
For lasting effect you need to persuade the rational brain
But also resonate with the emotional brain
Measles heatmap: http://graphics.wsj.com/infectious-diseases-and-vaccines/
Gain chart: http://sten.tamkivi.com/2013/05/week-37-small-world-churn-measuring-sales-startup-hr/
Streamgraph: http://antheawhittle.com/post/336352214/this-stream-graph-visualisation-shows-your
Parallel Coordinates: http://stackoverflow.com/questions/19213961/parallel-coordinates-program-written-with-processing-cant-show-anything-in-mac
SOM heatmap: http://www.visualcinnamon.com/portfolio/heatmaps
Buildings in the Netherlands: http://code.waag.org/buildings/
Genome similarities: http://www.swissinfographics.com/archives/308
Data Sweetspot: Cannot remember, sorry
Brazil's demographic opportunity: by Alberto Cairo from The Functional Art
Phone brand Switching: http://www.visualcinnamon.com/portfolio/phone-brand-switching
U.S. Gun Deaths: http://guns.periscopic.com/?year=2013
Apple stock: http://www.nickdiakopoulos.com/2013/09/17/storytelling-with-data-visualization-context-is-king/
Urbanization in East Asia: http://www.visualcinnamon.com/portfolio/urbanization
General 5 step concept based upon and inspired by Michael Freeman's talk at Strata: http://mfviz.com/strata
Visualization examples: