Data visualizations are not ‘seen’ in a glance – they require active exploration, across a series of visual filtering operations.
With @talboger + @SBMost, we show that these powerful filters can cause 93% of people to miss a *dinosaur* within the ignored data values. #ieeevis
With @talboger + @SBMost, we show that these powerful filters can cause 93% of people to miss a *dinosaur* within the ignored data values. #ieeevis
We gave people a tough visual task within the pattern of blue values, causing them to ignore the green values. 93% missed these ‘Jurassic Marks’ at 1s, and 61% still missed them at 2.5s.
Try the experiment, watch the 8-min talk, or read the paper here: datasaurus-vis.herokuapp.com
Try the experiment, watch the 8-min talk, or read the paper here: datasaurus-vis.herokuapp.com
What does this mean for you?
When your visualization needs to communicate a data pattern, use ‘storytelling’ (annotate + highlight key values/comparisons), and ask sample viewers what they see.
Otherwise, your audience may not see what you see in your visualization.
When your visualization needs to communicate a data pattern, use ‘storytelling’ (annotate + highlight key values/comparisons), and ask sample viewers what they see.
Otherwise, your audience may not see what you see in your visualization.
@talboger drove this project
(Awarded Best Short Paper at #ieeevis), so keep your eye out for him at Ph.D. admissions time next fall.
Original datasaurus here thefunctionalart.com/2016/08/downlo…
#sorrynotsorry, @AlbertoCairo
(Awarded Best Short Paper at #ieeevis), so keep your eye out for him at Ph.D. admissions time next fall.
Original datasaurus here thefunctionalart.com/2016/08/downlo…
#sorrynotsorry, @AlbertoCairo
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