Visualize the data on cats that drink milk or wales that dive almost a kilometer to gulp a krill. «Design for an audience»

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If you quit doing what you do right now and instead read this cool transcript of the Jonathan Corum's talk «Design for an Audience», just in two minutes you will see the magic of data visualization. I promise.


Jonathan Corum is the science graphics editor at The New York Times and founder of 13pt LLC, an information design studio. He has a sharp mind and the talent to tell comprehensible stories using the complicated data.


Here is the summary of the slides and important things from the transcript.

— Who do we make graphics for?
Remember about different audiences. You may have four: yourself, your group, department or university, journals, and the public. You may have more or fewer audiences but remember about them.
— Find the visual idea.
— Translate.
A visual idea should translate the data to your audience.
— Tell a visual story.
— Focus attention, don/t scatter it.
It often happens, that we have a lot to tell and show. It is necessary to be able to remove the redundancy.
— Show the content, not the frame.
— Show the content, not the table.

I try to eliminate that kind of heavy visual framework and get closer to the data whenever possible.

— Be consistent.
— What can you remove?
Reveal the data, get rid of the information noise like logos, dark lines.
— Reference the real world.
Connect the scientific data with the real world with a visual metaphor that reader can understand.
— Connect images and data.
— Explain why.
— Provide context.
— Build a sequence.
— Show movement and change.
The dynamics always keep the story alive.
— Encourage visual comparisons.
Place comparable things side-by-side, and highlight discrepancy.
— More labels, fewer legends.
Let reader slide over your infographics don't make them go back and forth from a picture to a key.
—Annotate.
— (Some assembly required).
I want to do the work.
I don’t want my reader to do the work.

— Data visualization: use the tools you have.
It might be Excel (note: use REPT function).
—  Start small.
— Don't lose sight of the real world.
— Edit vectors.
— Try interactive notebooks.
For example, Jupiter, R-Studio, Google's Colaboratory.
— Communicate the visual data.
— Think of visualization as a process.
Sketch —> Refine —> Publish —> Explain
— Sketch for yourself...
— but design for someone else.

Jonathan's visualization tells stories about visualization in terms of cats, different grapes and wines, and wales, which dive almost a kilometer to gulp a krill. That is the best way to tell about complicated data with comprehensible, interesting story.

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25*365*2018

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