Design

5 posts
Making the most detailed map of auto emissions in America

Using estimates from the Database of Road Transportation Emissions, Nadja Popovich and Denise Lu for The New York Times mapped auto emissions at high granularity. Popovich described their process on Storybench: I want to make graphics that really resonate with people. If that is your goal as a visual journalist, something to think through is just how you can tie data back to a more human experience. To kind of...

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Why scientists need to be better at visualization

For Knowable Magazine, Betsy Mason looks at the state of (not so good) data visualization in science and offers some direction for how it can improve: [S]cience is littered with poor data visualizations that confound readers and can even mislead the scientists who make them. Deficient data visuals can reduce the quality and impede the progress of scientific research. And with more and more scientific images making their way into...

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Randall Munroe of xkcd on Data Stories

Randall Munroe of xkcd was on the Data Stories podcast. He talks about his work, his process, and communicating complex ideas to a wide audience. It’s amazing how much of his process overlaps with visualizing data. Worth the full listen. Tags: Data Stories, Randall Munroe, xkcd

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How data changes the design process at every stage

On Multiple Views, the Interactions Lab talks about their experience as a design studio and how quickly implementations can change when you introduce real data into the system: It’s easy to assume that the tools and approaches used for general software design apply equally to data visualization design. But data visualization design and interface design are often deeply and fundamentally distinct from one another. We learned this the hard way...

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Techniques for adding context to visualization

When it comes to meaningful visualization, context is everything. Richard Brath, at the 2018 Information+ Conference, looks back on historical visualization approaches and how they might be applied today to make data graphics easier to read and use. Tags: context, Richard Brath, talk

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Differences between enterprise data visualization and data journalism

Toph Tucker used to make graphics for Bloomberg Businessweek. Now he does enterprise visualization for finance. He wrote about the major differences between the two jobs. On the iconic Bloomberg Terminal: There are more things in Bloomberg than are dreamt of in your meetings. This was not the consensus when I worked at Bloomberg, but I now believe the Terminal is incredibly well-designed. Folks reply, “I get that it’s useful,...

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Women workers taken for a loop or four

I was drawn to the following chart in Business Insider because of the calendar metaphor. (The accompanying article is here.) Sometimes, the calendar helps readers grasp concepts faster but I'm afraid the usage here slows us down. The underlying data consist of just four numbers: the wage gaps between race and gender in the U.S., considered simply from an aggregate median personal income perspective. The analyst adopts the median annual...

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Illustrated color theory

Lauren Baldo illustrated how he applies color theory in his paintings and illustrations. You don’t have to travel far to see how this transfers to visualization. Tags: color

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Powerful photos visualizing housing conditions in Hong Kong

I was going to react to Alberto's post about the New York Times's article about economic inequality in Hong Kong, which is proposed as one origin to explain the current protest movement. I agree that the best graphic in this set is the "photoviz" showing the "coffins" or "cages" that many residents live in, because of the population density.  Then I searched the archives, and found this old post from...

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What is a bad chart?

In the recent issue of Madolyn Smith’s Conversations with Data newsletter hosted by DataJournalism.com, she discusses “bad charts,” featuring submissions from several dataviz bloggers, including myself. What is a “bad chart”? Based on this collection of curated "bad charts", it is not easy to nail down “bad-ness”. The common theme is the mismatch between the message intended by the designer and the message received by the reader, a classic error...

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