The Moksha Roundup
Issue #5, March 1 - 7, 2022
Welcome to this week’s Moksha Roundup! This small newsletter is a weekly roundup of the latest and greatest in the data visualization/design/visual storytelling world. Every week, we compile our favorite projects from journalists, storytellers, and technologists and share them with you.
In this issue, we share great visual storytelling pieces from The Markup, RAND Corporation, and FlowingData. If you’re not subscribed already and want to see more in the future, sign up below:
By The New York Times
The team at NYT has made a wonderful tool to bookmark if you live in a snow-covered area (or, if you like looking at pretty maps). Aatish Bhatia, Josh Katz and Margot Sanger-Katz have taken publicly available data on the probability of snowfall from the National Weather Service, and turned it into wonderful visualizations.
They first introduce your cities’ likelihood by inch in a simple-to-understand histogram of sorts, and then present maps visualizing three ranges of snowfall: the most likely number of inches, the low end, and the high end. They also do a good job of visualizing uncertainty by showing the range of potential outcomes, so you can see how confident weather forecasters are about snow in your city.Visit the piece →
By RAND Corporation
Through her role as RAND Corporation’s data artist-in-residency, information designer Gabrielle Mérite has put together one of the most gorgeous charts we’ve seen in a while, visualizing Costa Rica’s plans to become carbon-neutral by 2050.
The chart is a sort of mix between a barchart, a slopechart, and art. It organizes each sector of Costa Rica’s economy by their overall contribution to carbon emissions, and then encodes the slope of each to represent that sector’s intended change between 2018 and 2050. The use of illustrations makes the chart feel real, and makes you feel that much more connected to the environment’s future.
For more, see Gabrielle’s thread on the visualization.Visit the piece →
By The Markup
The topic at hand is location data privacy, and the tricky ways that brokers are collecting your location data without you knowing. The highlight of this article, for us, was the use an “illustrated explainer” that walks the reader through how the market for your location data has changed over time. The visuals are cute, despite the subject matter being scary. This kind of list explains the concepts well, using accessible langauge and fun illustrations to make the topic more understandable.Visit the piece →
Nathan Yau has put together another interesting visualization—nothing new here. This time, he used the Current Population Survey (which he commonly uses) to show how, since 1976, the composition of households has changed.
Since the 1970s, it seems like we’ve gotten a bit lonelier; from 21% of households only having one person in 1976, to 28% of households today. Beyond this, the chart shows how other household types, such as composite (living with roommates) are on the rise. The alluvial diagram used also feels hand-drawn, and is chock-full of meaningful annotations.Visit the piece →
By Christiaan Triebert
In an illuminating Twitter thread, investigative visual journalist Christiaan Triebert explains how journalists were able to verify the accuracy of a video alleging to depict an explosion in Ukraine.
He explains the reasons verification is important, and the tools & methods that are used (ranging from local news outlets, NASA’s active fire data, and the speed of sound).
For more information, see the related Washington Post article.Visit the piece →
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