Each Friday we share some favorite reporting on, and examples of, data driven visualizations and embedded analytics that came onto our radar in the past week.
Round Numbers: To celebrate Pi Day on March 14 – augmented this year by two more digits (3.1415) – the Washington Post rounded up 10 pi-related data visualizations on its Wonkblog. Several examples – including the one above, which color-codes the first 13,689 digits of pi and displays them on an appropriately circular graphic – were created by Martin Krzywinski, a Canadian bioinformatics designer whose day job is visualizing cancer genomes . Be sure to visit and bookmark Krzywinski’s website, which includes an extensive, well-rounded collection of data visualization resources.
Daily Data: Giorgia Lupi and Stefanie Posavec are at the midpoint of “Dear Data,” a fascinating year-long data visualization project. Each week the two women collect data on a selected aspect of their lives, hand-draw original visualizations of that data on postcards, and mail the results to each other. So far, the topics have ranged from phone-use and shopping to the number of times they look in the mirror (illustrated by Posavec above). The women, both professional data visualization designers, share their work online as time permits. They say the project “challenges the increasingly widespread assumption that “big data” is the ultimate and definitive key to unlocking, decoding and describing people’s public and private lives.”
Heads Up: Last month, the Guardian’s Data Blog (subtitle: “Facts are Sacred”) published an interactive map showing every known meteorite fall on earth. (We show a snippet above; click through for the complete, interactive version.) They also published the underlying data and an explanation of how they created the map. While it’s fun to explore, the map is also an object lesson in how data collection impacts results: Because the map only displays found meteorite falls (either the meteorites themselves or the impact craters left behind were cataloged), the data correlates with population density; if nobody is around to collect the data, the data doesn’t get collected. In other words, don’t assume based on the map above that you’re less likely to be struck by a meteor if you’re sailing on the ocean or visiting Kazakhstan.