The Design of Information

Here’s a nice interactive example of making data friendly to the average human. What country would you like to live in? With the OECD Better Life Initiative, you can pick what you care about (Environment, Work-Life Balance, Health, etc.) and see which countries rise above the rest. Another interactive wonder from the brain of Moritz Stefaner. He’s the same designer who created the Notabilia Wikipedia project that I posted about a while back. Looks like it’s time for me to move to Australia.

I recently discovered Data Stories, a podcast devoted to data visualization hosted by Moritz Stefaner and Enrico Bertini. I have been listening daily in the car on my way from here to there and have made it up to Episode #7 – Color. I think I’ve found my tribe.

Hans Rosling is an entertaining and compelling presenter. He uses the now-Google-owned Public Data Explorer technology (developed by his organization Gapminder), to take you on a journey testing your concept of the developing world.

I recommend watching him in this TED talk delivered to the U.S. Department of State:

I’m impressed with two things about the World Bank’s approach to data: first, their commitment to openness in sharing data with the world, and second, their devotion to data visualization. They have also done a nice job inviting exploration with the way they have organized their data website.

Interesting to see that the mortality rate for children under 5 in the US is about 37% higher than the average of high income OECD countries.

And the US spends way more on healthcare than almost any other country in the world. Maybe we’re not spending it on the young.

Note: The World Bank is the source of data for the sample I gave a while back using the Google Public Data Explorer.

I posted about the wind map of the United States a while back. Now there’s a global wind map. Mesmerizing.

First impression: it’s a whole lot more windy over the oceans than it is over land. Intuitively obvious (even to the casual observer, as an old friend used to say), but the visualization drives the point home instantly. Now, what happens if we combine global wind data with ocean current data? It would be interesting to see how they interact.

Thanks to Andy Kirk at Visualising Data for pointing this out.