Quite some time back, I had come across this talk by Hans Rosling at ted.com. Ted is one site, which I frequently visit to listen to great speakers, tech leaders and futuristic ideas. Hans is a Swedish professor, who built a tool to present data in a visual format using multiple dimensions rather than the usual 2 dimensional graphs.
The presentation is one of the most popular ones at Ted, partly due to the fact that the tool is amazing. But a large part of it was due to Hans’ great enthusiasm. His passion for data and pedagogy is naturally evident in the video as his shows off his tool. He plays with the audience with great anecdotes and his natural humor is just endearing. I’m posting that video from Ted (its a must watch):
Hans’ website is Gapminder.org, where he talks more about his project, with more examples and datasets. Then an interesting news came up. Gapminder had been acquired by Google. Now it became even more intriguing to imagine what Google might do with it. The way Google generally works with their acquisitions is use parts from it in lot of other services and integrate the product itself in the Google ecosystem. So Google Public Data was one of the products to use some of the technology in visualizing the tons of data available on government databases. This was precisely one of Hans’ goals in unearthing data from public systems.
Finally I came across Google tables in Google Labs, which seems to be the first legitimate version of Gapminder under Google’s parentage. Now Google tables is still fairly limited in features and is more like an early beta. But already, one can see the where Google is headed to. For starters you can use one of the datasets which Google provides to create graphs and visualize data. The same principle of using multiple dimensions which Hans demoed is visible in the graphs in Google tables and the ease of doing something as potentially complicated as that is just amazing. I tried one of those visualizations on a map. This one maps the GDPs of countries of the world. In the map, the higher ranked countries are marked in a lighter shade, whereas the poorer countries are marked in darker shades. I made this up in less than 2 minutes. Although the data leant itself to such visualizations to enable the quick producing of the this chart, the tool is beautiful in itself.
