In addition, those behind it (Seed and GE) are also connecting people in the real world with their data visualization marathons for students, which are looking to be the dataviz equivalent of the ever popular hackathons held around the world. As far as I know no one else is really doing this sort of thing, with a couple notable exceptions - for example Datakind and their Data Dive events (these not strictly visualization focused, however).
Okay, enough copious hyperlinking.
The latest challenge was to visualize the return on education around the world using some educational indicators from the OECD, and I thought I'd give it a go in Tableau Public.
For my visualization I chose to highlight the differences in the return on education not only between nations, but also the gender-based differences for each country.
I incorporated some other data from the OECD portal on GDP and public spending on education, and so the countries included are those with data present in all three sets.
The World Map shows the countries, coloured by GDP. The bar chart to the right depicts the public spending on education, both tertiary (blue) and non-tertiary (orange), as a percentage of GDP.
The scatterplots contrast both the gender-specific benefit-cost ratios per country, as well as between public (circles) and private (squares) benefit, and between the levels of education. A point higher up on the plots and to the left has a greater benefit-cost ratio (BCR) than a point lower and to the right, which represents a worse investment. The points are sized by internal rate-of-return (ROR).
All in all it was fun and not only did I learn a lot more about using Tableau, it gave me a lot of food for thought about how to best depict data visually as well.