When I watched Barack Obama accept the Nobel Peace Prize, I thought about how the world has changed since the inception of the prize, and how it will continue to change. Since the winners of the Prize are themselves a reflection of what’s changing, I thought I’d try using Freebase to visualize them over the century the Prize has existed.

What you can find out, with Freebase, depends on its coverage of the topics you’re asking about. So realize that what I’ll show here is possible because Nobel Peace Prize winners are a well-covered topic. Still, it’s wildly impressive.

The Nobel site tells us that 89 Nobel Peace Prizes have been awarded since 1901. I haven’t been able to reproduce that number in Freebase because there are multiple winners in a few years, and I haven’t found a way to group results by year. But for my purposes this related query is good enough:

That number, 100, isn’t as closely related to 89 as you might think. It’s less by the number of years no award was given, but more by the number of recipients in multiple-award years. Perhaps a Freebase guru can show us how to measure those uncertainties, but I’ve eyeballed them and I don’t think they invalidate my results.

How did I wind up querying the topic /award/award_winner? It wasn’t immediately obvious. I spent a while searching and then exploring the facets that emerged, including:

The crazy thing about Freebase is that, in a way, it doesn’t matter where you start. Everything’s connected to everything, so you can pick up any node of the graph and re-dangle the rest.

Except when you can’t. I haven’t yet gotten a good feel for which paths to prefer and why.

But in the end I came up with the kind of results I’d envisioned:

1901-2009 nobel peace prize winners by gender
male female

1901-2009 nobel peace prize winners by nationality
male female

Taken together they show a couple of trends. First, of course, we see most female winners after about 1960. Second, we see a more even geographic distribution of female winners because, prior to 1960, most winners were not only male but also American or European.

These results didn’t surprise me. What did is the relative ease with which I was able to discover and document them. I thought it would be necessary to write MQL queries in order to do this kind of analysis. I’d previously done a bit of work with MQL, and dug further into it this time around.

But in the end I found that it was just as effective to use interactive filtering. Now to be clear, getting the software to actually do the things I’ve shown here wasn’t a cakewalk. I had to develop a feel for the web of topics in the domain I chose. And it’s painfully slow to add and drop filters.

But still, it’s doable. And you can do it yourself by pointing and clicking. That is an astonishing tour de force, and a glimpse of what things will be like when we can all fluently visualize information about our world.