One of the tenets of the so-called Web 2.0 is that it’s about an “architecture of participation”, allowing users (i.e., everyone) to contribute their knowledge and expertise — or just enthusiasm — to harness our “collective intelligence”. That’s why Wikipedia is about as good as the Britannica — and why you can look up photos of pretty much anything out there on Flickr.
But now we’ll be able to put that collective intelligence to some really good use: astronomy. One of the hardest, most human-intensive tasks has always been “morphological classification”, that is, using how something looks to assign it to a particular group. In particular, astronomers since the early 20th Century have classified galaxies according to categories first enumerated by Edwin Hubble (who also discovered the expansion of the Universe that underlies the Big Bang). Galaxies are either Spirals (like all the famous pictures that you have seen) or Ellipticals (round, smoothly-distributed agglomerations of stars) with subcategories describing the details (and at least some of the underlying physics).
For perfect images, this is the kind of problems that Artificial Intelligence techniques like neural networks have been able to handle with some success. But with realistic, messy data humans are still much better — and if lots of people can vote, it’s even possible to iron out disagreements. At GalaxyZoo, a group of young astronomers, including Oxford’s Kate Land, Chris Lintott, Anse Slosar, and Kevin Schawinski, have teamed up with the Sloan Digital Sky Survey, the largest single dataset of galaxy images yet produced, and created a website that lets the rest of us out on the internet help with that classification — no formal training required, although there are practice images and a test to make sure you can handle the pressures of modern science.