Successful Crowdsourcing Projects: Galaxy Zoo

Galaxy Zoo is an online astronomy project which invites people to assist in classifying over a million galaxies. The original project was launched in July 2007 and since there were so many galaxies to be classified, the team thought it might take at least two years for visitors to the site to work through all of them.

Within 24 hours of launch, the site was receiving 70,000 classifications an hour!


After one month 80,000 volunteers had already classified more than 10 million images of galaxies meeting the goals for the first phase of the project.

In the first year more than 150,000 from around the world have logged on to the Galaxy Zoo website to take part in the project run from Oxford University’s physics department to study images of galaxies taken for the Sloan Digital Sky Survey, a robot telescope based in New Mexico that is producing a digital map of the universe.

The volunteers had a tutorial available on the site and had to take a test before they could sign up. The two categories in which they had to classify the galaxies were spirals, which are circular pinwheels, like our Milky Way galaxy, and elliptical galaxies, which are rugby ball like shaped. Because of their complex shape, computer programs have been unable to classify the galaxies, but the human eye proved to be much better at this task.

For verification purposes, the same image was shown to several users and scientists have been struck by how good the amateurs are at classifying these images. “We’ve proved that random people are as good as professional astronomers”, Dr Chris Lintott, a member of the Oxford team, said. (source: The Telegraph)

Galaxy Zoo is a collaboration between researchers at many institutions, including Oxford University, Portsmouth University, Nottingham University, Johns Hopkins University, Yale University, University of California, Berkeley and Fingerprint Digital Media, Belfast.

This project is another example of how crowdsourcing delivers productivity that would otherwise not be possible. And another thing that is worth pointing out is the accuracy of the information provided by amateurs, who proved out to be as good as the experts in the field at classifying the images.

Other examples of successful crowdsourcing projects would be those run by Google, Amazon, Procter & Gamble, Hewlett-Packard, LEGO, Pepsi, Canada’s Cambrian House, Eli Lilly (Innocentive), Kraft, General Mills, Nike, MasterCard, iStockphoto, Zebo and many more.

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