In 2007, Oxford doctoral candidate Kevin Schawinski, exhausted from classifying 50,000 galaxies in one week, decided to solicit help from the robust community of amateur astronomers, using a technique known as crowdsourcing. The resulting project, Galaxy Zoo, allowed volunteers to classify images from the Sloan Digital Sky Survey on their home computers.
Within 24 hours of its debut, the site was generating 70,000 classifications an hour. An upgraded Galaxy Zoo 2, launched two years later, collected 60 million classifications from tens of thousands of users in 14 months. On the back end, a statistical process called “cleaning clicks” searched for and eliminated the inevitable bogus and mistaken classifications.
The interface was so intuitive that even Galaxy Zoo participant Matthew Graham’s 6-year-old could grasp it. “She thought it was a game,” he says. But Galaxy Zoo is much more than a toy. It has produced two dozen scientific papers and identified several previously unknown objects, most notably Hanny’s Voorwerp (right), a peculiar intergalactic blob named after the Dutch schoolteacher who spotted it, and a class of hyperactive galaxies dubbed the Green Peas. “Nonexperts end up discovering weird things because they don’t know not to ask, ‘Hey, what’s that over there in the corner?’ ” says Lucy Fortson, an associate professor at the University of Minnesota and project manager for the Citizen Science Alliance.
Galaxy Zoo has since morphed into the larger Zooniverse, which oversees more than 380,000 volunteers engaged in a variety of astronomical projects. Moon Zoo is attempting to count every crater on the moon. Its volunteers have so far classified more than 1.7 million images from NASA’s Lunar Reconnaissance Orbiter. The Milky Way Project scours infrared data from the Spitzer Space Telescope for evidence of gas clouds: Participants use their computers to draw circles on cloud “bubbles” thought to result from shock waves stirred up by extremely bright young stars. Planet Hunters, meanwhile, puts citizen scientists to work analyzing readings from NASA’s Kepler space telescope, designed to find Earth-like planets orbiting other stars. Equally if not more important, scientists are using the classifications made by Zooniverse participants to develop more accurate machine-learning algorithms so that computers will be able to do this kind of work in the future.See for yourself:
Telescopes Without Borders
To learn as much as possible about distant objects, astronomers observe them with telescopes that “see” in various wavelengths. Unfortunately, the resulting data sets are archived in many locations all over the world, which makes them difficult to access; most are also inherently incompatible, so merging them requires a lot of painstaking labor. About 10 years ago, a group of astronomers started talking about creating a unified, global virtual observatory. Like the Internet, the virtual observatory is more a framework than a physical thing—a research environment linking data from a wide array of telescopes and archives and providing the tools to study them.
In the United States, an experimental version (the National Virtual Observatory) launched in 2002, but the lack of good data-analyzing tools made it difficult to use. “There was no science involved, just plumbing,” says Caltech astronomer George Djorgovski, a member of the virtual observatory’s science advisory council. “People who wanted to do science, myself included, got impatient and went to work on their own projects. No results to show, nobody wants to use it. Nobody wants to use it, no results to show.” The prospects for virtual astronomy improved dramatically last May when NASA and the National Science Foundation kicked in funding of $27.5 million over five years to finally bring the Virtual Astronomical Observatory (VAO) online and continue to develop tools for sharing data with astronomers worldwide.
The vao will not produce breakthroughs on its own, but it will make them possible. Kirk Borne likens it to the http protocol used to surf the Internet: “The Internet changed the world. But http made it possible.” See for yourself: usvao.org
Smile: The Universe
in 1 Trillion Dazzling Pixels
Early this year astronomers with the Sloan Digital Sky Survey released the largest color image of the universe ever made, a trillion-pixel set of paired portraits that covers one-third of the night sky. It includes roughly a quarter of a billion galaxies and about the same number of stars within our home galaxy, the Milky Way. The brownish image at far left—dubbed the “orange spider” by one team member—is one of the portraits, covering the Milky Way’s southern hemisphere. Each point in the image represents multiple galaxies.
A dive into the image’s densely packed imagery reveals astonishing detail. The orange box at far left calls out M33, the Triangulum Galaxy, which at 3 million light-years away is one of our closest galactic neighbors. Zooming in shows M33’s spiral form. A further zoom brings into view green, spidery NGC 604, one of the largest nebulas in M33 and home to more than 200 newly formed stars. “Astronomers can use the data we drew on to create this image as a kind of guidepost,” New York University astronomer Michael Blanton says. And so they are: In the first two weeks after the Sloan team made the map available online, researchers queried the data about 60,000 times.
SLOAN DIGITAL SKY SURVEY
Greatest Mapmaker in the Universe
The Sloan Digital Sky Survey (SDSS), launched in 2000, heralded the modern age of big-picture astronomy. For years, scientists who needed a global sense of what was out there relied on one dominant set of photographs—the Palomar Observatory Sky Survey—created in the 1950s. The Sloan Telescope (located at the Apache Point Observatory in New Mexico) retraced much of the Palomar Survey but replaced photographic plates with digital imagery that could be updated and analyzed electronically, anywhere. “Sloan was the single biggest player in converting people to embrace this approach,” says Caltech astronomer George Djorgovski. “Sky surveys became respectable not only because they brought in so much data but because the content of the data was so high that it enabled so many people to do science.”
Sloan scientists have made some spectacular discoveries. In 2000 the project’s researchers spotted the most distant quasar ever observed. But independent astronomers have authored the vast majority of the 2,000-plus scientific papers based on SDSS; they simply use Sloan public data as the basis of their research. In one dramatic example, astronomers at Cambridge University discovered the “Field of Streams,” a spray of stars stretching nearly one-quarter of the way across the sky. They seem to be the shreds of small galaxies that were cannibalized by the Milky Way.
Data mining and other tools of informatics have been particularly helpful in extracting useful information from basic brightness measurements. Such data were thought to be of secondary importance when Sloan began but actually enabled astronomers to identify 100 times as many objects as expected. University of Illinois astronomer Robert Brunner is still reveling in the Sloan’s expanded view of the universe: “Our techniques allow us to start inquiring into the relationship between dark matter and supermassive black holes and how they influence galaxy formation and evolution.” See for yourself: sdss.org
Survey Telescope Movie Camera to the Stars
The Large Synoptic Survey Telescope [LSST], being built atop Cerro Pachón in Chile, is a $450 million megaproject that will truly cement the relationship between astronomy and informatics. It is designed to probe dark energy and dark matter, take a thorough inventory of the solar system, map the Milky Way in unprecedented detail, and generally watch for anything that changes or moves in the sky.
Armed with an 8.4-meter (27-foot) optical telescope and a 3,200-megapixel camera—the world’s largest—the LSST will record as much data in a couple of nights as the Sloan Survey did in eight years. “For the first time, we’re going to have more astronomical objects cataloged in a coherent survey than there are people on Earth,” says Simon Krughoff, a member of the LSST data management team. (For those keeping score at home, experts project 20 billion objects.)
The numbers are so big and daunting that the LSST is the first astronomical project ever to formally incorporate informatics into its design architecture. “I made the case that we needed a group focused on data mining, machine learning, and visualization research to involve not just astronomers but also computer scientists and statisticians,” says Kirk Borne, who chairs the informatics and statistics team. The LSST will image the entire visible sky so rigorously that it will produce, in effect, a 10-year-long feature film of the universe. This should lead to tremendous advances in time-domain astronomy: studying fast-changing phenomena as they occur—black holes being born, supernovas exploding—as well as locating potentially Earth-threatening asteroids and mapping the little-understood population of objects orbiting out beyond Neptune. See for yourself: lsst.org