Help us and get involved
Researchers in Oxford's astrophysics group have come up with a novel way of dealing with the flood of images and information heading towards them from the world's telescopes and satellites: cry for help. Visitors to zooniverse.org can help sift through galaxies, explore the surface of the Moon or even hunt for planets.
The story starts back in 2007, when Kevin Schawinski, who was then a DPhil student, worked his way through 50,000 galaxies, dividing them between beautiful spirals and balls of stars known as ellipticals. Unfortunately for Kevin, his results revealed that humans were better than computers at this sort of pattern recognition task, leaving him with another million galaxies to go through.
The astronomers cried for help, and the launch of Galaxy Zoo - a website which invited the public to help Kevin sort through galaxies - was so successful that the computers that ran the site blew up! More than 100,000 people took part in this original project, and the results were spectacular. Not only was the collected wisdom of the classifiers more accurate than that of astronomers, but the team discovered a critical advantage of using human brains to sort through your data - the ability to discover the weird and the wonderful.
Objects discovered by volunteers have been puzzled over by astronomers ever since. One, a Kermit-shaped green glob of gas now known as 'Hanny's Voorwerp', has even been studied with the iconic Hubble Space Telescope. Meanwhile, a set of small, round green galaxies (known as the 'Peas') have turned out to be the most efficient sites of star formation anywhere in the local Universe.
Another side effect of the success of Galaxy Zoo is that the team's email inboxes exploded with enquiries from scientists facing their own version of the data flood that had threatened Kevin's studies of galaxies. The two most recent projects launched by the team concentrate not on distant galaxies, but on our own Milky Way.
The first uses incredibly beautiful images from the Spitzer space telescope, revealing wispy tendrils of gas sculpted into bizarre shapes by the presence of massive stars. Visitors to milkywayproject.org can use the interface to record the presence of bubbles associated with newly formed stars.
Some of those stars will undoubtedly have planets forming around them, and Planet Hunters, the second Zooniverse project launched last month, invites volunteers to take part in modern astronomy's greatest adventure - the discovery of other worlds. The task is to search for the slight dip in brightness associated with the presence of an orbiting planet.
So by logging on to the Zooniverse website, you could become the first to detect a planet, the first to explore part of the lunar surface or the first to classify an unusual galaxy. Other projects explore World War I ships logs, mining them for weather data, or detecting solar storms heading toward the Earth.
climateprediction.net is a distributed computing project to produce predictions of the Earth's climate up to 2100 and to test the accuracy of climate models. To do this, we need people around the world to give us time on their computers - time when they have their computers switched on, but are not using them to their full capacity.
The various experiments undertaken by Climateprediction.net are shown below:
- Thermohaline experiment - A study of the possible effects of a prescribed slowdown of the North Atlantic meridional overturning circulation
- Sulphur cycle experiment - With this experiment we aim identify the effects of sulphate aerosol on the global climate system and the sensitivity of the model to perturbing sulphur cycle parameters
- Mid-holocene experiment
- Geoengineering experiment - An estimate of the possible effects of climate change mitigation strategies
- Millennium experiment - An experiment to refine the accuracy of climate models of the last millennium, including the “Medieval warm period” and the “little ice age”
- Validation and attribution experiment
- Seasonal Attribution Experiment - An investigation of the possible impact of human activity on extreme weather risk.