Name: Home TA: Lab #4 Citizen Science: Disk Detective
Introduction
This lab is the first of several “Citizen Science” labs we will do together this semester as part of the zooniverse.org project family. The concept of Citizen Science is that some Astronomical databases are so large and the data so complex that computer algorithms cannot accurately or reliably sort through all of the data to find the kinds of interesting things that astronomers are looking for.
For example, consider NASA’s Wide-field Infrared Survey Explorer (WISE) mission: this is a space based telescope that surveyed the entire sky for the first time ever in the infrared part of the spectrum. As a result, we now have a catalog of infrared images of around 700 million astronomical objects. These objects could be asteroids, galaxies, planets, stars, nebulae, or any number of strange objects.
That’s where scientific analysis comes in. We must examine the images closely along with other data (in this case, images of the same objects taken at different wavelengths by other surveys) in order to classify the objects we have found. What we are looking for specifically in this case are circumstellar dusty disks that indicate the possible presence of a planetary system.
These kinds of objects are extremely difficult for automated programs to spot. Sure, a very smart computer program might be able to find some dusty disks if you give it some basic guidelines of what to look for, but inevitably, some objects in the sky are outside of the boundaries of whatever definition you provide to your computer algorithm. The human eye, it turns out, is far better at basic pattern recognition that any computer algorithm, and so astronomers have turned to crowdsourcing to find dusty disks buried in their immense ocean of data that computers have missed.