Whether being used to locate billions of dollars in gold for savvy mining companies or tracking online contributions to Barack Obama’s campaign it appears that my esteemed colleague Chris was correct in dubbing 2008 the year of the crowd.
I was so intrigued by the idea of successfully enlisting random strangers to do important and interesting things that I did what I do whenever something incites my cat-like curiosity. I looked up “crowdsourcing” in wikipedia.
I was surprised to see that there is an unprecedented crowdsourcing program in action at the UC Berkeley Space Sciences Lab. My running buddy, Ryan “The Brain” Ogliore, works there, and he was kind enough to offer some insight into his project, AKA, Stardust.
Would you tell me a little bit about yourself and what you’re doing?
I'm a postdoctoral scholar at UC Berkeley's Space Sciences Lab. I work on NASA's Stardust mission: a comet-return from a Jupiter family comet called Wild2.
What is Stardust?
The Stardust mission captured cometary particles in a low-density material called aerogel. Before the rendezvous with the comet, the opposite side of the collector was exposed in a part of space where a stream of interstellar dust travels through our solar system. This material has been viewed astronomically before, but never has a solid sample been returned to the lab for study.
What does the Stardust crowdsourcing project entail?
The interstellar dust particles that were collected by Stardust are microscopic, and they make very tiny tracks in the aerogel. To scan the entire surface of the detector would take many person-years of microscope-searching. The detector containing the interstellar tracks was photographed digitally. The logical thing to do, then, would be to program a computer to scan through these digital images and find the tracks.
This turns out to be a very difficult if not impossible problem, because the aerogel contains many imperfections and cracks that would fool an image-recognition algorithm. A person, however, with minimal training, can identify these particle tracks with high accuracy.
So Stardust@home was created as a way to have hundreds of volunteers search the microscope images and identify particle tracks that interstellar dust made in the detector. Using test images randomly given to the volunteers, or "Dusters" as they've called themselves, we determined that they were very good at this task.
The volunteers are extremely dedicated, abundant, and talented. Unlike other projects, like SETI@home, which are essentially a large, distributed electronic computer, Stardust@home is a network of human brains doing something that (at this point in time) only human brains can do extremely well.
How long has the program been in place and what have your results been so far?
The project has been going on for a year and a half and we already have something to show for it: last week, three of the candidate interstellar particles, found by our volunteers, were extracted from the detector.
The project's success is dependent on the work of the volunteers -- this is real science, unique and exciting, that was made possible by the "crowds" of passionate people, eager to be involved with the science.
I think this kind of cool space stuff appeals to a lot of people, and the opportunity to actually search for an interstellar needle in a haystack is something people jumped on: every time you log in you can see a piece of never-before-seen galactic material.
Is there anything else you’d like to share?
The Stardust@home approach has proven successful and could spawn another image recognition project: instead of looking for interstellar dust, trained eyes can search for hominids.
Thanks a lot, Ryan!
(End of Interview)
Even aside from all of the amazing things that are being accomplished with crowdsourcing, I am constantly impressed by the underlying sentiment from which these projects emanate. More than anything else, I think that crowdsourcing highlights the willingness of people to pitch in and selflessly donate their time based on their desire for excitement, a challenge, or simply to help in whatever manner they are able. As much as crowdsourcing can accomplish for the original sourcer, the fulfillment and sense of purpose it provides the crowd should not be overlooked or undervalued.
To quote Bill Nye – science rules!