The Lincoln Park Zoo is asking armchair scientist to help them identify animals seen on nearly 100 web cams set up throughout the Chicago area in an attempt to between archive their photos and verify the presence of various local wildlife.

The website, Chicago Wildlife Watch has well over 300,000 photos taken by motion activated cameras that have yet to be looked at.

Seth Magle, director of the Lincoln Park Zoo's (LPZ) Urban Wildlife Institute admitted to the Chicago Tribune that while the zoo has been working tirelessly to organize these photos, "things are getting away from us a little bit."

So citizen scientist enabler Zooniverse got together with the LPZ and Adler Planetarium to make the Chicago Wildlife Watch a reality - using crowd-sourced assessments of each photo to identify Chicago's animals.

The website shows one photo at a time and asks the viewer to identify what best characterizes its coat, tail, and build or whether it's one of 29 various choices, including beaver, bird, and human. It even has the option to identify the "creature" as a bike or lawnmower... just in case.

The captured include both daytime and filler-flash-assisted night photos, and sometimes are relatively hard to see. Still, thanks to the nature of crowd-sourcing, the LPZ can pick the most popular of all identifications for the same photo in order to ensure the most optimal accuracy.

NASA launched a similar initiative not long ago, using the same fail-safe design. The "Dark Skies of ISS" project asks people from all over the world to help them identify what city or region photos from the International Space Station (ISS) are picturing.

"Without the help of citizens, it is almost impossible to use these images scientifically," explained Alejandro Sanchez, whose involved in the ISS project. "Algorithms cannot distinguish between stars, cities, and other objects, such as the moon. Humans are much more efficient for complex image analysis."

The Chicago Wildlife Watch, which started on Thursday, is no different, using people to help identify animals in hazy and poorly cropped photos that otherwise would have been useless to experts.