Big Data scares some as stories about NSA-spying and Facebook collecting personal data dominate headlines.

But data for social good?

It may sound like science fiction, but at the University of Chicago, 12 groups of summer fellows put data to use, measuring or predicting issues that range from  predictive crime to garbage route efficiency, infant immunization trends to when to expect a “code blue” in a hospital.

The Data Science for Social Good program was funded by Eric and Wendy Schmidt (the former is executive chairman for Google). The program was run by former Obama campaign data guru Rayid Ghani.

The fellows gathered in Chicago from all over the world and were partnered with mentors to tackle social problems using data available from public portals or institutions that provided anonymous data such as patient health data and prisoner information.

An event Tuesday at the university’s downtown Gleacher Center showed off the fellows’ work like a high-tech science fair. Colorful graphs lit HD displays and screens glowed with examples of how Twitter helps disaster relief workers.

“The goal for the program was to take people like me… who are interested and who have the skills in data and analytics and want to use that to help people,” said Ghani to the crowd of attendees, which included academics, city officials, representatives from the Argonne National Laboratory and a member of the Pritzker family.

Fellow Varoon Bashyakarla, a recent Yale graduate from Kansas, worked on predicting crime and searching for correlation between drug arrests and homicides.

“Before we could do anything like predict crime levels in the city, we first had to invest the time in understanding historical crime patterns,” he said.

“We see that this relationship is very clear, there’s a clear positive association,” Bashyakarla said, pointing to correlations between violent crime and historical temperatures in Chicago.

Other projects had Chicago commuters in mind.

Utilizing boarding data and schedules from the Chicago Transit Authority, University of Chicago student David Sekora’s team created a tool to allow the CTA to predict bus crowding ahead of making schedule or route changes.

“If they make a change to try and reduce crowding, what they do now is make a change, wait three months and collect all this data on the ridership and see if this made an impact,”  Sekora said. “And then they make similar changes in the future.”

The group’s collaboration with the CTA resulted in working tool. Sekora says by simulating the ridership data, CTA doesn’t have to rely on the three month test runs.

Ghani says his goal is for fellows to utilize their skills to make a difference.

“The perfect person we wanted to leave this program was a person who had the scientific background and rigor to really think hard about the problems they’re solving,” Ghani said. “It’s not enough to have the skills, you also have to care about making an impact.”

Elliott Ramos is a data reporter and Web producer for WBEZ. Follow him @ChicagoEl.