Using Data Science to Solve Society's Problems

By Samuel Greengard  |  Posted 2016-04-05 Email Print this article Print
 
 
 
 
 
 
 
Data Science

In the Data Science Bowl, researchers work on real problems to develop solutions that will benefit society. This year's competition focused on heart disease.

Over the last decade, data science has evolved from a promising idea into a mainstream tool that businesses and others use to take products and services to an entirely different level. Of course, data science is also valuable for addressing a growing array of problems in areas including medicine and biology.

"The advances in the field are profound," observes Steven Mills, a principal and data science executive leader at management and IT consulting firm Booz Allen Hamilton. "Data science now touches almost every aspect of our lives."

One of the offshoots of this is the just completed Data Science Bowl, a 90-day open competition that the organization launched last year in collaboration with data science organization Kaggle. This year's topic, "Transforming How We Diagnose Heart Disease," attracted 993 participants and involved 1,392 algorithms.

The winning algorithm was built by Qi Liu and Tencia Lee, hedge fund analysts and self-described "quants" (experts in quantitative analysis). They have no medical experience, but they were able to create an algorithm that can diagnose heart disease from an MRI scan in real time. Currently, it requires 20 minutes for a doctor to analyze the scan. This technique could also trim medical costs and enable new research methods.

The National Institutes of Health and Children's National Medical Center contributed data for the project. Chip maker Nvidia contributed an additional sum to the cash prize, which reached $125,000—up from $100,000 in 2015.

An Algorithm to Monitor Ocean Health

Last year, teams examined the topic "Assessing Ocean Health at a Massive Speed & Scale." Oceanographers from Oregon State University's Hartfield Marine Science Center supplied the data.

For that competition, participants examined more than 100,000 images in the search for an algorithm that would allow researchers to monitor ocean health at a speed and scale never before possible. A team from Ghent University (which finished in second place this year) captured the top prize with an algorithm that automatically classifies more than 100,000 underwater images of plankton.

The Data Science Bowl is designed to increase awareness about data science and to encourage people to go into the field. Yet, it's also about focusing attention on real-world issues and problems.

"What is compelling about the competition is that there are researchers from around the world working on a very real problem with very real benefits to society," Mills explains. "Although the prize money is substantial, most people enter the competition because they are passionate about data science and making the world a better place. Many of the participants are passionate about what they do, and they are eager to contribute to society."

The contest also benefits Booze Allen Hamilton and Kaggle, which compete for a limited number of data scientists. In addition to the Data Science Bowl, about once per quarter, Booz Allen Hamilton holds internal events and competitions designed to help its 600 data scientists grow professionally and solve other social problems, ranging from pet adoption to poverty.

"It has become imperative for companies to have data scientists focused on complex problems," Mills points out. "These events are an opportunity to promote learning and knowledge sharing, while addressing real issues and problems."



 
 
 
 
Samuel Greengard writes about business and technology for Baseline, CIO Insight and other publications. His most recent book is The Internet of Things (MIT Press, 2015).
 
 
 
 
 
 

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