Over 120 student developers, designers, and data enthusiasts from across the United States gathered last September to participate in the University of Iowa’s 2nd Midwest Big Data Hackathon.
Groups of four students per team, spanning over fifteen universities, contributed to a non-stop, two-day project “hacking” web, mobile, desktop, or hardware applications.
“The student’s mission was to create a working prototype of their application within 2 days,” says Ibrahim Demir, Assistant Professor of Civil and Environmental Engineering, and UIOWA Hackathon Chair.
With over six-thousand-dollars’ worth of prizes, nearly half of the participating groups were awarded prizes. Categories included “Most Creative Application of Water Data Services” won by a plotting heat map of water levels. “1st Place” prize is given to an innovative VR experience, which allows users to delve through the wide-reaching space of Twitter networks.
“The goal is to create a community around this event," says Demir. “It’s not just about a single competition, but growing a list of activities.” He explains that the project created during the Hackathon is the participants' own, and they are encouraged to work on it after the event ends.
The most notable development during this year’s Hackathon was the utilization of social media, and potential artificial intelligence and machine learning projects to identify trends within data and predict potential outcomes in real time.
Demir says that sponsors like 3M, State Farm and many others, as well as a partnership with CUAHSI – a consortium of universities for water research – allowed them to attract far more participants this year. He says he expects next year to require a bigger venue than the second-floor ballroom of the Iowa Memorial Union.
Students participating in HackUiowa were provided travel, lodging, and food assistance throughout their involvement. This funding came in part by academic and industry partners.
Next year's Hackathon is expected to be scheduled for the beginning of October 2018.
For more information, visit http://bigdata.uiowa.edu.