Open Data Contest 2019

The third annual Nova Scotia Open Data Contest was held March 2-3, 2019 in partnership with the School of Information Management and the Rowe School of Business (Faculty of Management, Dalhousie University) in conjunction with International Open Data Day.

The Challenge

Participants were challenged to spend the weekend of March 2-3 developing innovative applications, visualizations, predictive models, or any creative solution using data from Nova Scotia’s Open Data portal.
Participants were free to explore any topic but Nova Scotia’s priorities of Healthy People and Communities, Investing in Early Years and Education, Safe and Connected Communities, and Inclusive Economic Growth were provided for inspiration.

The Winners

The contest began on International Open Data day, March 2 and ended on Sunday, March 3 with 28 teams delivering two-minute pitches to the panel of judges. Participants included students from Saint Mary's University, Dalhousie University, Citadel High School, and the community. 
“These students were challenged to put their creativity and problem-solving skills to work and create something new and beneficial for the public,” said Minister of Internal Services Patricia Arab. “They showed us what is possible when we use, reuse and share our data.”

First Place

First place was awarded to Om Agarwal for a predictive model to aid cancer diagnosis that uses diagnostic procedure results and machine learning to determine the likelihood of cancer.

Second Place

The team of Keji Fasuyi, Sadman Hoque Sadi and Sarbottam Thapa Magar won second place for an application that notifies food banks when businesses have surplus food to donate.

Third Place

Third place was awarded to Yingda Guo and Matthew Richard for their application using predictive modeling that examines disease prevalence and weather to predict upcoming disease trends.

People's Choice

The People’s Choice award, selected by contest participants, was won by Tina Roberts-Jeffers for an application that allows users to find activities and outings and suggests alternatives depending on various factors.

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