Data is part of everything we do, especially given the current open data movement. From financial market performance to farmer’s market locations, weather to health care, bridge and road safety to population information, significant amounts of data are yielded and available for aggregation and analysis, and can be applied to improve public services. This is the philosophy behind the open data movement —that if we make all of this data available to the public, at least the high-value data, we can crowdsource public service issues and come up with the best possible solutions.
But open data is only as good as the data analytics platforms and true data transparency policies on which it relies. Bringing big data, open data and data transparency together empowers data to solve some of the world’s most challenging problems. Over the last few years alone, I have seen big data used to reduce sepsis, understand Parkinson’s disease, combat child sex trafficking and fight Ebola, among many other noble causes.
One such cause was the University of Texas at Austin (UT) and the Texas Advanced Computing Center collaborating on two Data for Good hackathons to develop solutions to prevent, detect, fight and reduce mosquito-transmitted diseases, including the Zika virus. More than 120 data scientists, engineers and UT Austin students brought together their diverse set of skills to apply data to a number of questions related to the virus.
In the first hackathon, solutions involved scraping outbreak data from the Centers for Disease Control and Prevention (CDC), the World Health Organization (WHO) and other similar organizations around the world. These “hackers” paired the data with news reports and social media feeds to create visualizations of the quick progression of Zika cases across Central America in an effort to learn more about the Aedes mosquito and the spread of the virus. One participant presented a method to detect stagnant bodies of water and differentiate between green or brown bodies of water from a clear pool or a stream in hopes of identifying prime mosquito breeding grounds. Others worked on a data collection mobile app that allows people to quickly and easily report potential Zika cases and symptoms on their mobile device.
At the second hackathon, projects focused on research in the clinical and epidemiological areas of Zika. Projects ranged from identifying Zika in water samples using metagenomic data to exploring the Zika protein and docking to identify potential drugs to fight infections. The identification of Zika in publicly available water sample data was a huge discovery — and proof that these projects have the potential of making a significant scientific impact. These projects are hopefully the seed to future discoveries or insights.
