This IPRO section will focus on challenges offered by American Red Cross, a Motorola Solutions Foundation grantee, related to innovating concepts to improve preparedness and responsiveness to fire emergencies, informed by studying a diversity of big data sets, patterns and insights derived from them.

Anticipating and managing disasters has never been more critical to the safety of individuals, property, and the economy, than it is today. The purpose of this IPRO project is to apply “Big Data” techniques to improve public safety relative to natural and man-made disasters. Our initial focus will be on learning the “Big Data” analytical research process – Data Gathering, Pre-Processing, Modeling and Visualization. We will then explore our findings for logical implications for the future, and Predictive Analytics.

Given the above purpose, the IPRO team will pursue the following goals:

1. Work in teams to select and explore a specific research question in a socially relevant topic. This goal will be accomplished by students reflecting on and sharing what is important to them and using their passions to select a topic area and a specific research question to address public safety in the face of disasters with a focus on fire emergencies.
2. Learn each step of the Big Data analytical research process. This goal is addressed by organizing IPRO team members that study a large data set to identify and answer an important questions associated with an urban social/technical issue, their research question in a compelling way and show their results.

Students representing a variety of disciplines have an opportunity to explore their interests and apply their knowledge in a collaborative way that creates enhancements for public safety and preparedness for and responsiveness to fire emergencies: information design, devices and applications, designs and technology solutions for the built environment, social behavior patterns, public policy and the regulatory environment, etc.

ADDITIONAL BACKGROUND INFORMATION ON BIG DATA: This IPRO section is inspired by the conviction that data science is the foundation field on which to introduce a progressive, developmental approach to building “data consciousness” into the fabric of learning. This includes learning how to make decisions based on the best available data, and to discern and understand the meaning of the data they may encounter. Issues of ethics, privacy and security also come into play in a variety of organization settings. The goal is to advance all learners toward higher levels of data competency: data literacy (understanding data and statistical concepts) begins in the early years, data science expertise (designing data science analyses) typically starts in the undergraduate college years, and data science mastery (building data science systems and performing complex analyses) is developed at the graduate school and working professional levels. This then extends to the responsibility professionals have as citizens and as leaders in a range of roles in society, the economy and government.

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