Excellence in Research: Human Centered Visual Analytics for Evidence Based Decision Making in Hunger Relief

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Food insecurity defined as the uncertain or limited access to safe and nutritious food for an active, healthy life is a growing problem in the United States. Nonprofit hunger relief organizations, such as food banks, play a significant role in providing safe and nutritious food to people who experience food insecurity. Hunger relief operations rely on evidence based decisions and they lack scientifically-based validated tools and resources that can assist their decision making. This project integrates the computing power of data analytics with human factors to improve evidence based decision making that impacts food insecurity and hunger relief operations. This project has substantial benefits to society. The ability to provide evidence based decisions through interactive visualization that combines analytical power and human reasoning will empower food banks to have better understanding of all aspects of food bank operations including behaviors of donors and partner agencies, demand and supply, and therefore, allow them to make informed decisions to help the people in need. This project will enable hunger relief organizations to satisfy greater demand by more efficiently allocating available resources, thus impacting human life. The nature of this project has the potential to increase participation of underrepresented minority students to conduct research in the application of engineering to problems with societal benefit. This project will focus on improving the way hunger relief organizations interact with information and develop a systematic approach that is human centered and accounts for human cognitive limitations to provide interactive visual analytics toolkits that are accessible, interpretable, and readily implementable, and are tailored to hunger relief operations. This project will significantly contribute to the knowledge base with regard to data analytics and visualization of in-kind donations and food need, which is an important but understudied topic. This project will provide a framework for how big data can be synthesized and visualized that is truly human centered in the hunger relief sector and transform the way the operations of these organizations interact with information and improve the efficiency and effectiveness of their decision making.This project is co-funded by the Historically Black Colleges and Universities-Undergraduate Program (HBCU-UP).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.