Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability - Pitts, Joshua; Gopal, Sucharita; Ma, Yaxiong; Koch, Magaly; Boumans, Roelof M.; Kaufman, Les (Frontiers in Big Data, 2020)
Abstract With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of the most pressing challenges the world faces today. There is an increasing priority placed by the UN and US federal agencies on efforts to ensure the index of these critical resources, understand their interactions, and address common underlying agendas. At the heart of the technological challenge is data science applied to environmental data. The aim of this special publication is the focus on big data science for food, water, and energy systems (FEWS). We describe a research methodology to frame in the FEWS context, including decision tools to aid policymakers and NGOs to tackle specific UN Sustainability Development Goals (SDGs). By conducting this exercise, we aim to improve the "supply chain" of FEWS research, from gathering and analyzing data to decision tools to support policymakers in addressing FEWS issues in specific contexts. We describe research in each of the segments to discuss problems and future research directions.