CC* Team: Oregon Big Data Research and Education Team

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Today, more than ever before, big data pervade every area of the life, environmental, biomedical, earth, marine, computational, physical, urban, and social sciences, as well as numerous other domains. Increasingly powerful computing technologies have opened the pathway for researchers to address major global challenges through use of large and heterogeneous data sets and through complex models and simulations. This project provides domain scientists, including research students, with the expertise and training needed to collaborate effectively with specialists in these advanced computational and statistical methodologies. The project also provides training and research experiences for students and instructors from small regional colleges, including Hispanic-serving and Native-American-serving institutions. To widely share best practices, it supports a community of practice. The project employs research and training staff (facilitators) with expertise in data integration, multi-modal data analytics and machine learning. These three related sets of methods enable the analysis of large complex data sets of different types or from different sources, which may or may not have been collected as part of a planned studies. Specifically, a four-person facilitation team is established across Oregon State University, the University of Oregon, and Portland State University. The interdisciplinary, cross institutional team will establish the tools and managements practices to serve the researchers in the state. The research facilitated by this project will lead to better understanding of earthquakes, diverse ecosystems, and plant and animal form and function. It supports development of faster computing systems, more secure energy systems, and improved environmental health. The data challenges posed by these application areas also motivate new foundational research in advanced data analytics and machine learning. The project also prepares a new generation of students from diverse backgrounds to enter the knowledge economy.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.