This Project will support the establishment of a Big Data Consulting Services and Training Center at the University of Georgia (UGA). The goal of this center is to provide faculty and students with basic consultation and training services in order to help them more efficiently meet their data collection, processing, storage, access, sharing, curation, and publications needs. The project proposes to focus on three areas: 1) the use of high performance computing; 2) data management; and 3) cross-disciplinary coordination. Many of the elements are already in place at UGA to support data intensive research. For example, the Georgia Advanced Computing Resource Center (GACRC) and the CUDA Teaching Center already offer resources and some training on the use of high performance computing; the UGA Libraries offer services to help researchers write data management plans; and there are a variety of campus-wide and national resources that researchers can use for their data generation, analysis, and management needs. However, currently there is no clearinghouse or coordinating organization to which any researcher on campus can turn into in order to best incorporate data-intensive approaches into their research. To meet these needs, the project plans to: Form a campus-wide committee comprised of faculty, administrators, information technology (IT) staff, librarians, and students. Survey the campus in order to get a better understanding of data management needs. Visit with individuals who are working with data that are large, long-term, and/or structurally complex to learn about their needs in more detail and identify the campus and national resources that are available for big data users. The project will then develop a set of web resources that can serve as both a central resource for the campus and a starting point for further efforts to enhance UGA's cyberinfrastructure capabilities. Finally, the project will continue to conduct the popular university-wide "big data" events under the auspices of the center to aid in communicating, coordinating, and disseminating activity around data-intensive research.
