I/UCRC: Site application to join I/UCRC known as CHMPR

North Carolina State University, Raleigh NC

Investigators

Abstract

Nearly every research field and industry sector is struggling with managing and extracting useful information from massive data sets, that are commonly referred to as Big Data. Modeling, data management, and analytics are key elements in understanding and using these data sets, and their importance in academia and industry is predicted to grow exponentially. One central challenge can be expressed as follows: Given specific analysis tasks and specific constraints on the available Big Data, how do we enable productive, efficient, and secure end-to-end value extraction from the data? To address this challenge, we propose to join industry members with participating academic centers in a new site of the existing Center for Hybrid Multicore Productivity Research (CHMPR) I/UCRC, at NC State University (NCSU) in Raleigh, NC, with the goal of conducting trans-disciplinary translational science and research of enabling better decision making in presence of Big Data. The fundamental research done at CHMPR/NCSU will be translated into technology developments, delivering practical solutions to hard problems. This translation will apply to federal agencies, government organizations, and industry sectors struggling with hard Big-Data problems, thus contributing to the progress of science and advancing the future Big-Data needs of the industry and society. Success in solving the problem of extracting value from massive data hinges on balancing fundamental research, technological know-how, and commercial market intelligence. We propose both to address recognized aspects of this problem and to develop the science and training that will address future aspects of this problem. The CHMPR/NCSU effort toward end-to-end enablement of data will focus on developing technologies and tools for bridging the time gap between the acquisition of data and real-time and long-term decision making. CHMPR/NCSU research projects will be addressing the issue of what are appropriate technologies for: storing and cleaning the data; modeling the data; making the data secure; asking the right analysis questions; pre- and post-processing the data with regard to the analysis; and, finally, making the analysis results useful. The resulting techniques will be applicable across multiple industry sectors, including national security, health care, manufacturing, energy, and business intelligence. The research being done at NCSU will contribute to the computationally intensive analytics-research program of CHMPR, while complementing its portfolio by the NCSU big-data transformation and analysis expertise. The technologies and tools resulting from the proposed work will change the results that can be obtained from the data, as opposed to just obtaining the results faster. The ultimate success of this paradigm shift by the Big-Data-analysis industry will rest on the ability of universities such as NCSU to prepare experts in taking advantage of the data-enablement science and technologies to solve a variety of real-life applications.