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

几乎每个研究领域和行业都在努力从大量数据集中管理和提取有用的信息，这些数据通常被称为大数据。建模、数据管理和分析是理解和使用这些数据集的关键要素，它们在学术界和工业界的重要性预计将呈指数级增长。一个核心挑战可以表述如下：给定特定的分析任务和对可用大数据的特定约束，我们如何实现从数据中高效、安全地提取端到端价值？为了应对这一挑战，我们建议在现有的混合多核生产力研究中心（CHMPR）I/UCRC的新站点加入行业成员和参与学术中心，该中心位于北卡罗来纳州罗利的北卡罗来纳州立大学（NCSU），目标是进行跨学科的转化科学和研究，以便在大数据的情况下更好地做出决策。在CHMPR/NCSU完成的基础研究将转化为技术开发，为困难问题提供实用的解决方案。这一翻译将适用于联邦机构、政府组织和正在努力解决大数据难题的行业部门，从而为科学进步做出贡献，并推动行业和社会未来的大数据需求。成功解决从海量数据中提取价值的问题取决于平衡基础研究、技术诀窍和商业市场情报。我们建议既解决这一问题的公认方面，又发展科学和培训，以解决这一问题的未来方面。CHMPR/NCSU致力于端到端的数据支持，将重点开发技术和工具，以弥合数据获取与实时和长期决策之间的时间差距。CHMPR/NCSU研究项目将解决什么是适当的技术问题：存储和清理数据;数据建模;使数据安全;提出正确的分析问题;预处理和后处理与分析有关的数据;最后，使分析结果有用。由此产生的技术将适用于多个行业，包括国家安全、医疗保健、制造业、能源和商业智能。NCSU正在进行的研究将有助于CHMPR的计算密集型分析研究计划，同时通过NCSU的大数据转换和分析专业知识补充其产品组合。从拟议的工作中产生的技术和工具将改变可以从数据中获得的结果，而不仅仅是更快地获得结果。大数据分析行业这种范式转变的最终成功将取决于NCSU等大学是否有能力利用数据支持科学和技术来解决各种现实生活中的应用。

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.