221 research outputs found

    The Federal Big Data Research and Development Strategic Plan

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    This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

    The Federal Big Data Research and Development Strategic Plan

    Get PDF
    This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

    Graduate Research Fair Program, 2011

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    Trust as a Competitive Parameter in the Construction Industry

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    DEVELOPMENT OF A QUALITY MANAGEMENT ASSESSMENT TOOL TO EVALUATE SOFTWARE USING SOFTWARE QUALITY MANAGEMENT BEST PRACTICES

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    Organizations are constantly in search of competitive advantages in today’s complex global marketplace through improvement of quality, better affordability, and quicker delivery of products and services. This is significantly true for software as a product and service. With other things being equal, the quality of software will impact consumers, organizations, and nations. The quality and efficiency of the process utilized to create and deploy software can result in cost and schedule overruns, cancelled projects, loss of revenue, loss of market share, and loss of consumer confidence. Hence, it behooves us to constantly explore quality management strategies to deliver high quality software quickly at an affordable price. This research identifies software quality management best practices derived from scholarly literature using bibliometric techniques in conjunction with literature review, synthesizes these best practices into an assessment tool for industrial practitioners, refines the assessment tool based on academic expert review, further refines the assessment tool based on a pilot test with industry experts, and undertakes industry expert validation. Key elements of this software quality assessment tool include issues dealing with people, organizational environment, process, and technology best practices. Additionally, weights were assigned to issues of people, organizational environment, process, and technology best practices based on their relative importance, to calculate an overall weighted score for organizations to evaluate where they stand with respect to their peers in pursuing the business of producing quality software. This research study indicates that people best practices carry 40% of overall weight, organizational best v practices carry 30% of overall weight, process best practices carry 15% of overall weight, and technology best practices carry 15% of overall weight. The assessment tool that is developed will be valuable to organizations that seek to take advantage of rapid innovations in pursuing higher software quality. These organizations can use the assessment tool for implementing best practices based on the latest cutting edge management strategies that can lead to improved software quality and other competitive advantages in the global marketplace. This research contributed to the current academic literature in software quality by presenting a quality assessment tool based on software quality management best practices, contributed to the body of knowledge on software quality management, and expanded the knowledgebase on quality management practices. This research also contributed to current professional practice by incorporating software quality management best practices into a quality management assessment tool to evaluate software

    Catalog 2021-2022

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    Catalog 2020-2021

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