Forecasting Innovation Pathways of Big Data & Analytics

预测大数据创新路径

• 批准号: 1527370
• 负责人: Alan Porter
• 金额: $ 5万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527370&HistoricalAwards=false
• 关键词: Forecasting; Innovation; Pathways; Big; Data

Research and development (R&D) leads to the creation of new science-based technology innovations. There is a need to improve understanding of how research discoveries translate into new technologies and then develop into useful innovation. Methods used to address this concern either draw on trends in large amounts of historic information or draw on expert judgment. This project will apply advanced research techniques to enhance methods to identify trends and patterns, and to help forecast innovation pathways. Such knowledge is vital to promote scientific progress by investing judiciously in high promise R&D. It also can aid in technology management to determine how best to advance a specific field of science.This project will provide a case study to improve five analytical processes, identified as vital to improve the methodology of forecasting innovation pathways. The case to be analyzed is ?big data & analytics? ? a topic of great national importance. Figuring out how to gain advantage from large data sets will impact national scientific progress, industrial productivity, and defense. At the same time, big data poses issues of privacy and security, among others. The topic of big data was selected because it is under study by the U.S. Government Accountability Office (GAO). We anticipate sharing information on methods and findings with GAO to gain insight into ways to make our methodology more useful. . This proposal extends a previously funded SciSIP project (1064146) to address a time-limited opportunity to address the GAO case.

研究与开发 (R&D) 带来新的基于科学的技术创新。 有必要加深对研究发现如何转化为新技术，然后发展为有用的创新的理解。 用于解决这一问题的方法要么利用大量历史信息的趋势，要么利用专家判断。 该项目将应用先进的研究技术来增强识别趋势和模式的方法，并帮助预测创新路径。 这些知识对于通过明智地投资于高前景的研发来促进科学进步至关重要。 它还可以帮助技术管理确定如何最好地推进特定科学领域。该项目将提供一个案例研究来改进五个分析过程，这些过程被认为对于改进预测创新路径的方法至关重要。 要分析的案例是“大数据与分析” ？一个具有重大国家意义的话题。 弄清楚如何从大数据集中获得优势将影响国家科学进步、工业生产力和国防。 与此同时，大数据带来了隐私和安全等问题。 选择大数据这一主题是因为美国政府问责办公室（GAO）正在研究它。 我们预计与 GAO 分享有关方法和调查结果的信息，以深入了解如何使我们的方法更加有用。 。该提案扩展了之前资助的 SciSIP 项目 (1064146)，以提供处理 GAO 案件的限时机会。