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.

研发（R＆D）导致创建新的基于科学的技术创新。 有必要提高人们对研究发现如何转化为新技术的理解，然后发展为有用的创新。 用于解决此问题的方法要么利用大量历史信息的趋势，要么借鉴专家判断。 该项目将采用先进的研究技术来增强识别趋势和模式的方法，并帮助预测创新途径。 这种知识对于通过明智地投资于高希望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的科学领域。该项目将提供一个案例研究，以改善五个分析过程，这对于改善预测创新途径的方法论至关重要。 要分析的情况是大数据和分析吗？ ？一个非常重要的话题。 弄清楚如何从大型数据集中获得优势将影响国家科学进步，工业生产力和防御。 同时，大数据提出了隐私和安全性问题。 之所以选择大数据的话题，是因为美国政府问责办公室（GAO）正在研究。 我们希望与GAO共享有关方法和发现的信息，以了解使我们的方法更有用的方法。 。该提案扩展了一个先前资助的SCISIP项目（1064146），以解决一个时间限制的机会来解决GAO案件。