Digital Government: Data Confidentiality, Data Quality and Data Integration For Federal Databases: Foundations to Software Prototypes

数字政府：联邦数据库的数据保密性、数据质量和数据集成：软件原型的基础

• 批准号: 0131884
• 负责人: Alan Karr
• 金额: $ 124万
• 依托单位: National Institute of Statistical Sciences
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0131884&HistoricalAwards=false
• 关键词: Digital; Government; Data; Confidentiality; Quality

EIA-0131884Alan KarrNational Institute of Statistical SciencesDigital Government: Data Confidentiality, Data Quality, and Data Integration for Federal Databases: Foundations to Software PrototypesThis award will support research in data confidentiality, data quality, and data integration. Prototypes will be built which can scale to operate on large sets of Federally held data. Researchers will partner with several large Federal Government statistical agencies. This topic is of particular importance given the balance of these agencies must strive for, in terms of their dual missions to collect and keep private confidential data, while at the same time making that data accessible for research and policy issues. This grant will support a multi-disciplinary multi-institution team, with participants from five universities, one non-profit, and one national laboratory. The disciplines represented include computer science, statistical science, and systems engineering.

国家统计科学研究所数字政府：联邦数据库的数据机密性、数据质量和数据集成：软件原型的基础该奖项将支持数据机密性、数据质量和数据集成方面的研究。将建立原型，这些原型可以扩展到对联邦政府持有的大型数据集进行操作。研究人员将与几家大型联邦政府统计机构合作。考虑到这些机构必须在收集和保存私人机密数据，同时使这些数据可供研究和政策问题使用的双重任务方面取得平衡，这一专题尤其重要。这笔赠款将支持一个多学科、多机构的团队，参与者来自五所大学、一所非营利性组织和一个国家实验室。代表的学科包括计算机科学、统计科学和系统工程。