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

美国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，可以扩展到在联邦政府持有的大型数据集上操作。研究人员将与几个大型联邦政府统计机构合作。鉴于这些机构必须在收集和保存私人机密数据的双重使命方面争取平衡，同时使这些数据可用于研究和政策问题，因此这个专题特别重要。这项资助将支持一个多学科、多机构的团队，参与者来自五所大学、一个非营利组织和一个国家实验室。这些学科包括计算机科学、统计科学和系统工程。

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.