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

Research Project

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NISS conducted research in data confidentiality, data quality, and data integration. Prototypes were built which could scale to operate on large sets of Federally held data. Researchers partnered with several large Federal Government statistical agencies. This topic was 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. NISS helped convene 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.

Technical Report(s):


Research Team: 

Funding Sponsor: National Science Foundation

Principal Investigator(s): Alan Karr, NISS; Stephen Fienberg, Carnegie Mellon

Senior Investigator(s): Jerry Reiter, Duke, David Banks, Duke

Post Doctoral Fellow(s):  Adrian Dobra, Ashish Sanil, Shanti Gomatam, Xiaodong Lin

Funding Sponsors: