The NCRN-Cornell node is a part of the NSF-Census Research Network, the first nodes of which were created and funded in 2011.

For more information, see http://www.ncrn.cornell.edu

Recent Submissions

  • How Will Statistical Agencies Operate When All Data Are Private 

    Abowd, John M (2016-09-06)
    The dual problems of respecting citizen privacy and protecting the confidentiality of their data have become hopelessly conflated in the “Big Data” era. There are orders of magnitude more data outside an agency’s firewall ...
  • Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics 

    Haney, Samuel; Machanavajjhala, Ashwin; Abowd, John M; Graham, Matthew; Kutzbach, Mark (2017-05-14)
    National statistical agencies around the world publish tabular summaries based on combined employeremployee (ER-EE) data. The privacy of both individuals and business establishments that feature in these data are protected ...
  • Proceedings from the 2016 NSF–Sloan Workshop on Practical Privacy 

    Vilhuber, Lars; Schmutte, Ian; Abowd, John M. (2017-01-22)
    On October 14, 2016, we hosted a workshop that brought together economists, survey statisticians, and computer scientists with expertise in the field of privacy preserving methods: Census Bureau staff working on implementing ...
  • CED 2 AR: The Comprehensive Extensible Data Documentation and Access Repository 

    Lagoze, Carl; Vilhuber, Lars; Williams, Jeremy; Perry, Benjamin; Block, William C. (Digital Libraries (JCDL), 2014 IEEE/ACM Joint Conference on, 2014-12-04)
    We describe the design, implementation, and deployment of the Comprehensive Extensible Data Documentation and Access Repository (CED 2 AR). This is a metadata repository system that allows researchers to search, browse, ...
  • How Will Statistical Agencies Operate When All Data Are Private? 

    Abowd, John M. (Journal of Privacy and Confidentiality, 2016-09-06)
    The dual problems of respecting citizen privacy and protecting the confidentiality of their data have become hopelessly conflated in the “Big Data” era. There are orders of magnitude more data outside an agency’s firewall ...

View more

Statistics

RSS Feeds