The NCRN-Cornell node is a part of the NSF-Census Research Network, the first nodes of which were created and funded in 2011.
As part of the Cornell node's activities, we are building a Comprehensive Extensible Data Documentation and Access Repository (CED²AR) designed to improve the documentation and discoverability of both public and restricted data from the federal statistical system. The CED²AR will be based upon leading metadata standards such as the Data Documentation Initiative (DDI) and Statistical Data and Metadata eXchange (SDMX) and be flexibly designed to ingest documentation from a variety of source files.
We are also developing High Performance Logistic Regression Methods for Data Edits and Imputation for (a) multiple response variables (Census example: race/ethnicity coding) as well as (b) incompletely coded links (Census example: unit-to-worker imputation).
Finally, we are teaching a multi-site distance learning class on "Social and Economic Data" (INFO 7470). The course is designed to teach students basic and advanced techniques for acquiring and transforming raw information into social and economic data. The course is particularly aimed at American Ph.D. students from multiple fields (economics, political science, demography, sociology, etc.) who are interested in using confidential U.S. Census Bureau data, and the confidential data of other American statistical agencies that cooperate with the Census Bureau. We cover the legal, statistical, computing, and social science aspects of the data "production" process. More information is available at the course website http://www.vrdc.cornell.edu/info7470/.