Overview of CENS Statistics and Data Practices Research
Abstract
Data, statistical models and inferential procedures permeate CENS deployments, from the four founding scientific application areas to the more recent urban sensing campaigns. This cross-center research breaks down into three classes of research: 1) General statistical models for embedded sensing, with specific applications to data quality and continuous sampling, 2) Significant CENS-designed and supported databases and repositories, and 3) Studies into the data lifecycle for embedded sensing systems.
Suggested Citation
David Fearon, Matt Mayernik, Keith Mayoral, Sheela Nair, Andrew Parker, Alberto Pepe, Erick Romero, Abhishek Sharma, Jillian Wallis, Yuan Yao, Richard Guy, Mike Taggart, Christine Borgman, Deborah Estrin, Leana Golubchik, Ramesh Govindan, and Mark Hansen. "Overview of CENS Statistics and Data Practices Research" 2009 Site Visit (2009).
Link to Full Text