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Overview of CENS Statistics and Data Practices Research
- Fearon, David;
- Mayernik, Matt;
- Mayoral, Keith;
- Nair, Sheela;
- Parker, Andrew;
- Pepe, Alberto;
- Romero, Erick;
- Sharma, Abhishek;
- Wallis, Jillian;
- Yao, Yuan;
- Guy, Richard;
- Taggart, Mike;
- Borgman, Christine;
- Estrin, Deborah;
- Golubchik, Leana;
- Govindan, Ramesh;
- Hansen, Mark
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.