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Overview of CENS Statistics and Data Practices Research

  • Author(s): 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
  • et al.
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.

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