Data analysis tools for sensor-based science

  • Authors:
  • Stuart Ozer;Jim Gray;Alex Szalay;Andreas Terzis;Razvan Musaloiu-E;Katalin Szlavecz;Randal Burns;Josh Cogan

  • Affiliations:
  • Microsoft Research;Microsoft Research;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University

  • Venue:
  • Proceedings of the 4th international conference on Embedded networked sensor systems
  • Year:
  • 2006

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Abstract

Science is increasingly driven by data collected automatically from arrays of inexpensive sensors. The collected data volumes require a different approach from the scientists' current Excel spreadsheet storage and analysis model. Spreadsheets work well for small data sets; but scientists want high level summaries of their data for various statistical analyses without sacrificing the ability to drill down to every bit of the raw data. This demonstration describes our prototype data analysis system that is suitable for browsing and visualization - like a spreadsheet - but scalable to much larger data sets.