VizTree: a tool for visually mining and monitoring massive time series databases

  • Authors:

  • Jessica Lin;Eamonn Keogh;Stefano Lonardi;Jeffrey P. Lankford;Daonna M. Nystrom

  • Affiliations:

  • Computer Science & Engineering Department, University of California, Riverside, Riverside, CA;Computer Science & Engineering Department, University of California, Riverside, Riverside, CA;Computer Science & Engineering Department, University of California, Riverside, Riverside, CA;The Aerospace Corporation, El Segundo, CA;The Aerospace Corporation, El Segundo, CA

  • Venue:
  • VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
  • Year:
  • 2004

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Abstract

Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spite of a fault, or a false negative, stopping a potentially successful launch, can be measured in the tens of millions of dollars, not including the cost in morale and other more intangible detriments. The Aerospace Corporation is responsible for providing engineering assessments critical to the go/no-go decision for every Department of Defense (DoD) launch vehicle. These assessments are made by constantly monitoring streaming telemetry data in the hours before launch. For this demonstration, we will introduce VizTree, a novel time-series visualization tool to aid the Aerospace analysts who must make these engineering assessments. VizTree was developed at the University of California, Riverside and is unique in that the same tool is used for mining archival data and monitoring incoming live telemetry. Unlike other time series visualization tools, VizTree can scale to very large databases, giving it the potential to be a generally useful data mining and database tool.