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Automated Data Quality Monitoring in the BABAR Online and Offline Systems

Edward Chen1, Scott Metzler1, Gregory Dubois-Felsmann1, Paul Bright-Thomas2
  1. California Institute of Technology
  2. University of Birmingham (UK)

Speaker: Edward Chen

  (for the BaBar computing group)
  An automatic monitoring system, developed for the BaBar experiment, allows for the evaluation of the contents of data quality diagnostic histograms produced in other components of the experiment. Both the data-acquisition system and the subsequent reconstruction make use of this facility.
  It supports periodic statistical tests of histogram bin contents against reference distributions, which may be other stored histograms or analytic distributions, and tests the parameters resulting from fits to histograms for consistency.
  Tests may be performed against entire one- and two-dimensional histograms, or on a bin-by-bin basis, a capability used for monitoring the appearance of single dead or hot channels in the detector. Fitting of histogram data to specified functional forms allows testing of parameters against reference values.
  Alarms of various sorts may be logged and sent to operators at consoles or to experts via e-mail, based on configurable tolerance thresholds for each test performed.
  Graphical tools are available for configuring and monitoring the system. The tools allow performance monitoring of the system and access to the data underlying the statistical tests.

Presentation:  PowerPoint Short Paper:  Adobe Acrobat pdf 

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