Monitoring the performance of a geophysical data processing pipeline using financial analysis inspired tools

• Autores: William N. Junek, Charles A. Houchin, Joseph A. Wehlen III, Alan Poffenberger, Anne S. Henson
• Localización: Seismological Research Letters, ISSN 0895-0695, ISSN-e 1938-2057, Vol. 87, Nº. 5, 2016, págs. 1138-1142
• Idioma: inglés
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• Resumen

  • Routine monitoring of the United States National Data Center (US NDC) geophysical data processing system’s performance is critical for identifying potential or ongoing problems that may otherwise go unnoticed. Daily reviews of the US NDC system’s automated network and station processing results are conducted by a human analyst using an interactive web application constructed from a collection of open-source software. A key feature of this tool is its use of time-series visualization techniques typically employed by the financial industry to analyze stock market trends. These techniques allow the user to quickly visualize the relationship between multiple time-series datasets (e.g., automatic detections, background noise, and analyst-reviewed detections).

    This enables the identification of a variety of problems such as the influence of seasonal noise variations on automatic signal detectors or the effect software changes have on system performance over time. The tool empowers the user to make data-driven decisions when selecting the appropriate corrective action for solving a particular problem.