MUSTANG: A Community-Facing Web Service to Improve Seismic Data Quality Awareness Through Metrics

Thursday, 18 December 2014
Mary E. Templeton, Timothy Keith Ahern, Robert E Casey, Gillian Sharer, Bruce Weertman and Sarah Ashmore, IRIS Data Management Center, Seattle, WA, United States
IRIS DMC is engaged in a new effort to provide broad and deep visibility into the quality of data and metadata found in its terabyte-scale geophysical data archive. Taking advantage of large and fast disk capacity, modern advances in open database technologies, and nimble provisioning of virtual machine resources, we are creating an openly accessible treasure trove of data measurements for scientists and the general public to utilize in providing new insights into the quality of this data.

We have branded this statistical gathering system MUSTANG, and have constructed it as a component of the web services suite that IRIS DMC offers. MUSTANG measures over forty data metrics addressing issues with archive status, data statistics and continuity, signal anomalies, noise analysis, metadata checks, and station state of health. These metrics could potentially be used both by network operators to diagnose station problems and by data users to sort suitable data from unreliable or unusable data.

Our poster details what MUSTANG is, how users can access it, what measurements they can find, and how MUSTANG fits into the IRIS DMC's data access ecosystem. Progress in data processing, approaches to data visualization, and case studies of MUSTANG's use for quality assurance will be presented. We want to illustrate what is possible with data quality assurance, the need for data quality assurance, and how the seismic community will benefit from this freely available analytics service.