MUSTANG : Data Quality Assurance Infrastructure Encouraging Cooperation Across Seismological Communities

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Gillian Sharer1, Robert E Casey1, Mary E. Templeton1, Timothy Keith Ahern1, Bruce Weertman2 and Laura Keyson1, (1)Incorporated Research Institutions for Seismology, Seattle, WA, United States, (2)IRIS Data Services, IRIS DMC, Seattle, WA, United States
One of the key challenges of curating environmental data is the need for trustworthy quality assurance. Researchers and other data users need to be reasonably confident that the condition of the data is suitable for their specific uses and that the data is accurately reflected by its metadata. The IRIS Data Management Center (DMC) maintains a large and expanding archive of seismic data, for which the task of quality assurance is complex and evolving. To that end, IRIS has recently completed its introduction of MUSTANG, a service oriented infrastructure for seismic data quality assessment. MUSTANG provides approximately 50 quality-related metrics and Power Spectral Density measurements freely accessible to the research community through web service interfaces. We are in the process of consistently applying these measurements across our entire archive for all past and current seismic time series data and implementing algorithms to update these measurements in response to metadata or data changes.

In this presentation we will show how value added to data archived at the IRIS DMC by MUSTANG data quality metrics is providing incentive for seismic network operators to share data across regional and geopolitical borders. In a 2014 Data Management Workshop in Bogotá, Colombia, 32 regional seismic networks in Latin America chose to share data from their networks for a one year period so that data quality metrics could be calculated, that will result in a paper coauthored by all participants. In addition, the MUSTANG metrics for these networks are reviewed by a DMC analyst and summarized in monthly network quality reports that can be used to improve future data quality. As a result, more than 400 permanent stations from the region are becoming openly available. We will also present another feature of the MUSTANG system, namely its ability to incorporate data quality metrics from other Data Centers, thereby enhancing quality assurance cooperation throughout the earth science community.