The Future of Seismic Data Quality Assurance at the IRIS DMC
Abstract:The IRIS Data Management Center (DMC) hosts a large and ever-growing archive of
data from seismic stations around the world. One of the challenges in maintaining this archive is the need for providing Quality Assurance (QA) on its contents so that the data can be most effectively used by the scientific community. In the past, IRIS has focussed its QA efforts on improving data quality for a targeted subset of seismic networks, most notably the Earthscope USArray Transportable Array and the Global Seismic Network (GSN). Now with the rollout of MUSTANG, the DMC's new automated data quality metrics system, we are embarking on an ambitious effort to bring QA to the entirety of the DMC seismic data archive.
Analysts at the DMC are in the process of developing improved techniques to find data problems, document significant issues, and communicate our results. Our initial efforts are directed at creating a prototype of a scalable QA process using GSN data and MUSTANG metrics. We will show how MUSTANG metrics, both as single measurements and aggregates of multiple measurements, can be used to quickly flag potential problems and demonstrate how analysts can use visualization tools to track changes in data quality at stations and across networks. Communication between IRIS, network operators, and data users will be crucial to the success of any QA effort. To that end, we are also improving our web presence with the aim of increasing data quality awareness within the seismological community and providing a place where people can report issues they encounter with either data or metrics measurements.