Data Quality Parameters and Web Services Facilitate User Access to Research-Ready Seismic Data
Abstract
IRIS Data Services has the mission of providing efficient access to a wide variety of seismic and related geoscience data to the user community. With our vast archive of freely available data, we recognize that there is a constant challenge to provide data to scientists and students that are of a consistently useful level of quality. To address this issue, we began by undertaking a comprehensive survey of the data and generating metrics measurements that provide estimates of data quality. These measurements can inform the scientist of the level of suitability of a given set of data for their scientific investigation. They also serve as a quality assurance check for network operators, who can act on this information to improve their current recording or mitigate issues with already recorded data and metadata. Following this effort, IRIS Data Services is moving forward to focus on providing tools for the scientist that make it easier to access data of a quality and characteristic that suits their investigation. Data that fulfill this criterion are termed "research-ready". In addition to filtering data by type, geographic location, proximity to events, and specific time ranges, we will offer the ability to filter data based on specific quality assessments. These include signal-to-noise ratio measurements, data continuity, timing quality, absence of channel cross-talk, and potentially many other factors. Our goal is to ensure that the user receives only the data that meets their specifications and will not require extensive review and culling after delivery. We will present the latest developments of the MUSTANG automated data quality system and introduce the Research-Ready Data Sets (RRDS) service. Together these two technologies serve as a data quality assurance ecosystem that will provide benefit to the scientific community by aiding efforts to readily find appropriate and suitable data for use in any number of objectives.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMIN41C1675T
- Keywords:
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- 1912 Data management;
- preservation;
- rescue;
- INFORMATICSDE: 1916 Data and information discovery;
- INFORMATICSDE: 1950 Metadata: Quality;
- INFORMATICSDE: 1990 Uncertainty;
- INFORMATICS