Improvements in Data Quality, Integration and Reliability: New Developments at the IRIS DMC

Abstract

Abstract. With the support of the US National Science Foundation (NSF) and on behalf of the international seismological community, IRIS developed a Data Management Center (DMC; Ahern, 2003) that has for decades acted as a primary resource for seismic networks wishing to make their data broadly available, as well as a significant point of access for researchers and monitoring agencies worldwide that wish to access high quality data for a variety of purposes. Recently IRIS has taken significant new steps to improve the quality of and access to the services of the IRIS DMC. This paper highlights some of the current new efforts being undertaken by IRIS. The primary topics include (1) steps to improve reliability and consistency of access to IRIS data resources, (2) a comprehensive new approach to assessing the quality of seismological and other data, (3) working with international partners to federate seismological data access services, and finally (4) extensions of the federated concept to extend data access to data from other geoscience domains.

Surface wave imaging of the weakly extended Malawi Rift from ambient-noise and teleseismic Rayleigh waves from onshore and lake-bottom seismometers

“…The dashed grey lines indicate the Peterson high and low noise models. Spectra were acquired from the Modular Utility for STAtistical kNowledge Gathering (MUSTANG) system (Ahern et al 2015). The spectra are shown for the (a) vertical component (HHZ), (b) horizontal component 1 (HH1) and (c) horizontal component 2 (HH2).…”

WFCatalog: A catalogue for seismological waveform data

“…We provide a reference implementation which is adopted across EIDA data centres. This implementation builds on top of a popular community-driven Python library, namely ObsPy , and it takes MiniSEED (Ahern et al, 2009) data as input. We chose MiniSEED as it is by far the most used format in EIDA data centres and for compatibility with the fdsnws-dataselect web service.…”

“…The computation of the quality metrics presented several challenges. In order to align the theoretical definitions with the computation, we had to overcome several issues mainly introduced by the SEED (Ahern et al, 2009) data format and by the data archival system. Adaptations allowed us to obtain thorough and accurate results conforming with the definitions.…”

Research on Application of High - efficiency Data Mining to Electric Power Data under Big Data

“…In general, big data refers to can't within tolerable time with traditional information technology and the hardware and software tools to perceive, acquisition, management, data collection, processing and services [3]. According to the characteristics of the electric power industry, electric power big data mainly comes from electric power production, management, operation, smart grid, the three areas.…”