IRIS DMC Web Services

Services implementation: MUSTANG

Introduction

Welcome to the MUSTANG data quality metrics web service home page. MUSTANG has six service interfaces described in the request tools table below, each returning different information related to data quality. Each of the service links can be navigated to for more specific information and usage examples. If you scroll down past the table on this page, you will find a general overview of MUSTANG and contact information.

You can also visit our Quality Assurance home page to get the scoop on how we are using MUSTANG and the processes we use to analyze the quality of the data we receive. In addition to general quality assurance information, you can find MUSTANG tutorials and other helpful information here.

Metrics values on IRIS Data Services archive data are calculated daily for both recent data and for past archival data. Changes in data and metadata result in retasking of calculations within a reasonable frame of time. Our metrics code is constantly being improved, and the products of these improvements also make their way into MUSTANG.

Request tools

Service interface Version Summary Return options

measurements

v.1

The main MUSTANG web service returning measurements for metrics relating to station data quality.

  • XML (default)
  • text
  • CSV
  • JSON
  • JSONP

noise-psd

v.1

Returns Power Spectral Density estimates of seismic data and can generate aggregate plots.

  • Text – CSV
  • XML
  • Plot (PNG)

noise-pdf

v.1

Returns Probability Density Functions in frequency `bins` and can generate aggregate plots.

  • Text – CSV
  • XML
  • Plot (PNG)

noise-pdf-browser

v.1

Returns browseable views of Mustang PDF plots

  • Text
  • JSON
  • HTML

noise-mode-timeseries

v.1

Returns PDF Mode Timelines at select frequencies and can generate plots.

  • Text – CSV
  • Plot (PNG)
  • XML

metrics

v.1

The metrics web service returns a description of available metrics in a variety of formats

  • XML
  • HTML
  • XSD
  • JSON
  • JSONP

targets

v.1

The targets web service returns a list of stations and channels for a given metric.

  • Text

Overview

The Modular Utility for STAtistical kNowledge Gathering system is an IRIS effort to bring data quality analysis services to data archived at IRIS Data Services. We have a large number of statistical and noise measurements that are produced and stored in the MUSTANG database, and are made directly available to the user community with easy to use web service interfaces. We continually cover the entirety of the data archive and process data up to near real-time to provide the most current metrics possible.

MUSTANG is designed along the following principles:

  1. The system is modular: designed around discrete components (scheduler, calculator, storage and retrieval), MUSTANG has the ability to adapt and extend more readily than a single, monolithic system. The components can also be distributed among compute resources more easily, including geographic and cloud distribution.
  2. It is service oriented: data and metric access is performed via web services, keeping components of the system sufficiently decoupled from each other and adhering to established interfaces that are independent of implementation details. The power of programmatic access to metrics allows for powerful discovery and visualization pipelines to be developed for clients. Large scale automated analysis studies are also enabled via this web service access.
  3. It is extensible: a bulk of the metrics calculations are performed using open-source R utilities, within a framework that allows for sufficient testing of new metrics prior to inclusion in the production system. Continual improvements and additions are being made to this R code base, and we have begun to share this code with the public via CRAN.
  4. Data coverage is comprehensive: not satisfied to examine recently arrived data sets, MUSTANG`s mission is to regressively scour the data archives to provide a complete history of seismic data quality for all networks stored at IRIS Data Services.
  5. Metrics are up to date: MUSTANG recalculates metrics on conditions where data or metadata conditions have changed, allowing for processing of corrected data to show more accurate measurements. Recalculations are also performed as the result of metrics code corrections and improvements.

Features

What you can expect from MUSTANG is the ability to:

  1. view basic statistics such as mean, max, and median values
  2. collect data availability and data gap analysis
  3. find daily maximum STA/LTA values and the time of day of the maxima
  4. view event-oriented estimates such as signal to noise ratio as well as orientation and polarity checks
  5. look at power spectral density and probability density function plots for noise analysis
  6. view correlation coefficients, such as checks for cross talk and pressure effects
  7. view dead channels and note channel up times
  8. gather state of health and activity flag counts
  9. collect routine snapshots of real-time data latency

There are more than 40 separate metrics, and the list is growing. MUSTANG can return measurements to you in XML, text, CSV, and JSON formats using a REST-ful web service interface.

You can perform ordering by date, by station name, by metric, by value, and so on. You can also filter for specific conditions.

For more information about currently documented metrics, please consult the ‘measurements’ service link above and click on the red button. To begin querying for measurements, try using the ‘Builder’ tool accessible by clicking on the ‘hard hat’ button. Note that the noise metrics run in separate services, found at the listing at the top of this page. These are special in the additional features they provide specific to noise measurements.

Accessibility

MUSTANG is accessible from a web browser, command line, or a tool designed to talk to MUSTANG services. You can easily write your own if you are familiar with curl, wget, or an HTTP code library.

We are also working on, and interested in, client tools to make MUSTANG more accessible and useful. Examples are:

  1. MUSTANG Databrowserhttp://ds.iris.edu/mustang/databrowser
  2. LASSOhttp://lasso.iris.edu
  3. ISPAQComing Soon
  4. Noise PDF Browserhttp://service.iris.edu/mustang/noise-pdf-browser/1/
  5. Mustangular – (Univ. of Washington) – Coming Soon

Feedback and Discussion

The best means of fostering discussion about MUSTANG, or if you need to report an issue, is to sign up to our mustang-qa mailing list via the IRIS Data Services Message Center :

http://ds.iris.edu/message-center/topic/mustang-qa/