IRIS DMC Web Services

Services implementation: MUSTANGBETA

Request tools

Service interface Version Summary Return options

noise-pdf

v.1

Returns Probability Density Functions

  • Text – CSV
  • XML
  • Plot (PNG)

noise-psd

v.1

Returns Power Spectral Density estimates

  • Text – CSV
  • XML
  • Plot (PNG)

noise-mode-timeseries

v.1

Returns PDF Mode Timelines

  • Text – CSV
  • XML
  • Plot (PNG)

measurements

v.1

Returns measurements for metrics relating to station data quality

  • XML (default)
  • CSV
  • text

metrics

v.1

The metrics web service returns metric metadata in a variety of formats

  • XML
  • HTML
  • XSD

targets

v.1

The targets web service returns a list of targets for the given metric. Targets can be filtered.

  • Text

Welcome

Welcome to the MUSTANG data quality metrics web service home page. We are currently in the beta release stage, with the database being built and improved on a daily basis. This can be a good place to start navigating the features we have here. Each of the service links you see above can be navigated to to see more specific information.

Overview

The M odular U tility for STA tistical k N owledge G athering system is an IRIS project to bring data quality analysis services to data sited at IRIS DMC, covering the entirety of the data archive, all the way to present time. It 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.
  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 can allow for powerful visualization pipelines to be developed for clients.
  3. It is extensible: the metrics calculations are performed using open-source R utilities, within a framework that allows for sufficient testing of new metrics and then inclusion into the system. Already, a long list of measurements are available, and more are on the way.
  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 a given network.
  5. Metrics are up to date: a process in development will allow MUSTANG to recalculate metrics on conditions where data or metadata conditions have changed, allowing for processing of corrected data to show more accurate measurements.

Features

What you can expect from MUSTANG is the ability to:

  1. view basic statistics such as mean, max, and median values
  2. view event-oriented estimates such as signal to noise ratio
  3. (soon) gather power spectral density and probability density function values for noise analysis
  4. view correlation coefficients
  5. view dead channels and annotate channel up and channel down times
  6. find maximum STA/LTA values
  7. gather state of health and activity flag counts

MUSTANG can return measurements to you in XML, text, CSV, and JSON formats.

You can perform ordering by date, by station name, by metric, by value, and so on.

For more information about currently documented metrics, please consult the `metrics` service link above and go to the Help screen.

To begin querying for measurements, please go to the `measurements` service link and try using the `Builder` tool accessible in the top right corner. Once you are familiar with the syntax, you can craft your own URLs by hand and use a web browser or command line tool to access MUSTANG measurements.