Water quality agencies at many levels (local, state and national) deploy water quality sensors and
collect continuous data. Some agencies already make their data available publicly via web
services. However, unless these data providers and available data sets are known to the individual
seeking data, this information can be difficult to discover and access. The purpose of U.S. EPA’s
Watersheds-based Monitoring and Interoperable Data Platforms project was to pilot the
development of a centralized catalog for discovering sensor data. This could provide a single
portal, where participants could register their sensors, and be included in data searches based on
parameters collected or geographic attributes.
This project centered around three main components:
- Developing a metadata catalog and associated web services.
- Aiding identified partner agencies in making data from their deployed sensors available
through web services.
- Building a web-based data discovery tool that illustrates the capabilities of the catalog
The project features multi-entity collaboration, and seeks to leverage the talents and assets of
several federal agencies (U.S. EPA, U.S. Geological Survey, U.S. Army Corps of Engineers),
various U.S. EPA offices and regions, and four states, as well as interested commercial entities.
To make useful water quality data available as widely and quickly as possible, the team has
committed to using open data standards wherever possible and to leveraging successful existing
approaches. For example, the team now is evaluating the Sensor Observation Service standard
developed by the Open Geospatial Consortium, an international nonprofit organization.
The team worked with water quality data providers of all levels (federal, state, tribal, and local) in two watersheds in Ohio and New Jersey to demonstrate the seamless sharing of sensor data in a common format across multiple platforms. The IWN data discovery tool, Currents, was released and tested, and the map-based interface underwent a six-month evaluation period and iterative releases. The team exceeded its partner participation goal to have eight partners with 15,678 sensors.
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