Moving Sensor Data Onto The Internet With SensorML

By Roland Piquepaille

According to this Sensors article, a new XML encoding scheme may make it possible for you to remotely discover, access, and use real-time data obtained directly from Web-resident sensors, instruments, and imaging devices.

Members of the Open GIS Consortium, Inc. (OGC), including NASA, the National Imaging and Mapping Agency, and EPA, are developing a standard XML encoding scheme for metadata describing sensors, sensor platforms, sensor tasking interfaces, and sensor-derived data.
The goal is to make all types of Web-resident devices discoverable and accessible using standard services and schemas. The Sensor Model Language (SensorML) is a vital component that provides sensor information necessary for discovery, processing, and georegistration of sensor observations.

Nice words, but where is the OGC really standing?

OGC is creating and testing a framework to maximize the discoverability and interoperability of sensor systems through standard Web-based services. Currently, the framework defines catalog services for discovering sensors and sensor data; collection services for accessing real-time or archived observation data; planning services for tasking sensors; and notification services for providing users the results of task requests or for alerting users of other services of observed phenomena of interest.

What are the possible applications?

Online catalogs of XML-based metadata for online sensors and data repositories constitute a revolution in the discovery and assessment of live data sources and archived data produced by sensors. Just as the Web is based on fairly simple standards, the sensor Web enablement framework is not particularly complicated. By describing sensors using SensorML, anyone can put sensors or sensor data online for others to find and use.

And because it's XML-based, it means all this data will easily be searchable.

For example, searching for particular kinds of sensors and data in a particular geographic region, with data collected within a particular time window, will be easy. This has significance for science, environmental monitoring, transportation management, public safety, disaster management, utilities operations, industrial controls, facilities management, and many other activities.

The Sensors's article contains more technical details about the technology. And if you're really interested, please visit the SensorML homepage.

Source: Mike Botts and Lance McKee, for Sensors, April 2003


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