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The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture, with the core classes and properties defined using minimal axiomatization in a graph called SOSA (Sensor, Observation, Sample, and Actuator) supplemented with additional axiomatization and terms in further graphs. These allow SSN to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things.
The namespace for the core terms is http://www.w3.org/ns/sosa/.
The suggested prefix for the SOSA namespace is sosa.
The SOSA graph containing the core definitions is available at http://www.w3.org/ns/sosa/.
The SSN graph with the full axiomatization of the core terms is available at http://www.w3.org/ns/ssn/.
General Information
For OGC this is a Public Draft of a document prepared by the Spatial Data on the Web Working Group (SDWWG) — a joint W3C-OGC project (see charter). The document is prepared following W3C conventions. The document is released at this time to solicit public comment.
This section introduces the specifications for the modules that align SOSA and SSN to a variety of related ontologies and specifications.
Results of the wide review of SOSA and SSN is summarized here.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
In order to characterize a thing with a large extent, or which is not directly accessible, the usual
observational strategy is to obtain one or more samples. Observations can then be made more conveniently on
the samples, with the intention of characterizing the larger thing. This intentionality is captured using
the property sosa:isSampleOf.
In the following example, the ice core is a sample of the Antarctic ice sheet, and observations are made on the ice core.
A convenient side effect of this feature is that all observations related to the larger thing (the ice sheet) can be found, and then potentially joined together in a meta-analysis in order to characterize that.
An RDF file containing a graph corresponding to this example is available.
An RDF file containing a graph corresponding to this example is available.
This example shows how the conditions (temperature and humidity) in a room can be measured using one or more sensors. Each sensor observes the conditions in its immediate vicinity, and the values are then used to characterize the room.
In Room 145 one of the walls is external in the building, so there is expected to be a temperature gradient
across the room, and there are two sensors on different walls. In room 245 there is one sensor on the south
wall.
Each of these locations corresponds to a sosa:Sample of the entire room.
The wall also serves as a sosa:Platform on which the sensors are mounted.
An RDF file containing a graph corresponding to this example is available.
This example describes the IP68 Smart Sensor that and some of its capabilities and operating ranges. A specific IP68 Smart Sensor observes the air temperature, and its own battery state.
An RDF file containing a graph corresponding to this example is available.
The editors recognize the major contribution of the members of the original W3C Semantic Sensor Networks Incubator Group. The editors also gratefully acknowledge the contributions made to this document by all members of the SSN subgroup of the Spatial Data on the Web working group.
For this new edition of SSN, in addition to the contributors listed at the top of the document, the editors acknowledge the work of the editors of ISO 19156:2023 [[OMS]].
A full change-log is available on GitHub.