Database Reference
In-Depth Information
tion needed for discovering sensors, locating sensor observations,
processing low level sensor observations, and listing taskable prop-
erties.
Transducer Model Language (TML):
These are standard models
and XML schema for describing transducers and supporting real-
time streaming of data to and from sensor systems.
Sensor Observation Service (SOS):
This is the standard Web ser-
vice interface for requesting, filtering, and retrieving observations
and sensor system information.
Sensor Alert Service (SAS):
This is the standard Web service in-
terface for publishing and subscribing to alerts from sensors.
Sensor Planning Service (SPS):
This is the standard Web service
interface for requesting user-driven acquisitions and observations.
Web Notification Services (WNS):
This is the standard Web ser-
vice interface for delivery of messages or alerts from
Sensor Alert
Service
and
Sensor Planing Services
.
We note that all of the above services are useful for different aspects of
sensor data processing, and this may be done in different ways based on
the underlying scenario. For example, the
discovery
of the appropriate
sensors is a critical task for the user, though it is not always easy to know
a-priori about the nature of the discovery that a user may request. For
example, a user may be interested in discovering physical sensors based
on specific criteria such as location, measurement type, semantic meta-
information etc., or they may be interested in specific sensor related
functionality such as alerting [57]. Either goal may be achieved with
an appropriate implementation of the SML module [21, 57]. Thus, the
specific design of each module will dictate the functionality which is
available in a given infrastructure.
The World Wide Web Consortium (W3C) has also initiated the
Se-
mantic Sensor Networks Incubator Group (SSN-XL)
to develop Seman-
tic Sensor Network Ontologies, which can model sensor devices, pro-
cesses, systems and observations. This ontology enables expressive rep-
resentation of sensors, sensor observations, and knowledge of the envi-
ronment. This is already being adopted widely by the sensor networking
community, and has resulted in improved management of sensor data on
the Web, involving annotation, integration, publishing, and search. In
the case of sensor data, the amounts of data are so large, that the seman-
tic annotation of the underlying data is extremely important in order to
enable effective discovery and search of the underlying resources. This
