Database Reference
In-Depth Information
technology that enables the advancement of sensor data mining applica-
tions in a variety of critical domains.
4.2.1 Ontologies.
Ontologies are at the heart of any semantic
technology, including the Semantic Sensor Web. An ontology, defined
formally as a specification of a conceptualization [43], is a mechanism
for knowledge sharing and reuse. In this chapter, we will illustrate two
important ontologies that are particularly relevant to the sensor data
domain. Our aim is to provide an understanding of ontologies and on-
tological frameworks per se, as well as highlight the utility of existing
ontologies for (further) developing practical sensor data applications.
Ontologies are essentially knowledge representation systems. Any knowl-
edge representation system must have mechanisms for (i) Representation
and (ii) Inference. In this context, we provide a brief introduction to two
important Semantic-Web ontology representation formalisms - namely
RDF
and
OWL
.
RDF
stands for the “
Resource Description Framework
”andisalan-
guage to describe resources [76]. A resource is literally any thing or
concept in the world. For instance, it could be a person, a place, a
restaurant entree etc. Each resource is uniquely identified by a
URI
,
which corresponds to a Unique Resource Identifier. What RDF enables
us to do is to:
Unambiguously describe a concept or a resource.
Specify how resources are related.
Do inferencing.
The building blocks of RDF are
triples
, where a triple is a 3-tuple of
the form
< subject,predicate,object >
where subject, predicate and
object are interpreted as in a natural language sentence. For instance
the triple representation of the sentence “
Washington DC is the capital
of the United States
” is illustrated in
Figure 12.1
.
RDF Triple:
<
URI1#
Washington DC
> <URI2#
capitalOf
> <URI3#
USA
>
subject
object
predicate
Figure 12.1.
RDF Triples
