THE INTERNET OF THINGS: A SURVEY FROM THE DATA-CENTRIC PERSPECTIVE - Managing and Mining Sensor Data - page 400

RDF(S) is used for defining classes, properties, hierarchies, collections,
reification, documentation and basic entailments for reasoning.
City
Rdfs:subClassOf
Capital City
<rdfs:Classrdf:ID=“someURI#CapitalCity”>
<rdfs:subClassOfrdf:resource=“someURI#City”/>
</rdfs:Class>
Figure 12.4. RDF Schema
For instance, let us say that we need to define a separate collection of
cities that are capital cities of any country. A capital city is of course a
sub-class of cities in general. This is represented in RDF(S) as shown in
Figure 12.4 .
OWL stands for Web Ontology Language [76]. This is another ontol-
ogy formalism that was developed to overcome the challenges with RDF.
RDF (and RDF Schema) are limited in that they do not provide ways
to represent constraints (such as domain or range constraints). Further,
transitive, inverse or closure properties cannot be represented in RDF(S).
Extending RDF(s) with the use of standards (XML, RDF etc.,), making
it easy to use and understand, and providing a Formal specification is
what results in OWL. Both RDF and OWL ontology formats have ex-
tensive developer community support in terms of the availability of tools
for ontology creation and authoring. An example is Protege [101], which
supports RDF and OWL formats, data storage and management stores
such as OpenSesame , for ecient storage and querying of data in RDF
or OWL formats. Furthermore, there is significant availability of actual
ontologies in a variety of domains in the RDF and OWL formats.
Specific ontologies: We now describe two such ontologies - SSN
[119] and SWEET [92] that are particularly relevant to sensor data se-
mantics. Both these ontologies have been created with the intention of
being generic and widely applicable for practical application tasks. SSN
is more sensor management centric, whereas SWEET has a particular