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Internet of Things (IoT)
• maxCardinality: A maxCardinality one restriction is termed a functional or
distinctive property. That is, if a maxCardinality of one is declared on a property
with regard to a class, then any instance of that class will be associated with at the
most one individual by that property.
In OWL, properties are characterized consistent with individuals, whether or not they
relate to individuals (object properties) or to data-type properties. OWL uses most of the
intrinsic XML Schema data types.
13.2.3.3 Incremental Language Description of OWL DL and OWL FULL
OWL FULL and OWL DL have the same vocabulary while OWL DL has some restrictions. Furthermore, OWL DL properties can be DatatypeProperties or ObjectProperties.
ObjectProperties are relations between instances of two classes while DatatypeProperties
are relations between instances of classes, RDF literals, and XML Schema data types.
The OWL DL and OWL Full vocabulary that extends the constructions of OWL Lite are
described below.
• oneOf: (enumerated classes): Classes can be designated by enumeration of a variety of individuals. The class members are exactly the set of enumerated individuals; no more, no less. For example, the class of Sensor_Type for a sensor network
can be described by simply enumerating the individuals as UV sensors, touch
sensors, humid sensors, pressure sensors, thermal sensors, etc.
• hasValue: Certain individual values can be associated for a property, also sometimes referred to as property values. For example, instances of the class of
Chemical_sensors can be characterized as those sensors that have gas as a value
of their chemical component. (The chemical component value, gas, is an instance
of the class of chemical_components.)
• disjointWith: Classes can be disjoint. For instance, Analog_sensors and Digital_
sensors can be considered as disjoint classes. So a reasoner can infer an inconsistency when an individual is stated to be an instance of both and similarly a
reasoner can reason out that if sensor_A is an instance of Analog_sensor, then A
cannot be an instance of Digital_sensor.
• complementOf, unionOf, intersectionOf: OWL DL allows Boolean combinations of classes and restrictions—complementOf, unionOf, and intersectionOf.
For example, using complementOf, we could state that analog sensors are not digital sensors and using unionOf, we can state that a class contains sensors that are
either Analog_sensors or Digital_sensors.
• minCardinality, maxCardinality, cardinality: FULL OWL allows cardinality
statements for arbitrary positive integers, while in OWL Lite, cardinalities are
limited to at least, at most, or exactly 1 or 0.
13.3 Existing Standardizations in IoT Semantics
Semantic sensor networks work on the interoperability of physical sensor networks to ease
the sensor discovery. Further, they focus on semantically annotating sensor information to
Internet of Things (IoT)
• maxCardinality: A maxCardinality one restriction is termed a functional or
distinctive property. That is, if a maxCardinality of one is declared on a property
with regard to a class, then any instance of that class will be associated with at the
most one individual by that property.
In OWL, properties are characterized consistent with individuals, whether or not they
relate to individuals (object properties) or to data-type properties. OWL uses most of the
intrinsic XML Schema data types.
13.2.3.3 Incremental Language Description of OWL DL and OWL FULL
OWL FULL and OWL DL have the same vocabulary while OWL DL has some restrictions. Furthermore, OWL DL properties can be DatatypeProperties or ObjectProperties.
ObjectProperties are relations between instances of two classes while DatatypeProperties
are relations between instances of classes, RDF literals, and XML Schema data types.
The OWL DL and OWL Full vocabulary that extends the constructions of OWL Lite are
described below.
• oneOf: (enumerated classes): Classes can be designated by enumeration of a variety of individuals. The class members are exactly the set of enumerated individuals; no more, no less. For example, the class of Sensor_Type for a sensor network
can be described by simply enumerating the individuals as UV sensors, touch
sensors, humid sensors, pressure sensors, thermal sensors, etc.
• hasValue: Certain individual values can be associated for a property, also sometimes referred to as property values. For example, instances of the class of
Chemical_sensors can be characterized as those sensors that have gas as a value
of their chemical component. (The chemical component value, gas, is an instance
of the class of chemical_components.)
• disjointWith: Classes can be disjoint. For instance, Analog_sensors and Digital_
sensors can be considered as disjoint classes. So a reasoner can infer an inconsistency when an individual is stated to be an instance of both and similarly a
reasoner can reason out that if sensor_A is an instance of Analog_sensor, then A
cannot be an instance of Digital_sensor.
• complementOf, unionOf, intersectionOf: OWL DL allows Boolean combinations of classes and restrictions—complementOf, unionOf, and intersectionOf.
For example, using complementOf, we could state that analog sensors are not digital sensors and using unionOf, we can state that a class contains sensors that are
either Analog_sensors or Digital_sensors.
• minCardinality, maxCardinality, cardinality: FULL OWL allows cardinality
statements for arbitrary positive integers, while in OWL Lite, cardinalities are
limited to at least, at most, or exactly 1 or 0.
13.3 Existing Standardizations in IoT Semantics
Semantic sensor networks work on the interoperability of physical sensor networks to ease
the sensor discovery. Further, they focus on semantically annotating sensor information to