4
A. Chatzimichail et al.
1 Introduction
The era of the Internet of Things (IoT) is upon us, with a huge number of IoT
devices already in everybody lives. A large number of applications in Smart Cities,
E-health, Security and other domains are exploiting the IoT technologies, like sensors, smartphones and actuators. One of the most significant aspects of IoT is the
things interconnection providing an interconnected system of different services and
applications. Everyday huge amounts of data are being generated and these data provide extremely valuable knowledge databases. The IoT tries to estimate a situation
based on the data knowledge in order to enable services to make smart decisions.
However, several challenges arose with the existing IoT technologies regarding
the interoperability of those different IoT technologies since their data is based on
predetermined formats without following a catholic vocabulary to describe the interoperable data. The basic structure of the IoT is the Machine-to-Machine (M2M)
communication [1]. For example, the measurements of sensors are required to be
distributed and analyzed by other devices or sensors and not being human readable
without any kind of processing. Therefore, those measurements should be understandable from one machine to another. Although, towards the rendering capable of
global machine communication by autonomous information discovery and analysis,
it is mandatory to struct and group data respectively.
Semantic Web (SW) technologies have been widely used to interpret and integrate
data deriving from a plethoric variety of resources on the Web. The main objective
of the Semantic Web is the provision of a new form of content that is understandable
and can be edited by both humans and computers. IoT domain has recently adopted
several Semantic Web technologies in order to enhance the content of data and
interoperability [2]. This is achieved by virtualization IoT data based on reusable
vocabularies that can be interpreted by distinct software modules. This semantic
annotation employs various semantic web standards, such as RDF, RDFs and OWL
to construct intellectual models, like ontologies to describe different domain concepts
and the connections that exist among them. Through this way, the semantic annotation
transforms the human oriented Web to a machine-interpretable Web. Except for that,
semantic web provides several protocols and query languages, which can be deployed
to query and reason over RDF datasets to infer new knowledge from them.
The ubiquity of Web technologies renders them a viable solution for managing
data coming from things. The Internet of Things is transforming into Web of Things to
leverage the advantages of the Web. The Web Thing Model imposes software modules
that allow the things to easily integrate the Web (with JSON messages). Consequently,
the IoT systems can benefit through the representation and description of things and
their environments and through the semantic annotation of the data coming from
things, leading to better understand them.
The book chapter is organized as: On Sect. 2 Applications, Related Work and
Research Challenges in Semantic Web and IoT are presented. On Sect. 3 IoT knowledge Representation with Semantic Web technologies is analysed with more emphasis in Modelling sensors (Sect. 3.1), multimodal events and observations (Sect. 3.2)
A. Chatzimichail et al.
1 Introduction
The era of the Internet of Things (IoT) is upon us, with a huge number of IoT
devices already in everybody lives. A large number of applications in Smart Cities,
E-health, Security and other domains are exploiting the IoT technologies, like sensors, smartphones and actuators. One of the most significant aspects of IoT is the
things interconnection providing an interconnected system of different services and
applications. Everyday huge amounts of data are being generated and these data provide extremely valuable knowledge databases. The IoT tries to estimate a situation
based on the data knowledge in order to enable services to make smart decisions.
However, several challenges arose with the existing IoT technologies regarding
the interoperability of those different IoT technologies since their data is based on
predetermined formats without following a catholic vocabulary to describe the interoperable data. The basic structure of the IoT is the Machine-to-Machine (M2M)
communication [1]. For example, the measurements of sensors are required to be
distributed and analyzed by other devices or sensors and not being human readable
without any kind of processing. Therefore, those measurements should be understandable from one machine to another. Although, towards the rendering capable of
global machine communication by autonomous information discovery and analysis,
it is mandatory to struct and group data respectively.
Semantic Web (SW) technologies have been widely used to interpret and integrate
data deriving from a plethoric variety of resources on the Web. The main objective
of the Semantic Web is the provision of a new form of content that is understandable
and can be edited by both humans and computers. IoT domain has recently adopted
several Semantic Web technologies in order to enhance the content of data and
interoperability [2]. This is achieved by virtualization IoT data based on reusable
vocabularies that can be interpreted by distinct software modules. This semantic
annotation employs various semantic web standards, such as RDF, RDFs and OWL
to construct intellectual models, like ontologies to describe different domain concepts
and the connections that exist among them. Through this way, the semantic annotation
transforms the human oriented Web to a machine-interpretable Web. Except for that,
semantic web provides several protocols and query languages, which can be deployed
to query and reason over RDF datasets to infer new knowledge from them.
The ubiquity of Web technologies renders them a viable solution for managing
data coming from things. The Internet of Things is transforming into Web of Things to
leverage the advantages of the Web. The Web Thing Model imposes software modules
that allow the things to easily integrate the Web (with JSON messages). Consequently,
the IoT systems can benefit through the representation and description of things and
their environments and through the semantic annotation of the data coming from
things, leading to better understand them.
The book chapter is organized as: On Sect. 2 Applications, Related Work and
Research Challenges in Semantic Web and IoT are presented. On Sect. 3 IoT knowledge Representation with Semantic Web technologies is analysed with more emphasis in Modelling sensors (Sect. 3.1), multimodal events and observations (Sect. 3.2)