combined, to create IoT platforms that facilitate publishing, consuming, and analyzing data, within closed and open ecosystems. Taking into account the way that
IoT ecosystems are realized, a number of challenges can be identified. Among them
of definite importance are (but this list is, obviously, not exhaustive): (i) How to
provide common representation and/or shared understanding of data that will
enable analysis across (systematically growing) ecosystems? (ii) How to build
ecosystems based on data flows? (iii) How to track data provenance? (iv) How to
ensure/manage trust? (v) How to search for things/data within ecosystems?
(vi) How to store data and assure their quality?
Semantic technologies are often considered among possible ways of addressing
these (and other, related) questions. More precisely, in academic research and
industrial practice, semantic technologies materialize in the following contexts (this
list is, also, not exhaustive, but indicates the breadth of scope of semantic technology
usability): (i) representation of artifacts in IoT ecosystems and IoT networks,
(ii) providing interoperability between heterogenous IoT artifacts, (ii) representation
of provenance information, enabling provenance tracking, trust establishment, and
quality assessment, (iv) semantic search, enabling flexible access to data originating
in different places across the ecosystem, (v) flexible storage of heterogenous data.
Finally, Semantic Web, Web of Things, and Linked Open Data are architectural
paradigms, with which the aforementioned solutions are to be integrated, to provide
production-ready deployments.
Nevertheless, even though we can observe a systematic uptake of solutions
utilizing semantic technologies, in the IoT domain and across the Internet, the total
number of actual deployments is not large enough to provide a real-world grounded
guidance and best practices to follow. This provides the context for this book,
which aims at presenting the current trends in application of semantic technologies
in the IoT domain (and closely related areas, such as Semantic Web or Web of
Things) and explores enablers that they provide. Moreover, descriptions of real-life
use cases, where semantic technologies have been adopted, are included.
The book is divided into four parts and consists of 18 chapters. The first part has
five chapters and provides fundamentals that can help understand the remaining
parts of the book. The second part deals with IoT data and interoperability and
consists of six chapters. The third and fourth parts are devoted to domain-specific
and problem-specific applications, which are addressed, in seven chapters. Let us
now, briefly, summarize the content of each part.
The first part starts from the chapter by Angelos Chatzimichail, Evangelos
Stathopoulos, Dimos Ntioudis, Athina Tsanousa, Maria Rousi, Athanasios
Mavropoulos, George Meditskos, Stefanos Vrochidis, and Ioannis Kompatsiaris.
They provide an overview of the current trends in application of semantic technologies in the IoT domain, presenting practical applications in multiple domains,
such as health care, disaster management, public events, precision agriculture,
intelligent transportation, building and infrastructure management. Additionally,
research studies on semantic reasoning, aggregation, fusion, and interpretation that
aim to intelligently process and ingest sensor data are provided. Moreover, authors
elaborate on how semantic technologies can overcome the limitations of device and
vi
Preface
IoT ecosystems are realized, a number of challenges can be identified. Among them
of definite importance are (but this list is, obviously, not exhaustive): (i) How to
provide common representation and/or shared understanding of data that will
enable analysis across (systematically growing) ecosystems? (ii) How to build
ecosystems based on data flows? (iii) How to track data provenance? (iv) How to
ensure/manage trust? (v) How to search for things/data within ecosystems?
(vi) How to store data and assure their quality?
Semantic technologies are often considered among possible ways of addressing
these (and other, related) questions. More precisely, in academic research and
industrial practice, semantic technologies materialize in the following contexts (this
list is, also, not exhaustive, but indicates the breadth of scope of semantic technology
usability): (i) representation of artifacts in IoT ecosystems and IoT networks,
(ii) providing interoperability between heterogenous IoT artifacts, (ii) representation
of provenance information, enabling provenance tracking, trust establishment, and
quality assessment, (iv) semantic search, enabling flexible access to data originating
in different places across the ecosystem, (v) flexible storage of heterogenous data.
Finally, Semantic Web, Web of Things, and Linked Open Data are architectural
paradigms, with which the aforementioned solutions are to be integrated, to provide
production-ready deployments.
Nevertheless, even though we can observe a systematic uptake of solutions
utilizing semantic technologies, in the IoT domain and across the Internet, the total
number of actual deployments is not large enough to provide a real-world grounded
guidance and best practices to follow. This provides the context for this book,
which aims at presenting the current trends in application of semantic technologies
in the IoT domain (and closely related areas, such as Semantic Web or Web of
Things) and explores enablers that they provide. Moreover, descriptions of real-life
use cases, where semantic technologies have been adopted, are included.
The book is divided into four parts and consists of 18 chapters. The first part has
five chapters and provides fundamentals that can help understand the remaining
parts of the book. The second part deals with IoT data and interoperability and
consists of six chapters. The third and fourth parts are devoted to domain-specific
and problem-specific applications, which are addressed, in seven chapters. Let us
now, briefly, summarize the content of each part.
The first part starts from the chapter by Angelos Chatzimichail, Evangelos
Stathopoulos, Dimos Ntioudis, Athina Tsanousa, Maria Rousi, Athanasios
Mavropoulos, George Meditskos, Stefanos Vrochidis, and Ioannis Kompatsiaris.
They provide an overview of the current trends in application of semantic technologies in the IoT domain, presenting practical applications in multiple domains,
such as health care, disaster management, public events, precision agriculture,
intelligent transportation, building and infrastructure management. Additionally,
research studies on semantic reasoning, aggregation, fusion, and interpretation that
aim to intelligently process and ingest sensor data are provided. Moreover, authors
elaborate on how semantic technologies can overcome the limitations of device and
vi
Preface