© 2021

Semantic IoT: Theory and Applications

Interoperability, Provenance and Beyond

  • Rajiv Pandey
  • Marcin Paprzycki
  • Nidhi Srivastava
  • Subhash Bhalla
  • Katarzyna Wasielewska-Michniewska

Part of the Studies in Computational Intelligence book series (SCI, volume 941)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Angelos Chatzimichail, Evangelos Stathopoulos, Dimos Ntioudis, Athina Tsanousa, Maria Rousi, Athanasios Mavropoulos et al.
      Pages 3-33
    3. Jayashree R. Prasad, Priya M. Shelke, Rajesh S. Prasad
      Pages 35-57
    4. Reinaldo Padilha França, Ana Carolina Borges Monteiro, Rangel Arthur, Yuzo Iano
      Pages 59-79
    5. Hemanta Kumar Palo
      Pages 81-102
    6. Rajiv Pandey, Mrinal Pande
      Pages 103-129
  3. IoT Data and Interoperability

    1. Front Matter
      Pages 131-131
    2. Arunima Sharma, Ramesh Babu Battula
      Pages 133-159
    3. Gianfranco E. Modoni, Marco Sacco
      Pages 193-206
    4. Vitalina Babenko, Igor Shostak, Mariia Danova, Olena Feoktystova
      Pages 207-228
    5. Beniamino Di Martino, Antonio Esposito
      Pages 229-244
  4. Domain-Specific Applications

    1. Front Matter
      Pages 263-263
    2. Mahda Noura, Amélie Gyrard, Benjamin Klotz, Raphael Troncy, Soumya Kanti Datta, Martin Gaedke
      Pages 303-321
    3. Regel Gonzalez-Usach, Matilde Julian, Manuel Esteve, Carlos E. Palau
      Pages 323-346
    4. Gennady Chuiko, Yaroslav Krainyk, Olga Dvornik, Yevhen Darnapuk
      Pages 347-362
  5. Problem-Specific Applications

    1. Front Matter
      Pages 363-363

About this book


This book is focused on an emerging area, i.e. combination of IoT and semantic technologies, which should enable breaking the silos of local and/or domain-specific IoT deployments.

Taking into account the way that IoT ecosystems are realized, several challenges can be identified. Among them of definite importance are (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 its quality?

Semantic technologies are often considered among the possible ways of addressing these (and other, related) questions. More precisely, in academic research and in 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 artefacts in IoT ecosystems and IoT networks, (ii) providing interoperability between heterogeneous IoT artefacts, (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 heterogeneous 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.



Semantic IoT IOT & Big Data Web Semantic Data Representation Semantic Networks Interoperability Provenance

Editors and affiliations

  1. 1.Amity Institute of Information TechnologyAmity University Uttar Pradesh Lucknow CampusLucknowIndia
  2. 2.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  3. 3.Amity Institute of Information TechnologyAmity University Uttar Pradesh Lucknow CampusLucknowIndia
  4. 4.Database System LaboratoryUniversity of AizuAizu-WakamatsuJapan
  5. 5.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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