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Semantic IoT: Theory and Applications

Interoperability, Provenance and Beyond

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  • © 2021

Overview

Editors:
  1. Rajiv Pandey

    1. Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, India

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  2. Marcin Paprzycki

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  3. Nidhi Srivastava

    1. Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, India

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  4. Subhash Bhalla

    1. Database System Laboratory, University of Aizu, Aizu-Wakamatsu, Japan

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  5. Katarzyna Wasielewska-Michniewska

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  • Provides a guideline manual on how semantic technologies can be applied to solve real-life problems originating in the IoT domain
  • Focuses on semantic data representation and extended functionalities of the semantic layered
  • Discusses applications of the Internet of Everything concept in real-life solutions

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

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-xx
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  2. Fundamentals

    1. Front Matter

      Pages 1-1
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    2. Semantic Web and IoT

      • Angelos Chatzimichail, Evangelos Stathopoulos, Dimos Ntioudis, Athina Tsanousa, Maria Rousi, Athanasios Mavropoulos et al.
      Pages 3-33

    3. Semantic Web Technologies

      • Jayashree R. Prasad, Priya M. Shelke, Rajesh S. Prasad
      Pages 35-57

    4. A Look at Semantic Web Technology and the Potential Semantic Web Search in the Modern Era

      • Reinaldo Padilha França, Ana Carolina Borges Monteiro, Rangel Arthur, Yuzo Iano
      Pages 59-79

    5. Semantic IoT: The Key to Realizing IoT Value

      • Hemanta Kumar Palo
      Pages 81-102

    6. Provenance Data Models and Assertions: A Demonstrative Approach

      • Rajiv Pandey, Mrinal Pande
      Pages 103-129

  3. IoT Data and Interoperability

    1. Front Matter

      Pages 131-131
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    2. Need and Relevance of Common Vocabularies and Ontologies in IoT Domain

      • Arunima Sharma, Ramesh Babu Battula
      Pages 133-159

    3. PerfectO: An Online Toolkit for Improving Quality, Accessibility, and Classification of Domain-Based Ontologies

      • Amélie Gyrard, Ghislain Atemezing, Martin Serrano
      Pages 161-192

    4. Discovering Critical Factors Affecting RDF Stores Success

      • Gianfranco E. Modoni, Marco Sacco
      Pages 193-206

    5. Creation of Ontological Knowledge Bases in the Semantic Web by Analyzing Table Structures

      • Vitalina Babenko, Igor Shostak, Mariia Danova, Olena Feoktystova
      Pages 207-228

    6. Semantic Techniques to Support IoT Interoperability

      • Beniamino Di Martino, Antonio Esposito
      Pages 229-244

    7. Semantic IoT Interoperability and Data Analytics Using Machine Learning in Healthcare Sector

      • Pratiyush Guleria, Manu Sood
      Pages 245-262

  4. Domain-Specific Applications

    1. Front Matter

      Pages 263-263
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    2. SAGRO-Lite: A Light Weight Agent Based Semantic Model for the Internet of Things for Smart Agriculture in Developing Countries

      • Gaurav Kant Shankhdhar, Richa Sharma, Manuj Darbari
      Pages 265-302

    3. How to Understand Better “Smart Vehicle”? Knowledge Extraction for the Automotive Sector Using Web of Things

      • Mahda Noura, Amélie Gyrard, Benjamin Klotz, Raphael Troncy, Soumya Kanti Datta, Martin Gaedke
      Pages 303-321

    4. IoT Semantic Interoperability for Active and Healthy Ageing

      • Regel Gonzalez-Usach, Matilde Julian, Manuel Esteve, Carlos E. Palau
      Pages 323-346

    5. IoT in Provenance Management of Medical Data

      • Gennady Chuiko, Yaroslav Krainyk, Olga Dvornik, Yevhen Darnapuk
      Pages 347-362

  5. Problem-Specific Applications

    1. Front Matter

      Pages 363-363
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Keywords

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.

 

Editors and Affiliations

  • Amity Institute of Information Technology, Amity University Uttar Pradesh Lucknow Campus, Lucknow, India

    Rajiv Pandey, Nidhi Srivastava

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Marcin Paprzycki, Katarzyna Wasielewska-Michniewska

  • Database System Laboratory, University of Aizu, Aizu-Wakamatsu, Japan

    Subhash Bhalla

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