Data Visualization and Knowledge Engineering

Spotting Data Points with Artificial Intelligence

  • Jude Hemanth
  • Madhulika Bhatia
  • Oana Geman

Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 32)

Table of contents

  1. Front Matter
    Pages i-vi
  2. Lipika Goel, Sonam Gupta
    Pages 1-21
  3. Shilpi Aggarwal, Dipanjan Goswami, Madhurima Hooda, Amirta Chakravarty, Arpan Kar, Vasudha
    Pages 23-48
  4. Anurag Singh, Deepak Kumar Sharma
    Pages 49-78
  5. Manami Barthakur, Kandarpa Kumar Sarma
    Pages 79-107
  6. Abhinav Singh, Utsha Sinha, Deepak Kumar Sharma
    Pages 133-150
  7. Honey Jindal, Neetu Sardana, Raghav Mehta
    Pages 195-221
  8. Arti Jain, Devendra K. Tayal, Divakar Yadav, Anuja Arora
    Pages 223-248
  9. Shreyans Pathak, Shashwat Pathak
    Pages 249-271
  10. Rosy Madaan, Komal Kumar Bhatia
    Pages 273-298
  11. Aayushi Verma, Jorge Morato, Arti Jain, Anuja Arora
    Pages 299-319

About this book


This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge.
Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats.
Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role.
Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field.
Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.


Data Visualization Knowledge Engineering Knowledge Based System Abstract Data Types Spatial Data Exploration General Visualization

Editors and affiliations

  • Jude Hemanth
    • 1
  • Madhulika Bhatia
    • 2
  • Oana Geman
    • 3
  1. 1.Department of Electronics and Communication Engineering (ECE)Karunya UniversityCoimbatoreIndia
  2. 2.Amity UniversityNoidaIndia
  3. 3.Department of Electrical Engineering and Computer ScienceŞtefan cel Mare University of SuceavaSuceavaRomania

Bibliographic information