Data is the new gold in the 21st century. Artificial intelligence (AI), data visualization, and knowledge engineering are important fields that provide concepts, techniques, and methods that help draw insights from data, especially when working with sets at a scale that would be humanly difficult to comprehend. The trends, outliers, and patterns gleaned from these insights help organizations support data-driven decision-making, generating top-line value. Data visualization and knowledge engineering is an edited collection of chapters by experts working in these disciplines.

The book’s 13 chapters are not necessarily organized in any particular order. Each chapter is a self-contained case study from a diverse set of domains that includes software engineering, multimedia entertainment, imaging, text processing, semantic web, sustainability, web navigation, natural language processing, and data visualization.

The first chapter, from the software engineering domain, discusses “cross projects defect prediction” using public defect data repositories. The second chapter focuses on multimedia entertainment and describes a recommendation system that helps users select from multiple equally competitive choices. The third chapter describes the challenges related to image collection summarization and major research efforts to solve this problem. Chapter 4 includes details on deep learning approaches for the semantic segmentation of satellite images. Chapter 5 is “A Deep Dive into Supervised Extractive and Abstractive Summarization from Text.” Chapter 6 is on the semantic web and how it integrates data from disparate sources, making it more user friendly. Chapter 7 outlines how AI and machine learning, especially deep learning, can be leveraged for sustainable development that balances resource utilization with continued economic development. The focus of chapter 8 is the application of deep learning in medical imaging. Chapter 9 discusses the use of visualization in web navigation mining. Chapter 10 describes named entity recognition for the Hindi language. Chapter 11 provides techniques, models, and a taxonomy for data visualization. Chapter 12 covers visualization techniques in data mining. Chapter 13 describes a question-answering system for the legal domain that helps retrieve suitable documentation for law-related queries.

Many chapters are of an applied nature and do not necessarily cover advances in the topics discussed. In several instances, experimental results are presented after applying AI, data visualization, and knowledge engineering techniques, and then analyzed for their significance. This book does not offer any fresh perspectives, and researchers looking for new ideas will be disappointed. Those interested in a broad overview of the field may find relevant information, but the lack of structure and systematic treatment of the subject matter makes the book difficult to navigate.