Data Visualization Techniques
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Data Visualization Techniques
Data visualization techniques are a means to manipulate sampled and computed data for comprehensive display. Visualized data can be static or in motion, to provide visual explanations of algorithms or general information. This book draws on examples from a broad selection of subject areas, such as atmospheric sciences or biology, which deal with diverse data analysis and visualization techniques. The various visualization methodologies covered in this book also include moving images as well as static. It is an important source of information for computer graphics software engineers, graduates and researchers who work in the field of visualization techniques. Unique features in this book include: Details of data visualization techniques for scalar, vector and tensor field data and accompanying data structures Explanation of how to express visual images in computational terms and turn these into display, with minimum delay Methodology for "probing" a displayed visualization, in order to elicit more detail Collection of information from several interrelated subject areas in one volume Trends in Software - edited by Balachander Krishnamurthy of AT&T Research - is a sister publication of the journal Software: Practice and Experience
Interactive Data Visualization
An Updated Guide to the Visualization of Data for Designers, Users, and ResearchersInteractive Data Visualization: Foundations, Techniques, and Applications, Second Edition provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. In color throughout, it explains basic terminology
Linked Data Visualization
Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens. This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios. The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.