Interactive data visualization : foundations, techniques, and applications / Matthew Ward, Georges Grinstein, Daniel Keim.

Includes bibliographical references and index.

What Is Visualization? — History of Visualization — Relationship between Visualization and Other Fields — The Visualization Process — The Role of Cognition — Pseudocode Conventions — The Scatterplot — The Role of the User — Related Readings — Exercises — Projects —

Data Foundations —
Types of Data — Structure within and between Records — Data Preprocessing — Data Sets Used in This Book — Related Readings — Exercises — Projects —

Human Perception and Information Processing —
What Is Perception? — Physiology — Perceptual Processing — Perception in Visualization — Metrics — Cognition — Related Readings — Exercises — Projects —

Visualization Foundations —
The Visualization Process in Detail — Semiology of Graphical Symbols — The Eight Visual Variables.

An Updated Guide to the Visualisation of Data for Designers, Users, and Researchers:

Interactive Data Visualisation: Foundations, Techniques, and Applications, Second Edition offers the theory, detail, and practical tools required to design and build systems for visualising data. Presented in full colour, it introduces the essential terminology and concepts, discusses algorithmic and software engineering considerations, and outlines widely used techniques and higher-level algorithms. Complete source code is included to support implementation.

New in the Second Edition:

Additional recommended readings, exercises, and programming projects;

Improved figures, with many new illustrations;

A new chapter dedicated to techniques for time-oriented data.

This well-regarded text continues to examine the core elements of the visualisation process, from data through to the human observer. For developers, it provides guidance on designing effective visualisations informed by principles of human perception, graphical design, art, and usability. For practitioners, it illustrates how public and commercial visualisation systems can be applied to real-world problems across a variety of domains. For researchers, it surveys emerging technologies and current areas of innovation being explored in academic and industrial contexts.

Each chapter includes a range of exercises, from review questions to more open-ended problems that encourage readers to develop alternative approaches and extend their understanding. Programming projects further enable readers to move from basic algorithmic implementation to adapting and extending methods for more advanced applications.