Visualization is the process of representing data, information, and knowledge in a visual form to support the tasks of exploration, confirmation, presentation, and understanding. This book is designed as a textbook for students, researchers, analysts, professionals, and designers of visualization techniques, tools, and systems. It covers the full spectrum of the field, including mathematical and analytical aspects, ranging from its foundations to human visual perception; from coded algorithms for different types of data, information and tasks to the design and evaluation of new visualization techniques.
Sample programs are provided as starting points for building one's own visualization tools. Numerous data sets have been made available that highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings are given for each chapter. The book concludes with an examination of several existing visualization systems and projections on the future of the field.
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Matthew O. Ward is professor of Computer Science at Worcester Polytechnic Institute (WPI) in Worcester, MA. He has been an associate editor for IEEE Transactions on Visualization and Computer Graphics since 2006. Georges Grinstein is professor of Computer Science at the University of Massachusetts Lowell. He is the head of the Bioinformatics Program and codirector of the Institute for Visualization and Perception Research and the Center for Biomolecular and Medical Informatics. Daniel Keim is full professor and head of the Information and Visualization and Data Analysis Research Group at the University of Konstanz, Germany. He has been an associate editor of Information Visualization since 2001 and knowledge and Information Systems since 2006.
Visualization is the process of representing data, information, and knowledge in a visual form. This book covers the full spectrum of the field, including mathematical and analytic aspects, ranging from its foundations to human visual perception; from coded algorithms for different types of data, information and tasks to the design and evaluation of new visualization techniques. Sample programs are provided as starting points for the reader to build their own visualization tools. Numerous data sets highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings accompany each chapter. The book concludes with an examination of several existing visualization systems and projections on the future of the field.
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