Overview

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

Full Product Details

Author:   Min Chen ,  Helwig Hauser ,  Penny Rheingans ,  Gerik Scheuermann
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Weight:   0.776kg
ISBN:  

9783030344436

ISBN 10:   3030344436
Pages:   389
Publication Date:   12 August 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Part I: Theoretical Underpinnings of Data Visualization.- The Fabric of Visualization.- Visual Abstraction.- Measures in Visualization Space.- Knowledge-Assisted Visualization and Guidance.- Mathematical Foundations in Visualizations.- Transformations, Mappings and Data Summaries.- Part II: Empirical Studies in Visualization.- A Survey of Variables Used in Empirical Studies for Visualization.- Empirical Evaluations with Domain Experts.- Evaluation of Visualization Systems with Long-term Case Studies.- Vis4Vis: Visualization for (Empirical) Visualization Research.- 'Isms' in Visualization.- Open Challenges in Empirical Visualization Research.- Part III: Collaboration with Domain Experts.- Case Studies for Working with Domain Experts.- Collaboration Between Industry and University.- Collaborating Successfully with Domain Experts.- Part IV: Developing Visualizations for Broad Audiences.- Reflections on Visualization for Broad Audiences.- Reaching Broad Audiences from a Research Institute Setting.- Reaching Broad Audiences from a Large Agency Setting.-  Reaching Broad Audiences from a Science Center or Museum Setting.-  Reaching Broad Audiences in an Educational Setting.- Challenges and Open Issues in Visualization for Broad Audiences

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Author Information

Dr. Min Chen developed his academic career in Wales between 1984 and 2011. He is currently the professor of scientific visualization at Oxford University and a fellow of Pembroke College. His research interests include visualization, computer graphics and human-computer interaction. He has co-authored over 200 publications, including his recent contributions in areas such as theory of visualization, video visualization, visual analytics, and perception and cognition in visualization. He has worked on a broad spectrum of interdisciplinary research topics, ranging from the sciences to sports, and from digital humanities to cybersecurity. His services to the research community include co-chairships of several major conferences, associate editor-in-chief of IEEE Transactions on Visualization and Computer Graphics, and editor-in-chief of Computer Graphics Forum. He is a fellow of British Computer Society, European Computer Graphics Association, and Learned Society of Wales. Helwig Hauser is professor in visualization at the University of Bergen, Norway, and the leader of a new Center for Data Science at the same University. Since his undergraduate and graduate studies at Vienna University of Technology, Austria, where he completed his PhD in the field of visualization, he is active as a researcher, PI, reviewer, editor, conference chair, committee member, etc., and as University teacher for over 20 years. His interests include visualization in general and the interactive visual exploration and analysis of data as well as visual data science in particular. With over 200 published papers (h-index > 50) and over 100 talks (keynotes, invited talks, etc.), he is recognized for his contributions to the field. For more information, see vis.UiB.no Penny Rheingans is Professor and Director of the School of Computing and Information Science at the University of Maine, USA. She received a Ph.D in Computer Science from the University of North Carolina, Chapel Hill and an AB in Computer Science from Harvard University. She has made seminal contributions to the areas of perceptual, illustrative, and uncertainty visualization. She was part of the Executive Committee of the Visualization Research Challenges report in 2006. She serves on the Board of Directors of the Computing Research Association (CRA). Her current research interests include the visualization of data important to increasing student success, computing pedagogy, perceptual and illustration issues in visualization, and learning analytics. Gerik Scheuermann is full professor at the Computer Science Department at Leipzig University, Germany. He studied mathematics at TU Kaiserslautern, Germany where he also got a PhD in visualization. For more than 20 years, he is an active researcher and teacher in visualization, with more than 250 peer-reviewed publications in the field. He has been paper chair for all major conferences in visualization, co-organized major conferences, and served as associated editor for major journals. His interests include most areas of visualization with a focus on topological, mathematical, and feature-based approaches and applications in engineering, medicine, bioinformatics, environmental sciences, and digital humanities. For more information see www.informatik.uni-leipzig.de/bsv

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