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Foundations of Data Visualization

  • Book
  • © 2020

Overview

Editors:
  1. Min Chen

    1. University of Oxford, Oxford, UK

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  2. Helwig Hauser

    1. Department of Informatics, University of Bergen, Bergen, Norway

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  3. Penny Rheingans

    1. University of Maryland, Baltimore County, Baltimore, USA

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  4. Gerik Scheuermann

    1. Institut für Informatik, Universität Leipzig, Leipzig, Germany

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  • Enriches readers’ broad appreciation of the connections from theoretical and mathematical research to empirical studies and application case studies
  • Stimulates readers’ insight into the scientific foundations of data visualization
  • Inspires readers to make ground-breaking contributions to the discipline of visualization

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Table of contents (21 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Theoretical Underpinnings of Data Visualization

    1. Front Matter

      Pages 1-4
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    2. The Fabric of Visualization

      • G. Elisabeta Marai, Torsten Möller
      Pages 5-14

    3. Visual Abstraction

      • Ivan Viola, Min Chen, Tobias Isenberg
      Pages 15-37

    4. Measures in Visualization Space

      • Fabian Bolte, Stefan Bruckner
      Pages 39-59

    5. Knowledge-Assisted Visualization and Guidance

      • Silvia Miksch, Heike Leitte, Min Chen
      Pages 61-85

    6. Mathematical Foundations in Visualization

      • Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang
      Pages 87-119

    7. Transformations, Mappings, and Data Summaries

      • Ross Whitaker, Ingrid Hotz
      Pages 121-157

  3. Empirical Studies in Visualization

    1. Front Matter

      Pages 159-160
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    2. A Survey of Variables Used in Empirical Studies for Visualization

      • Alfie Abdul-Rahman, Min Chen, David H. Laidlaw
      Pages 161-179

    3. Empirical Evaluations with Domain Experts

      • Krešimir Matković, Thomas Wischgoll, David H. Laidlaw
      Pages 181-194

    4. Evaluation of Visualization Systems with Long-Term Case Studies

      • Bernhard Preim, Alark Joshi
      Pages 195-208

    5. Vis4Vis: Visualization for (Empirical) Visualization Research

      • Daniel Weiskopf
      Pages 209-224

    6. “Isms” in Visualization

      • Min Chen, Darren J. Edwards
      Pages 225-241

    7. Open Challenges in Empirical Visualization Research

      • Caroline Ziemkiewicz, Min Chen, David H. Laidlaw, Bernhard Preim, Daniel Weiskopf
      Pages 243-252

  4. Collaboration with Domain Experts

    1. Front Matter

      Pages 253-254
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    2. Case Studies for Working with Domain Experts

      • Johanna Beyer, Charles Hansen, Mario Hlawitschka, Ingrid Hotz, Barbora Kozlikova, Gerik Scheuermann et al.
      Pages 255-278

    3. Collaborations Between Industry and University

      • Daniela Oelke, Ariane Sutor
      Pages 279-283

    4. Collaborating Successfully with Domain Experts

      • Mario Hlawitschka, Gerik Scheuermann, Christian Blecha, Marc Streit, Amitabh Varshney
      Pages 285-293

  5. Developing Visualizations for Broad Audiences

    1. Front Matter

      Pages 295-295
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Keywords

About this book

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.


Editors and Affiliations

  • University of Oxford, Oxford, UK

    Min Chen

  • Department of Informatics, University of Bergen, Bergen, Norway

    Helwig Hauser

  • University of Maryland, Baltimore County, Baltimore, USA

    Penny Rheingans

  • Institut für Informatik, Universität Leipzig, Leipzig, Germany

    Gerik Scheuermann

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