Visualization Psychology

This book designates Visualization Psychology as an interdisciplinary subject. The book contains literature reviews and experimental works that exemplify a range of open questions at this critical intersection. It also includes discourses that envision how the subject may be developed in the coming years and decades.

The field of visualization is a rich playground for discovering new knowledge in both visualization and psychology. As visualization techniques augment human cognition, these techniques must be developed and improved by building on theoretical, empirical and methodological knowledge from psychology. At the same time, visualization processes surface numerous phenomena about interactions between the human mind and digital entities, such as data, visual imagery, algorithms, and computer-generated predictions and recommendations. Visualization psychology is a new type of science in the making.

Foreword

Preface

Acknowledgements

Contents

Part I VIS Theories and Psychology

1 External Representation as a Framework for Visualization Psychology Amy Rae Fox and James D. Hollan

1.1 On The Shoulders of Giants

1.2 What We Represent

1.3 How We Represent

1.4 Why We Represent

1.5 A Conceptual Framework for Visualization Psychology

1.6 What Remains To Be Discovered References

 2 Explaining Cost-Benefit Trade-offs in Visualization using Psychological Theories and Information Theory Min Chen and Sine McDougall

2.1 Introduction 2.2 Representative Phenomena in Visualization

2.3 Representative Phenomena in Cognition

2.4 The Role of Theories of Attention in Visualization

2.5 The Role of Learning in Creating Cost-benefit Payoffs in Visualization

2.6 The Role of Long-term Memory and Comprehension in Explaining Cost Reductions in Visualization 2.7 Visualization Theory: Cost-Benefit Trade-Of

2.8 Discussions and Remarks References

3 Task Matters When Scanning Data Visualizations Laura E. Matzen, Kristin M. Divis, Deborah A. Cronin and Michael J. Haass

3.1 Introduction

3.2 TBD

3.3 Discussion Acknowledgments References

4 Perceptual biases in scatterplot interpretation Kristin M. Divis, Laura E. Matzen, Michael J. Haass, and Deborah A. Cronin

4.1 Introduction

4.2 Methods

4.3 Results

4.4 Discussion Acknowledgements References

5. Visualizing Uncertainty in Different Domains: Commonalities and Potential Impacts on Human Decision Making Laura E. Matzen, Alisa Rogers, Breannan Howell and Andrew T. Wilson

5.1  Introduction

5.2  Common Methods for Visualizing Uncertainty

5.3  Conveying the Presence and Amount of Variability in Data Sets

5.4  Conveying Temporal and Spatial Uncertainty

5.5  State Uncertainty, Evaluation of Risk, and Decision Making

5.6  Discussion Acknowledgements References

 Part II Topics in Psychology

6 The Cognitive Science of Graph Comprehension Amy Rae Fox

6.1 Introduction

6.2 Models and Theories of Graph Comprehension

6.3 An Integrative Model of Graph Comprehension

6.4 Methods in Graph Comprehension

6.5 Implications for Instruction and Design

6.6 What Remains to be Discovered References

7 Mental Models and Visualization Florian Windhager and Eva Mayr

7.1 Introduction

7.2 Mental Models

7.3 Coherence Techniques

7.4 Empirical Evidence References

8 Intuitions and False Impressions: Cognitive Frameworks for Decision-Making with Visualization Melanie Bancilhon, Lace Padilla and Alvitta Ottley

8.1 Understanding Decision-Making with Visualization

8.2 Theories of Decision-Making

8.3 Demystifying Cognitive Frameworks

8.4 Evaluation Methods: Visualization through a Dual Process Perspective

8.5 Applications and Implications

8.6 Conclusion References

9 Visualization Psychology: Tools to for Trust Rita Borgo and Darren J. Edwards

9.1 Introduction

9.2 Psychological Theories of Trust

9.3 Visualization as a Tool for Trust

9.4 Real World Applications

9.5 Visualization Psychology Applications for Trust References

10 Analysis of Sensemaking Strategies: Psychological Theories in Practice Margit Pohl, Johanna Doppler, P. Seidler, N. Kodagoda, and B. L. W. Wong

10.1 Introduction

10.2 TBD

10.3 ... References

Part III Branches in Psychology

11 A Survey on Visualization Onboarding and the Use of Learning Theories Christina Stoiber, Markus Wagner, Holger Stitz, Marc Streit, Margit Pohl and Wolfgang Aigner

11.1 Introduction

11.2 Related Work

11.3 State of the Art

11.4 Results

11.5 Discussion

11.6 Conclusion References

12 Adaptive Visualization of Health Information Based on Cognitive Psychology and Visualization Guidelines – Problem and Research Opportunities Dietrich Albert, Michael Bedek, Karl Horvath, Klaus Jeitler, Bettina Kubicek, Tobias Schreck, Thomas Semlitsch, Lin Shao, Andrea Siebenhofer

12.1 Introduction

12.2 Health Information, Visualization, and Cognitive Psychology

12.3 Vision: Adaptive Visual Health Information System

12.4 Conclusion References

13 Leveraging Conscientiousness-Based Preferences in Information Visualization Design Tomás Alves, Bárbara Ramalho, Daniel Gonçalves, Joana Henriques-Calado, and Sandra Gama

13.1 Introduction

13.2 Related Work

13.3 Assessment of Personality and Design Preferences

13.4 Evaluation

13.5 Results

 13.6 Conclusions References

14 Developing Effective Community Network Analysis Tools According to Visualization Psychology Darren J. Edwards and Min Chen

14.1 Introduction

14.2 Community Network Analysis: A Discussion from the Perspective of Visualization Psychology 14.3 Case Study 1

14.4 Case Study 2

14.5 Observations and Discussions

14.6 Conclusions References

15 Design Cognition in Data Visualization Paul Parsons

15.1 Introduction

15.2 TBD

15.3 ... References

Part V Subject Development

16 The Huge Variable Space in Empirical Studies for Visualization – A Challenge as well as an Opportunity for Visualization Psychology Min Chen, Alfie Abdul-Rahman, and David H. Laidlaw

16.1 Introduction

 16.2 Observations

16.3 Types of Psychology Papers

16.4 Progressive Approaches

16.5 Conclusions References

17 What We See and What We Get from Visualization: Eye Tracking Beyond Gaze Distributions and Scanpaths Kuno Kurzhals, Michael Burch, and Daniel Weiskopf

17.1 Introduction

17.2 Experiences

17.3 Visualization Psychology for Eye Tracking

17.4 Example Scenario: Metro Maps

17.5 Future Directions References

 18 The Disciplinary Landscape of Visualization Psychology Amy Rae Fox 

18.1 Introduction 18.2 TBD

18.3 ... References

19 Opportunities for Mutual Benefit in Visualization Psychology Danielle Albers Szafir

19.1 Introduction

19.2 TBD

19.3 ...

References

Index

Dr. Danielle Albers Szafir is an Assistant Professor in the Department of Computer Science and ATLAS Institute, and a Fellow in the Institute of Cognitive Science at the University of Colorado Boulder. Within the scope of this proposal, her research has explored how visualization design influences the patterns people perceive in data and how people use that data in decision making, offering actionable models of task performance and guidelines for creating visualizations for people with varying cognitive abilities. Results from this research have been integrated into leading tools such as D3 and Tableau and have received best paper awards at IEEE VIS and IS&T Color and Imaging. She was named to the Forbes 30 Under 30 Class of 2018 for Science. She received a B.S. in Computer Science at the University of Washington as a NASA Space Grant Scholar and a Ph.D. in Computer Sciences at the University of Wisconsin-Madison. Szafir is a cofounder of VisXVision, an organization aimed at bridging data visualization and perceptual psychology. In this role, she has guest edited a Journal of Vision Special Issue on vision and visualization and has helped organize VisXVision events at IEEE VIS (2017 panel, 2018 meet-up, and 2019 workshop) and at the Annual Meeting of the Vision Sciences Society (2017 meet-up, 2018 symposium, and 2019 workshop).