Visualization Psychology

TRAMA

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.

SOMMARIO

ForewordPreface 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

AUTORE

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). Dr. Rita Borgo is Senior Lecturer in Data Visualization at the Informatics Department at King’s College London (KCL), Head of the Human Centred Computing research group and Deputy Director of the Centre for Urban Science and Progress (CUSP) - London. Her research focus is on Information Visualization and Visual Analytics with particular focus on the role of Human Factors in Visualization. Her research has followed an ambitious program of developing new data visualization techniques for interactive rendering and manipulation of large multi-dimensional and multivariate datasets. Novel in all aspects of the research is the aim at providing solutions that involve human in the loop of intelligent reasoning while reducing the burden of inspection of large complex data. Her research has been awarded supports from Royal Society, EPSRC and EU. She is currently championing the newly created Urban Living hub at KCL to increase impact of visualization within urban related challenges. Dr. Darren J. Edwards is a cognitive, health, and experimental psychology researcher at Swansea University (Senior Lecturer). He obtained his PhD (2010) in categorization and information processing of supervised and spontaneous stimuli tasks which included visual context effects. His research has explored information theories of cognition, particularly in the area of information reduction or unitization for visual route learning, simplicity, and categorization tasks. Darren has worked with computer science academics for several years, applying theories of psychology and cognition to areas such as data visualization on the perceptual orderability of visual channels and human-computer interaction. He has led a chapter as part of the lecture notes in computer science series, and most recently co-authored a chapter exploring the various ‘ism’ in psychology and visualisation. Darren is interested in how a new discipline of Visualization Psychology may be applicable to applied settings such as efficient visual displays of complex information in health care settings. Dr. Lace Padilla is an assistant professor in the Cognitive and Information Sciences department at the University of California Merced. She was awarded an NSF Postdoctoral Fellowship for work at Northwestern University. She received a PhD in Cognitive and Neural Sciences and an MFA in Design from the University of Utah. In 2018, she was awarded a Visionary Grant for research on Improving Trust in Uncertain Science funded by NASA. She has contributed significantly to research on decision making with visualizations, most recently with a review paper detailing a cognitive model for decision making with visualizations. Her empirical research utilizes displays of uncertainty, such as hurricane forecast maps, to understand how the brain represents, transforms, and reasons with visual information. She works collaboratively with visualization scientists, geographers, and anthropologists. In her spare time, she is a strong advocate for minoritized groups in STEM. The National Science Foundation appointed her as their 2017/2018 STEM ambassador for her outreach work, and she has received numerous awards for work with underserved populations. 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, data science, computer graphics, and HCI. He

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783031347375
• Dimensioni: 235 x 155 mm Ø 856 gr
• Formato: Copertina rigida
• Illustration Notes: XIX, 392 p. 1 illus.
• Pagine Arabe: 392
• Pagine Romane: xix