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E-raamat: Mobile Data Visualization

Edited by , Edited by , Edited by , Edited by (Microsoft Research, Redmond, Washington, USA)
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"Mobile Data Visualization is about facilitating access to and understanding of data on mobile devices. Wearable trackers, mobile phones, and tablets are used by millions of people each day to read weather maps, financial charts, or personal health meters. What is required to create effective visualizations for mobile devices? This book introduces key concepts of mobile data visualization and discusses opportunities and challenges from both research and practical perspectives. Mobile Data Visualization is the first book to provide an overview of how to effectively visualize, analyze, and communicate data on mobile devices. Drawing from the expertise, research, and experience of an international range of academics and practitioners from across the domainsof Visualization, Human Computer Interaction, and Ubiquitous Computing, the book explores the challenges of mobile visualization and explains how it differs from traditional data visualization. It highlights opportunities for reaching new audiences with engaging, interactive, and compelling mobile content. In nine chapters, this book presents interesting perspectives on mobile data visualization including: how to characterize and classify mobile visualizations; how to interact with them while on the go and with limited attention spans; how to adapt them to various mobile contexts; specific methods on how to design and evaluate them; reflections on privacy, ethical and other challenges, as well as an outlook to a future of ubiquitous visualization. This accessible book is a valuable and rich resource for visualization designers, practitioners, researchers, and students alike"--

Mobile Data Visualization is the first book to provide an overview of how to e­ffectively visualize, analyze, and communicate data on mobile devices. This accessible book is a valuable and rich resource for visualization designers, practitioners, researchers, and students alike.

Arvustused

Finally, the book I have wanted! An all-star team of researchers thoroughly survey the territory and show us the view up to and beyond the horizon. Ive been waiting for a book like Mobile Data Visualization to open the doors to many possibilities for future uses and devices.

--Ben Shneiderman, University of Maryland, College Park

Preface xi
Editors xvii
Contributors xix
Acknowledgments xxiii
Chapter 1 Introduction to Mobile Data Visualization
1(32)
Ricardo Langner
Lonni Besancon
Christopher Collins
Tim Dwyer
Petra Isenberg
Tobias Isenberg
Bongshin Lee
Charles Perin
Christian Tominski
1.1 Introduction
2(1)
1.2 Characterizing Dimensions
3(10)
1.2.1 Physical Data Display Size
4(1)
1.2.2 Data Display Mobility
5(2)
1.2.3 Data Source
7(1)
1.2.4 Reaction of Visualization to Display Movement
8(1)
1.2.5 Intended Viewing Timespan
9(1)
1.2.6 Visualization Interaction Complexity
10(1)
1.2.7 Intended Sharing
11(2)
1.3 Typical Examples Of Mobile Data Visualization
13(5)
1.3.1 Early Mobile Data Visualizations for PDAs
13(1)
1.3.2 Mobile Data Visualizations for Smartwatches
14(1)
1.3.3 Handheld Mobile Data Visualizations
15(2)
1.3.4 Mobile Data Visualizations on Tablet Devices
17(1)
1.4 Edge Cases Of Mobility-Related Visualizations
18(5)
1.4.1 Self-propelled Visualizations
18(1)
1.4.2 Micro-mobility for Visualization
19(2)
1.4.3 Mobile Data Visualizations in Multi-display Environments
21(1)
1.4.4 Large Movable Displays
22(1)
1.5 Summary And Reflections
23(10)
References
25(8)
Chapter 2 Responsive Visualization Design for Mobile Devices
33(34)
Tom Horak
Wolfgang Aigner
Matthew Brehmer
Alark Joshi
Christian Tominski
2.1 Context
34(2)
2.2 Responsive design vs. Responsive visualization design
36(1)
2.3 Factors Impacting Visualization Design On Mobile Devices
37(5)
2.3.1 Device Factors
38(1)
2.3.2 Usage Factors
39(1)
2.3.3 Environmental Factors
39(1)
2.3.4 Data Factors
40(1)
2.3.5 Human Factors
40(1)
2.3.6 Sensing and Inferring Multiple Factors
41(1)
2.4 Responsive Visualization Design Strategies
42(9)
2.4.1 Scale
43(2)
2.4.2 Aspect Ratio
45(1)
2.4.3 Layout
45(1)
2.4.4 Level of Detail
46(1)
2.4.5 Amount of Data
47(1)
2.4.6 Annotation and Guides
47(1)
2.4.7 Attentional Cues and Dynamic Guides
48(1)
2.4.8 Animation and Streaming Data
49(1)
2.4.9 Visual Encoding
49(1)
2.4.10 Interaction
50(1)
2.5 Challenges And Opportunities
51(4)
2.5.1 Develop Once, Deploy to Many
51(1)
2.5.2 Guidelines for Responsive Visualization
52(1)
2.5.3 Evaluating Responsiveness
52(1)
2.5.4 Authoring Support
52(1)
2.5.5 Responsiveness for New Devices
53(1)
2.5.6 Cross-device Responsiveness
54(1)
2.5.7 From Technical to Contextual Responsiveness
54(1)
2.5.8 Make Responses Understandable
54(1)
2.6 Summary
55(12)
References
55(12)
Chapter 3 Interacting with Visualization on Mobile Devices
67(44)
Matthew Brehmer
Bongshin Lee
John Stasko
Christian Tominski
3.1 Foundations
68(3)
3.1.1 Interacting with Visualization
69(1)
3.1.2 Interacting with Mobile Devices
70(1)
3.2 Overview
71(19)
3.2.1 Touch Interaction
73(9)
3.2.2 Spatial Interaction
82(7)
3.2.3 Voice Interaction
89(1)
3.3 Future Opportunities
90(6)
3.3.1 Consistency and Expressivity
91(1)
3.3.2 Multimodal Interaction
92(1)
3.3.3 Multi-device Interaction
92(1)
3.3.4 Visualization Authoring
93(1)
3.3.5 Inspiration from Mobile HCI
93(3)
3.4 Summary
96(15)
References
97(14)
Chapter 4 3D Mobile Data Visualization
111(40)
Lonni Besancon
Wolfgang Aigner
Magdalena Boucher
Tim Dwyer
Tobias Isenberg
4.1 Introduction
112(1)
4.2 Need For 3d Mobile Data Visualization
113(1)
4.3 Progress Toward 3d Mobile Data Visualization: A Moving Target
114(1)
4.4 Motivating Use Case
115(4)
4.4.1 An Example: Aliens
116(2)
4.4.2 Analysis of the Example: Different Kinds of Mobility
118(1)
4.5 Challenges Of 3D Mobile Data Visualization
119(3)
4.6 A Design Space For 3d Mobile Data Visualization
122(2)
4.7 Exploration Of Relevant Configurations Of Our Design Space
124(9)
4.7.1 Volumetric Data on Non-Stereoscopic Displays
124(3)
4.7.2 Volumetric Data on Stereoscopic Displays
127(2)
4.7.3 Non-Volumetric Data on Stereoscopic Displays
129(4)
4.8 Lessons Learned: Could The Marines Be Saved?
133(3)
4.9 Conclusion
136(15)
References
137(14)
Chapter 5 Characterizing Glanceable Visualizations: From Perception to Behavior Change
151(26)
Tanja Blascheck
Frank Bentley
Eun Kvoung Choe
Tom Horak
Petra Isenberg
5.1 Introduction And Context
152(1)
5.2 Perspectives On Glanceability
153(6)
5.2.1 Glanceability in Vision Science
154(1)
5.2.2 Glanceability in Visualization
155(2)
5.2.3 Glanceability in Ubiquitous Computing
157(2)
5.2.4 Summary
159(1)
5.3 Characteristics Of Glanceable Visualizations
159(5)
5.3.1 Presence and Access
160(1)
5.3.2 Simplicity and Understandability
161(1)
5.3.3 Suitability and Purpose
162(1)
5.3.4 Summary
163(1)
5.4 Evaluation Of Glanceable Visualizations
164(4)
5.4.1 Evaluations in the Lab
165(1)
5.4.2 Online Experiments
165(2)
5.4.3 Evaluations in the Field
167(1)
5.4.4 Summary
168(1)
5.5 Discussion And Future Challenges
168(1)
5.6 Conclusion
169(8)
References
169(8)
Chapter 6 Evaluating Mobile Visualizations
177(32)
Frank Bentley
Eun Kyoung Choe
Lena Mamykina
John Stasko
Pourang Irani
6.1 Introduction
178(1)
6.2 Background
179(4)
6.3 Method
183(1)
6.4 Framework
183(2)
6.5 Evaluation Methods
185(11)
6.5.1 Perception
185(3)
6.5.2 Usability
188(1)
6.5.3 Feasibility
189(2)
6.5.4 Understanding
191(2)
6.5.5 Reflection and Insights
193(1)
6.5.6 Behavior Change
194(2)
6.6 discussion
196(13)
References
197(12)
Chapter 7 Challenges in Everyday Use of Mobile Visualizations
209(32)
Daniel A. Epstein
Tanja Blascheck
Sheelagh Carpendale
Raimund Dachselt
Jo Vermeulen
7.1 Introduction
210(1)
7.2 Everyday Interaction Challenges Of Mobile Visualizations
211(7)
7.2.1 From Being Informed to Information Overload
211(3)
7.2.2 Fewer Opportunities for Interaction
214(4)
7.3 Everyday Privacy Challenges Of Mobile Visualizations
218(4)
7.3.1 Violating Privacy Expectations
218(4)
7.4 Everyday Ethical Challenges Of Mobile Visualizations
222(10)
7.4.1 Low Visualization Literacy
222(2)
7.4.2 Limited Resources Lead to Missing Context
224(3)
7.4.3 Persuasive Mobile Visualizations Can Foster Behavior Change, But Not Always for the Better
227(5)
7.5 Discussion
232(1)
7.6 Conclusion
233(8)
References
233(8)
Chapter 8 Mobile Visualization Design: An Ideation Method to Try
241(22)
Sheelagh Carpendale
Petra Isenberg
Charles Perin
Tanja Blascheck
Foroozan Daneshzand
Alaul Islam
Katherine Currier
Peter Buk
Victor Cheung
Lien Quach
Laton Vermette
8.1 Introduction
242(1)
8.2 Relationship To Other Design Methodologies
243(1)
8.3 Mobile Visualization Ideation Methodology
244(1)
8.4 Ideation Activities--Mobile Visualization Futures
245(12)
8.4.1 Approach 1: One Person with In Situ Notes
245(4)
8.4.2 Approach 2: One Person with Post Hoc Notes
249(2)
8.4.3 Approach 3: Two or More People in Discussion
251(2)
8.4.4 Approach 4: Larger Group with Ideation in Stuttgart
253(4)
8.5 Discussion
257(1)
8.6 Conclusion
258(1)
8.7 Acknowledgments
259(4)
References
259(4)
Chapter 9 Reflections on Ubiquitous Visualization
263(42)
Jo Vermeulen
Christopher Collins
Raimund Dachselt
Pourang Irani
Alark Joshi
9.1 Introduction And Context
264(2)
9.2 Approach
266(1)
9.3 Wesley Willett On Embedded Data Representations
267(8)
9.4 Niklas Elmqvist On Ubiquitous Analytics
275(7)
9.5 Sean White On Situated Augmented Reality
282(4)
9.6 Yvonne Rogers On Visualizations For Social Empowerment
286(7)
9.7 Discussion And Overall Reflection
293(5)
9.7.1 Mobile versus Ubiquitous Visualization
293(1)
9.7.2 Challenge: Information Overload
294(1)
9.7.3 Challenge: People Looking Down at Their Mobile Devices
295(1)
9.7.4 Opportunity: Mobile Displays as a Way to Envision the Future
296(1)
9.7.5 The Web as a Technology Platform
296(1)
9.7.6 How Will We Interact with Ubiquitous Visualization?
297(1)
9.8 Scenarios For Ubiquitous Visualization
298(2)
9.9 Revisiting The Dimensions Of Mobile Visualization
300(4)
9.9.1 Reflecting on the Dimensions of Mobile Visualization from Our Interviews
300(3)
9.9.2 Expanding the Dimensions with Context
303(1)
9.10 Conclusion
304(1)
References 305(12)
Index 317
Bongshin Lee is a Sr. Principal Researcher in the EPIC (Extended Perception Interaction Cognition) research group, part of Human-Computer Interaction Group (HCI@MSR), at Microsoft Research. She received her PhD in Computer Science from the University of Maryland, College Park in 2006. Bongshins research areas span data visualization, human-computer interaction, and human-data interaction, focusing on the design, development, and evaluation of novel data visualization and interaction techniques. The overarching goal of her research is to empower people to achieve their goals by leveraging data, data visualization, and technological advancements. Bongshin explores innovative ways to help people with different abilities to interact with data, by supporting easy and effective data collection, data exploration & analysis, and data-driven communication. Her most recent research endeavors include personal data visualization, data visualization on mobile devices, inclusive data visualization and multimodal interaction for data visualization. She is a member of the IEEE Visualization Academy and the IEEE Visualization Executive Committee.

Raimund Dachselt is a Full Professor of Computer Science at the Technische Universität Dresden, Germany. Since 2012, he leads the Interactive Media Lab Dresden at the Faculty of Computer Science. He received his PhD in 2004 from TU Dresden and was Professor for User Interface Engineering at the University of Magdeburg from 2007 to 2012. His research interests are at the intersection of natural, multimodal human computer interaction (HCI) and data visualization. He worked extensively in the area of interactive surfaces from smartwatches over tabletops to wall-sized displays and expanded the scope to Mixed Reality interfaces for immersive data analysis. He contributed several novel interface approaches for information visualization. He has co-authored more than 220 peer-reviewed publications and two major German HCI textbooks and received several Best Paper Awards at leading conferences. He has co-organized 17 international workshops at ACM and IEEE conferences, is the head of the ACM ISS steering committee and repeatedly served in numerous chairing and organizational roles as well as a PC member for international conferences.

Petra Isenberg is a research scientist at Inria, Saclay, France in the Aviz team and part of the Computer Science Laboratory of University Paris-Saclay (LISN). Prior to joining Inria, she received her PhD from the University of Calgary in 2010 on collaborative information visualization. Petra also holds a Diplom-engineer degree in Computational Visualistics from the University of Magdeburg. Her main research areas are visualization and visual analytics with a focus on non-desktop devices, interaction, and evaluation. She is particularly interested in exploring how people can most effectively work together when analyzing large and complex data sets on novel display technology such as small touch-screens, mobile devices, and wall displays, or tabletops. Petra is associate editor-in-chief at IEEE CG&A, associate editor of the IEEE Transactions on Visualization and Computer Graphics, has served on many organizing committee roles in various conferences, and has been the co-chair of the biennial Beliv workshop from 20122018.

Eun Kyoung Choe is an Associate Professor in the College of Information Studies at the University of Maryland, College Park. She received her PhD in Information Science from University of Washington, MS in Information Management and Systems from University of California, Berkeley, and BS in Industrial Design from KAIST. Her work sits at the intersection of HCI, Ubiquitous Computing, and Personal Informatics. With an overarching goal of empowering individuals, she examines some of the major challenges people face in leveraging personal data, such as data collection, data exploration, and data sharing. Drawing insights from formative studies, she designs novel systems to support personalized data collection and multimodal data exploration for people to interact with data. Her work has been funded by the National Science Foundation, National Institute of Health, and Microsoft Research. She has been serving on the editorial boards of PACM IMWUT and Foundations and Trends in Human-Computer Interaction, and as a subcommittee chair for CHI Health (20202021).