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Focus-Based Interactive Visualization for Structured Data

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Focus-Based Interactive Visualization for Structured Data FOCUS-BASED INTERACTIVE VISUALIZATION FOR STRUCTURED DATA DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of the Ohio State University By Ying Tu, B.S., M.S. Graduate Program in Computer Science and Engineering The Ohio State University 2013 Dissertation Committee: Prof. Han-Wei Shen, Advisor Prof. Roger Crawfis Prof. Richard Parent c Copyright by Ying Tu 2013 ABSTRACT Information visualization, a field that studies visual representations of abstract data where no spatial representation is available, has been playing an essential role in assist- ing people to understand the vast amount of information created by modern technology. Visualizing large complex structured data is an important area as the structured data are ubiquitous in many aspects of our lives. The large size, high complexity, and vast variety in user interests pose formidable challenges to create effective representations for those structured data. To help users understand detailed information in the large dataset based on their chang- ing interests, several focus-based interactive visualization methods have been described. To allow users to discover specific contextual information around the focused entities in large semantic graphs, we propose to use the embedded semantic queries during browsing as the main method for information discovery. In addition, to let users quickly understand the different aspects of the graph data, we propose to set up multiple contexts and enable users to quickly switch among the contexts without any abrupt layout changes. Moreover, to assist users in quickly identifying the focal entities when comparing two treemaps, we pro- pose novel contrast techniques to highlight the key differences of the two treemaps in the context of a single treemap so that direct comparison can be done easily. Furthermore, to facilitate the study of the details of multiple foci in a treemap, we propose a focus+context ii technique to seamlessly enlarge multiple foci in the same view while maintaining a consis- tent and stable layout. The effectiveness of these approaches are evaluated by case studies and user studies, where we have clearly demonstrated that users can better understand the structured data with more details and in less amount of time. Both free exploration and task-oriented scenarios were studied in our experiments. iii Dedicated To My parents Yuemei Zhang and Xiaoming Tu. iv ACKNOWLEDGMENTS Let me begin by thanking my advisor, Dr. Han-Wei Shen, for his guidance and support throughout this very long journey. His passion for research and the work quality have deeply influenced me. It would have not been possible for me to finish this doctoral thesis without his encouragement and understanding. I am also deeply indebted to Professor Richard Parent, Professor Roger Crawfis and Professor Yusu Wang, not only for their time and effort in serving in my dissertation com- mittee, but also for their generous help and insightful feedbacks. Thanks also go to other professors who passed their knowledge and academic spirits to me. I really enjoyed the time that I worked with my group members: Jonathan Woodring, Liya Li, Lijie Xu, Teng-Yok Lee, Yuan Hong, Thomas Kerwin, Boonthanome Nouane- sengsy, Steve Martin and Abon Chauduhri. Thanks to them for helping me broaden my interests and improve my research and skills. I thank Qian Zhu, Zhaozhang Jin, Guoqiang Shu, Lei Chai, Lifeng Sang, Ping Lai, Wang Huang, Na Li, Shuang Li and many other friends at OSU for their company and help in various aspects. I am grateful to my colleagues at Microsoft, especially my former manager, Franco Salvetti, who respects my passion in research, and encourages me to complete this work. I am also grateful to the researchers and authors whose works opened the door of the field of information visualization to me, and inspired me all along these years: Edward Tufte, Ben Shneiderman, Martin Wattenberg, Jarke J. van Wijk, Frank van Ham, George W. Furnas, Jeffrey Heer, Tamara Munzner, Manojit Sarkar, and many others. v I also owe a debt of gratitude to the anonymous paper reviewers. Their recognition of my works means a lot to me and their insightful suggestions have been extremely helpful for my research. Last but not least, I am deeply thankful to my families. Thanks to my husband, Qi Gao, who has been with me during the whole journey. He is smart, diligent, inspiring and he creates so much joy in my life. He is not only a great company for the past ten years, but also voluntarily gave up his greatest hobby of traveling to support me doing research during almost all the vacation days for the past three years. Without his support, it would have been impossible for me to finish this work. My deepest thanks go to my parents, who truly believe in me and patiently support me. Their persistence and optimism in their darkest days make them my role model to confront difficulties and never think about giving up easily. vi VITA 1983 .................................. BorninYichun, Jiangxi, China 2004 .................................. BachelorinEngineering, Zhejiang Univer- sity, China 2004–2005 ........................... GraduateStudent, Lehigh University 2009 .................................. MasterofScience, The Ohio State Univer- sity 2005-Present .......................... Graduate Student, The Ohio State Univer- sity PUBLICATIONS Ying Tu and Han-Wei Shen. “GraphCharter: Combining Browsing with Query to Ex- plore Large Semantic Graphs”. IEEE Pacific Visualization Conference (PacificVis’ 2013), Syndey, Australia, 2013. Ying Tu. “Multi-con: exploring graphs by fast switching among multiple contexts”. Pro- ceedings of the International Conference on Advanced Visual Interfaces (AVI’ 10), 259 - 266, Rome, Italy, 2010. Ying Tu and Han-Wei Shen. “Balloon Focus: a Seamless Multi-Focus+Context Method for Treemaps”. Proceedings of IEEE Conference on Information Visualization (InfoVis’ 08), a special issue of IEEE Transactions on Visualization and Computer Graphics, 1157 - 1164, Columbus, OH, USA, 2008. Ying Tu and Han-Wei Shen. “Visualizing Changes of Hierarchical Data using Treemaps”. Proceedings of IEEE Conference on Information Visualization(InfoVis’ 07), a special issue vii of IEEE Transactions on Visualization and Computer Graphics, 1285 - 1293, Sacramento, CA, USA, 2007. FIELDS OF STUDY Major Field: Computer Science and Engineering Specialization: Information Visualization viii TABLE OF CONTENTS Abstract......................................... ii Dedication........................................ iii Acknowledgments.................................... v Vita ........................................... vii ListofFigures...................................... xii CHAPTER PAGE 1 Introduction................................... 1 1.1 Motivation................................. 1 1.2 Contributions................................ 4 1.2.1 GraphCharter: find specific contextual information via focus- basedqueryforbrowsinglargesemanticgraphs . 6 1.2.2 Multi-Con: reveal various aspects of the focal nodes by fast switchingamongmultiplecontexts . 7 1.2.3 Contrast Treemap: identify focal entities by highlighting dif- ferences of the two treemaps in the context of a single treemap. 8 1.2.4 Balloon Focus: seamlessly enlarge multiple foci with a stable treemaplayoutasthecontext. 9 1.3 Outline................................... 10 2 Background&RelatedWorks ......................... 11 2.1 GraphDrawingforNode-linkDiagrams . 11 2.1.1 LayoutCreationforStaticGraphs . 13 2.1.2 LayoutCreationforDynamicGraphs . 17 2.1.3 OverlapRemovalAlgorithms . 18 2.2 Treemaps.................................. 19 2.2.1 TreemapLayouts . 19 2.2.2 Contentoftreemapitems. 22 2.2.3 TreeComparison . 23 ix 2.3 HybridDrawingStyles . 24 2.4 SemanticGraphVisualization . 25 2.5 FocusandContextViewing . 26 2.5.1 Focus+ContextforNode-LinkDiagrams . 27 2.5.2 Focus+ContextforTreemaps. 29 2.5.3 MultipleContexts. 30 2.6 GraphQueryFormulation . 31 2.7 DatabaseQuerySpecification . 32 3 GraphCharter .................................. 40 3.1 Overview.................................. 41 3.2 DesignConsiderations. 44 3.3 GraphCharterSystem . 46 3.3.1 QueryFormulationandQueryGraph . 48 3.3.2 QueryExecutionandResultPresentation . 52 3.3.3GraphBrowsing . .. .. .. .. .. .. .. 54 3.3.4 OtherInteractions&VisualFeatures. 56 3.4 CaseStudyonFreebaseKnowledgeGraph . 58 3.5 UserStudy................................. 65 3.5.1 SetupandProcedure . 65 3.5.2Tasks ............................... 66 3.5.3 ResultsandObservations. 67 3.6 Summary.................................. 69 4 Multi-Con.................................... 70 4.1 Overview.................................. 71 4.2 SingleContextVSMultipleContexts . .. 73 4.2.1 DeficiencyofSingleContext. 73 4.2.2 DesiredFeaturesofMultipleContexts . 75 4.3 Multi-ConApproach. 76 4.3.1TheSystem............................ 77 4.3.2 LayoutAdjustmentAlgorithm . 77 4.3.3Animation ............................ 81 4.4 CaseStudy................................. 82 4.4.1SingleFocus ........................... 83 4.4.2MultipleFoci ........................... 86 4.5 Summary.................................. 87 5 ContrastTreemap ................................ 88 5.1 Overview.................................. 89 5.2 VisualizingChanges/ContrastonTreemaps . ..... 90 5.2.1 TreeMappingandUnionTrees . 92 x 5.2.2 ContrastTreemapContentDesigns . 94 5.3 UserStudy.................................101 5.4 Summary..................................104 6 BalloonFocus..................................109
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