ITEM METADATA RECORD
Title: Biological Data Visualization: Analysis and Design
Other Titles: Biologische data visualisatie: analyse en ontwerp
Authors: Sakai, Ryo; R0308408
Issue Date: 18-May-2016
Abstract: Data visualization is an integral part of biological sciences and essential to enable dissemination of knowledge and sophisticated analysis of data. With advances in both biological data acquisition technologies and data-management and -processing technologies, researchers face challenges of developing better conjectures from the data that continue to increase in volume and complexity. Consequently, such data analysis often requires interdisciplinary expertise to address challenges in each case. In this thesis, we examine the design process of visualization projects from a wide range of application domains. The discussion includes the descriptive explanation of intermediate iterations towards the final design solution. The existing visualization model and framework are extended to characterise the design space of biological data visualization. Also, a practical 4-step guideline for visualization design is provided as an actionable evaluation method of visualization design. Careful retrospective analysis of each design case reveals that data visualization is ubiquitous, highlighting its vital role at different stages of data-intensive science.
Table of Contents: Abstract v
Acronyms ix
Contents xiii
List of Figures xix
List of Tables xxv

1 Introduction 1

2 Framework and Model of Visualization 7
2.1 What-Why-HowFramework.................... 7
2.1.1 What ............................ 8
2.1.2 Why............................. 8
2.1.3 How............................. 10
2.2 ModelofVisualization....................... 14
2.3 ChoiceofVisTools......................... 16
2.4 CustomVisualizationSolutions.................. 18
2.5 CardSortingTechnique ...................... 21
2.5.1 Abstract........................... 21
2.5.2 Introduction ........................ 21
2.5.3 RelatedWork........................ 23
2.5.4 CardSorting ........................ 23
2.5.5 CaseStudy ......................... 26
2.5.6 Discussion.......................... 28
2.5.7 Acknowledgements..................... 29

3 Visual Encoding Design 31
3.1 VisualAnalytics .......................... 31
3.2 CaseStudy:FlyPlot........................ 34
3.3 CaseStudy:Pipit ......................... 40
3.4 Pipit: Visualizing Functional Impacts of Structural Variations . 49
3.4.1 Summary .......................... 49
3.4.2 Availability:......................... 49
3.4.3 Introduction ........................ 49
3.4.4 Features........................... 51
3.4.5 Discussion.......................... 52
3.4.6 Acknowledgement ..................... 52

4 Data Sketching 53
4.1 WhyDataSketch? ......................... 53
4.2 Sequence Diversity Diagram - BioVis Redesign Challenge . . . 55
4.3 Sequence Diversity Diagram for Comparative Analysis of Multiple SequenceAlignments........................ 65
4.3.1 Abstract........................... 65
4.3.2 Background......................... 66
4.3.3 Methods........................... 69
4.3.4 Results ........................... 69
4.3.5 Conclusions......................... 71

5 Sequential Tasks 73
5.1 CaseStudy:Aracari ........................ 74
5.2 CaseStudy:Seagull ........................ 77
5.3 An eQTL Biological Data Visualization Challenge and Ap- proaches from the Visualization Community . . . . . . . . . . . 83
5.3.1 Abstract........................... 83

6 Interaction Design 95
6.1 Interaction ............................. 95
6.2 CaseStudy:BrainConstellation ................. 98
6.3 CaseStudy:TrioVis ........................ 103
6.4 CaseStudy:Dendsort ....................... 105
6.5 TrioVis: a Visualization Approach for Filtering Genomic Variants ofParent-childTrios ........................ 112
6.5.1 Summary:.......................... 112
6.5.2 Availability:......................... 112
6.5.3 Introduction ........................ 112
6.5.4 Features........................... 114
6.5.5 Conclusion ......................... 115
6.6 dendsort: Modular Leaf Ordering Methods for Dendrogram Representations in R........................ 116
6.6.1 Abstract........................... 116
6.6.2 Introduction ........................ 116
6.6.3 Methods........................... 118
6.6.4 Results ........................... 120
6.6.5 Discussion.......................... 127
6.6.6 Conclusions......................... 128
6.6.7 SoftwareAvailability.................... 128

7 Data Acquisition and Transformation 131
7.1 Introduction............................. 131
7.2 CaseStudy:Oligoprobe ...................... 133
7.3 CaseStudy:BiplotMatrix..................... 142

8 Beyond Desktop Applications 151
8.1 Introduction............................. 151
8.2 CaseStudy:FlyPlotinPrint................... 152
8.3 CaseStudy:CCRP......................... 154

9 Conclusion 159
9.1 Conclusion ............................. 159
9.2 LessonsLearned .......................... 161
9.2.1 SkillsandKnowledge ................... 162
9.2.2 DesignStudyGuideline .................. 162
9.2.3 VisualizationasaProcess................. 163
9.2.4 EnvironmentandWorkCulture. . . . . . . . . . . . . . 163
9.2.5 DesignContests ...................... 163
9.2.6 PracticeintheWild .................... 164
9.2.7 Summary .......................... 164

Bibliography 165

List of Publications 181
Publication status: published
KU Leuven publication type: TH
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics

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