Interactive visual data analysis:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton, London, New York
CRC Press
2020
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| Schriftenreihe: | A.K. Peters visualization series
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xvii, 345 Seiten Illustrationen, Diagramme (teilweise farbig) 24 cm |
| ISBN: | 9780367898755 9781498753982 |
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Datensatz im Suchindex
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| adam_text |
Contents Foreword xiii Preface XV Authors xvii Chapter 1.1 1 ■ Introduction BASIC CONSIDERATIONS 1.1.1 1.1.2 1.2 INTRODUCTORY EXAMPLES 1.2.1 1.2.2 1.2.3 1.3 Chapter 2.1 2.2 Visualization, Interaction, and Computation Five Ws of Interactive Visual Data Analysis Starting Simple Enhancing the Data Analysis Considering Advanced Techniques BOOK OUTLINE 2 ■ Criteria, Factors, and Models CRITERIA INFLUENCING FACTORS 2.2.1 2.2.2 2.2.3 2.2.4 The Subject: Data The Objective: Analysis Tasks The Context: Users and Technologies Demonstrating Example 1 2 2 4 5 5 8 10 13 15 16 19 19 28 35 38 vii
viii ■ Contents 2.3 PROCESS MODELS 2.3.1 2.3.2 2.3.3 2.4 Chapter 3.1 3.3 VISUAL ENCODING AND PRESENTATION Chapter 4.1 54 1 54 62 67 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.2.6 67 69 71 73 75 77 Table-based Visualization Combined Bivariate Visualization Polyline-based Visualization Glyph-based Visualization Pixel-based Visualization Nested Visualization VISUALIZATION OF TEMPORAL DATA 82 Time and Temporal Data Visualization Techniques 82 86 VISUALIZATION OF GEO-SPATIAL DATA 95 Geographic Space and Geo-spatial Data General Visualization Strategies Visualizing Spatio-temporal Data GRAPH VISUALIZATION 3.5.1 3.5.2 3.5.3 3.6 Encoding Data Values Presentation 51 MULTIVARIATE DATA VISUALIZATION 3.4.1 3.4.2 3.4.3 3.5 48 3 ■ Visualization Methods and Techniques 3.3.1 3.3.2 3.4 41 44 47 SUMMARY 3.1.1 3.1.2 3.2 41 Design Data Transformation Knowledge Generation Graph Data Basic Visual Representations Visualizing Multi-faceted Graphs SUMMARY 4 ■ Interacting with Visualizations HUMAN IN THE LOOP 4.1.1 4.1.2 Interaction Intents and Action Patterns The Action Cycle 96 99 106 111 111 113 118 124 129 131 132 135
Contents ■ ix 4.2 REQUIREMENTS FOR EFFICIENT INTERACTION 4.2.1 4.2.2 4.2.3 4.3 4.4 4.5 4.8 4.9 Chapter 5.1 144 145 146 Taking Action Generating Feedback INTERACTIVE SELECTION AND ACCENTUATION 148 4.4.1 4.4.2 4.4.3 149 153 156 Specifying Selections Visual Emphasis and Attenuation Enhanced Selection Support NAVIGATING ZOOMABLE VISUALIZATIONS Basics and Conceptual Considerations Visual Interface and Interaction Interaction Aids and Visual Cues Beyond Zooming in Two Dimensions INTERACTIVE LENSES Conceptual Model Adjustable Properties Lenses in Action 159 160 162 164 168 173 173 176 178 INTERACTIVE VISUAL COMPARISON 184 4.7.1 4.7.2 4.7.3 184 186 190 Basics and Requirements Naturally Inspired Comparison Reducing Comparison Costs INTERACTION BEYOND MOUSE AND KEYBOARD 194 4.8.1 4.8.2 4.8.3 194 197 202 Touching Visualizations Interacting with Tangibles Moving the Body to Explore Visualizations SUMMARY 5 ■ Automatic Analysis Support DECLUTTERING VISUAL REPRESENTATIONS 5.1.1 5.1.2 5.2 136 138 143 BASIC OPERATIONS FOR INTERACTION 4.6.1 4.6.2 4.6.3 4.7 136 4.3.1 4.3.2 4.5.1 4.5.2 4.5.3 4.5.4 4.6 Interaction Costs Directness of Interaction Design Guidelines Computing and Visualizing Density Bundling Geometrical Primitives FOCUSING ON RELEVANT DATA 204 207 209 209 212 214
x ■ Contents 5.2.1 5.2.2 5.2.3 5.3 ABSTRACTING DATA 5.3.1 5.3.2 5.4 Chapter 6.1 6 ■ Advanced Concepts VISUALIZATION IN MULTI-DISPLAY ENVIRONMENTS 6.3 6.4 Chapter 7.1 7.2 231 231 233 239 239 243 250 257 263 267 268 Environment and Requirements 269 Supporting Collaborative Visual Data Analysis 270 Multi-display Analysis of Climate Change Impact 276 GUIDING THE USER 6.2.1 6.2.2 6.2.3 214 220 224 Principal Component Analysis 258 Visual Data Analysis with Principal Components 260 SUMMARY 6.1.1 6.1.2 6.1.3 6.2 Classification Data Clustering Clustering Multivariate Dynamic Graphs REDUCING DIMENSIONALITY 5.5.1 5.5.2 5.6 Sampling and Aggregation Exploring Multi-scale Data Abstractions GROUPING SIMILAR DATA ELEMENTS 5.4.1 5.4.2 5.4.3 5.5 Degree of Interest Feature-based Visual Analysis Analyzing Features of Chaotic Movement 277 Characterization of Guidance 278 Guiding the Navigation in Hierarchical Graphs 283 Guiding the Visual Analysis of Heterogeneous Data 286 PROGRESSIVE VISUAL DATA ANALYSIS 288 6.3.1 6.3.2 6.3.3 290 294 297 Conceptual Considerations Multi-threading Architecture Scenarios SUMMARY 7 ■ Summary WHAT’S BEEN DISCUSSED HOW TO CONTINUE 303 305 305 307
Contents ■ xi Bibliography 311 Index 339 Figure Credits 343 |
| adam_txt |
Contents Foreword xiii Preface XV Authors xvii Chapter 1.1 1 ■ Introduction BASIC CONSIDERATIONS 1.1.1 1.1.2 1.2 INTRODUCTORY EXAMPLES 1.2.1 1.2.2 1.2.3 1.3 Chapter 2.1 2.2 Visualization, Interaction, and Computation Five Ws of Interactive Visual Data Analysis Starting Simple Enhancing the Data Analysis Considering Advanced Techniques BOOK OUTLINE 2 ■ Criteria, Factors, and Models CRITERIA INFLUENCING FACTORS 2.2.1 2.2.2 2.2.3 2.2.4 The Subject: Data The Objective: Analysis Tasks The Context: Users and Technologies Demonstrating Example 1 2 2 4 5 5 8 10 13 15 16 19 19 28 35 38 vii
viii ■ Contents 2.3 PROCESS MODELS 2.3.1 2.3.2 2.3.3 2.4 Chapter 3.1 3.3 VISUAL ENCODING AND PRESENTATION Chapter 4.1 54 1 54 62 67 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.2.6 67 69 71 73 75 77 Table-based Visualization Combined Bivariate Visualization Polyline-based Visualization Glyph-based Visualization Pixel-based Visualization Nested Visualization VISUALIZATION OF TEMPORAL DATA 82 Time and Temporal Data Visualization Techniques 82 86 VISUALIZATION OF GEO-SPATIAL DATA 95 Geographic Space and Geo-spatial Data General Visualization Strategies Visualizing Spatio-temporal Data GRAPH VISUALIZATION 3.5.1 3.5.2 3.5.3 3.6 Encoding Data Values Presentation 51 MULTIVARIATE DATA VISUALIZATION 3.4.1 3.4.2 3.4.3 3.5 48 3 ■ Visualization Methods and Techniques 3.3.1 3.3.2 3.4 41 44 47 SUMMARY 3.1.1 3.1.2 3.2 41 Design Data Transformation Knowledge Generation Graph Data Basic Visual Representations Visualizing Multi-faceted Graphs SUMMARY 4 ■ Interacting with Visualizations HUMAN IN THE LOOP 4.1.1 4.1.2 Interaction Intents and Action Patterns The Action Cycle 96 99 106 111 111 113 118 124 129 131 132 135
Contents ■ ix 4.2 REQUIREMENTS FOR EFFICIENT INTERACTION 4.2.1 4.2.2 4.2.3 4.3 4.4 4.5 4.8 4.9 Chapter 5.1 144 145 146 Taking Action Generating Feedback INTERACTIVE SELECTION AND ACCENTUATION 148 4.4.1 4.4.2 4.4.3 149 153 156 Specifying Selections Visual Emphasis and Attenuation Enhanced Selection Support NAVIGATING ZOOMABLE VISUALIZATIONS Basics and Conceptual Considerations Visual Interface and Interaction Interaction Aids and Visual Cues Beyond Zooming in Two Dimensions INTERACTIVE LENSES Conceptual Model Adjustable Properties Lenses in Action 159 160 162 164 168 173 173 176 178 INTERACTIVE VISUAL COMPARISON 184 4.7.1 4.7.2 4.7.3 184 186 190 Basics and Requirements Naturally Inspired Comparison Reducing Comparison Costs INTERACTION BEYOND MOUSE AND KEYBOARD 194 4.8.1 4.8.2 4.8.3 194 197 202 Touching Visualizations Interacting with Tangibles Moving the Body to Explore Visualizations SUMMARY 5 ■ Automatic Analysis Support DECLUTTERING VISUAL REPRESENTATIONS 5.1.1 5.1.2 5.2 136 138 143 BASIC OPERATIONS FOR INTERACTION 4.6.1 4.6.2 4.6.3 4.7 136 4.3.1 4.3.2 4.5.1 4.5.2 4.5.3 4.5.4 4.6 Interaction Costs Directness of Interaction Design Guidelines Computing and Visualizing Density Bundling Geometrical Primitives FOCUSING ON RELEVANT DATA 204 207 209 209 212 214
x ■ Contents 5.2.1 5.2.2 5.2.3 5.3 ABSTRACTING DATA 5.3.1 5.3.2 5.4 Chapter 6.1 6 ■ Advanced Concepts VISUALIZATION IN MULTI-DISPLAY ENVIRONMENTS 6.3 6.4 Chapter 7.1 7.2 231 231 233 239 239 243 250 257 263 267 268 Environment and Requirements 269 Supporting Collaborative Visual Data Analysis 270 Multi-display Analysis of Climate Change Impact 276 GUIDING THE USER 6.2.1 6.2.2 6.2.3 214 220 224 Principal Component Analysis 258 Visual Data Analysis with Principal Components 260 SUMMARY 6.1.1 6.1.2 6.1.3 6.2 Classification Data Clustering Clustering Multivariate Dynamic Graphs REDUCING DIMENSIONALITY 5.5.1 5.5.2 5.6 Sampling and Aggregation Exploring Multi-scale Data Abstractions GROUPING SIMILAR DATA ELEMENTS 5.4.1 5.4.2 5.4.3 5.5 Degree of Interest Feature-based Visual Analysis Analyzing Features of Chaotic Movement 277 Characterization of Guidance 278 Guiding the Navigation in Hierarchical Graphs 283 Guiding the Visual Analysis of Heterogeneous Data 286 PROGRESSIVE VISUAL DATA ANALYSIS 288 6.3.1 6.3.2 6.3.3 290 294 297 Conceptual Considerations Multi-threading Architecture Scenarios SUMMARY 7 ■ Summary WHAT’S BEEN DISCUSSED HOW TO CONTINUE 303 305 305 307
Contents ■ xi Bibliography 311 Index 339 Figure Credits 343 |
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| spelling | Tominski, Christian 1977- Verfasser (DE-588)13336089X aut Interactive visual data analysis Christian Tominski, Heidrun Schumann Boca Raton, London, New York CRC Press 2020 © 2020 xvii, 345 Seiten Illustrationen, Diagramme (teilweise farbig) 24 cm txt rdacontent n rdamedia nc rdacarrier A.K. Peters visualization series Visualisierung (DE-588)4188417-6 gnd rswk-swf Daten (DE-588)4135391-2 gnd rswk-swf Daten (DE-588)4135391-2 s Visualisierung (DE-588)4188417-6 s DE-604 Schumann, Heidrun 1954- Verfasser (DE-588)132788233 aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032142324&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Interactive visual data analysis |
| title_auth | Interactive visual data analysis |
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| title_full | Interactive visual data analysis Christian Tominski, Heidrun Schumann |
| title_fullStr | Interactive visual data analysis Christian Tominski, Heidrun Schumann |
| title_full_unstemmed | Interactive visual data analysis Christian Tominski, Heidrun Schumann |
| title_short | Interactive visual data analysis |
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| topic_facet | Visualisierung Daten |
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