在決策情境中，評估多維資料常常是必要的。平行坐標圖（Parallel Coordinates）是一種資料視覺化技術，透過多軸與線段有效呈現多維資料，廣泛應用於計算機科學、生態學及材料科學等領域。然而，現有的平行坐標圖設計主要針對如數值或類別資料類型，較少探討其他多樣資料類型的整合，如地理資料及圖像資料等，限制了其在現實決策場景中的應用。
本研究旨在克服這些限制，通過重新設計平行坐標圖來支援多種資料類型，包括數值資料、類別資料、地理資料、圖像資料，另外還有由布林資料與數值資料所組成的複合資料類型。基於以上設計，我們開發了一個新的決策支持系統DataFlexPC (DaFPC)，結合創新的視覺化技術，提高平行坐標圖在決策過程中對多元資料類型的適應性。

In decision-making scenarios, evaluating multidimensional data is often essential. Parallel Coordinates (PC), a data visualization technique, can effectively represent multidimensional data through multiple axes and line segments, making it widely applicable in various fields such as computer science, ecology, and materials science. However, existing PC designs primarily focus on two data types, numerical and categorical data, and rarely address the integration of other data types, such as geographical and image data. This limitation constrains the utility of PC in real-world decision-making applications.
This thesis aims to address these limitations by redesigning PC to support multiple data types, including numerical, categorical, geographical, image, boolean and the combination of boolean and numerical data. We have developed a new decision-support system, called DataFlexPC (DaFPC), that implements the new design to enhance PC's applicability to a wider variety of data types in decision making.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
Table of Contents v
Table of Figure viii
List of Table xi
CHAPTER 1 Introduction 1
1.1 Motivation 1
1.2 Research Questions 4
CHAPTER 2 Related Work 6
2.1 Data Types Supported by PC 7
2.1.1 Numerical Data 7
2.1.2 Categorical Data 8
2.1.3 Boolean Data 9
2.1.4 Geographical Data 9
2.1.5 Image Data 11
2.2 Summary 12
CHAPTER 3 System Design 14
3.1 System Requirements 14
3.2 Visualization System Design 17
3.3 Block 1 - Multi-Type Visualization Design (>5 cases) 23
3.3.1 Geographical Data Design 24
3.3.2 Numerical Data Design 29
3.3.3 Boolean Data Design 30
3.3.4 Categorical Data Design 32
3.4 Block 2 - Limited-Scale Data (≤ 5 cases) 33
3.4.1 Combined Boolean and Numerical Data 34
3.5 Block 3 - Limited-Scale Data (≤ 3 cases) 35
3.3.6 Image data Design 36
CHAPTER 4 Evaluation 38
4.1 Participants 38
4.2 Data 39
4.3 Control System 40
4.4 Tasks 41
4.4.1 Task in Instructional Phase 42
4.4.2 Tasks in Formal Evaluation Phase 42
4.5 Outcome Measures 49
4.5.1 Quantitative 49
4.5.2 Qualitative User Feedback 50
4.6 Study Procedure 50
4.7 Results 52
4.7.1 Quantitative Analysis 52
4.7.2 User Feedback 63
CHAPTER 5 Discussion & Conclusion 73
5.1 Research Contribution 74
5.2 Limitations 75
5.2.1 Limitations in Evaluation Design 76
5.2.2 Limitations in System and Visualization Design 76
References 78
Appendix A: Basic Information 85
Appendix B: Response Form for the Visualization Test 86
Appendix C: After Decision on Each Task with Predefined Objectives 88
Appendix D: Factors Influencing Decision-Making Survey 90
Appendix E: Post Study Questionnaire 91
Appendix F: Post Study Interview Guide 93

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