Visual Notation
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This document summarizes Daniel Moody's research on establishing scientific principles for constructing effective visual notations in software engineering. It discusses Moody's descriptive theory that explains how visual notations communicate through encoding and decoding processes. It also outlines Moody's prescriptive theory, which proposes seven principles for designing visual notations, including principles of semiotic clarity, perceptual discriminability, semantic transparency, and complexity management. The principles are intended to guide the development of visual notations that clearly and efficiently convey semantic meaning.
Visual Notation
- 1. The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering Daniel L. Moody, Member, IEEE Presented By: Raj Kumar Ranabhat M.E. In Computer Engineering, I/I Kathmandu University
- 2. February 14, 2017 2 Table of Content: 1. INTRODUCTION 2. RELATED RESEARCH 3. DESCRIPTIVE THEORY : HOW VISUAL NOTATIONS COMMUNICATE 4. PRESCRIPTIVE THEORY : PRINCIPLES FOR DESIGNING EFFECTIVE VISUAL NOTATIONS 5. CONCLUSION
- 3. February 14, 2017 3 1. INTRODUCTION 1.1 The Nature of Visual Languages 1.2 The Dependent Variable: What Makes a “Good” Visual Notation? 1.3 Visual Syntax: An Important but Neglected Issue 1.4 Why Visual Representation Is Important
- 4. February 14, 2017 4 2. RELATED RESEARCH 2.1 Ontological Analysis
- 5. February 14, 2017 5 3. DESCRIPTIVE THEORY : HOW VISUAL NOTATIONS COMMUNICATE 3.1 Communication Theory
- 6. February 14, 2017 6 3.2 The Design Space (Encoding Side)
- 7. February 14, 2017 7 3.3 The Solution Space (Decoding Side)
- 8. February 14, 2017 8 4. PRESCRIPTIVE THEORY : PRINCIPLES FOR DESIGNING EFFECTIVE VISUAL NOTATIONS 4.1 Principle of Semiotic Clarity: There Should Be a 1:1 Correspondence between Semantic Constructs and Graphical Symbols
- 9. February 14, 2017 9 4.2 Principle of Perceptual Discriminability: Different Symbols Should Be Clearly Distinguishable from Each Other 4.2.1 Visual Distance 4.2.2 The Primacy of Shape 4.2.3 Redudant Coding 4.2.4 Textual Differentiation
- 10. February 14, 2017 10 4.3 Principle of Semantic Transparency: Use Visual Representations Whose Appearance Suggests Their Meaning 4.3.1 Icons (Perceptual Resemblance)
- 11. February 14, 2017 11 4.3.2 Semantically Transparent Relationships
- 12. February 14, 2017 12 4.4 Principle of Complexity Management: Include Explicit Mechanisms for Dealing with Complexity
- 13. February 14, 2017 13 4.4.1 Modularization 4.4.2 Hierarchy (Levels of Abstraction)
- 14. February 14, 2017 14 4.5 Principle of Cognitive Integration: Include Explicit Mechanisms to Support Integration of Information from Different Diagrams
- 15. February 14, 2017 15 4.6 Principle of Visual Expressiveness: Use the Full Range and Capacities of Visual Variables
- 16. February 14, 2017 16 4.7 Principle of Dual Coding: Use Text to Complement Graphics
- 17. February 14, 2017 17 5. CONCLUSION 5.1 Practical Significance 5.2 Theoretical Significance 5.3 Limitations and Further Research 5.4 Wider Significance