3,134 research outputs found

    Design Guidelines for Agent Based Model Visualization

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    In the field of agent-based modeling (ABM), visualizations play an important role in identifying, communicating and understanding important behavior of the modeled phenomenon. However, many modelers tend to create ineffective visualizations of Agent Based Models (ABM) due to lack of experience with visual design. This paper provides ABM visualization design guidelines in order to improve visual design with ABM toolkits. These guidelines will assist the modeler in creating clear and understandable ABM visualizations. We begin by introducing a non-hierarchical categorization of ABM visualizations. This categorization serves as a starting point in the creation of an ABM visualization. We go on to present well-known design techniques in the context of ABM visualization. These techniques are based on Gestalt psychology, semiology of graphics, and scientific visualization. They improve the visualization design by facilitating specific tasks, and providing a common language to critique visualizations through the use of visual variables. Subsequently, we discuss the application of these design techniques to simplify, emphasize and explain an ABM visualization. Finally, we illustrate these guidelines using a simple redesign of a NetLogo ABM visualization. These guidelines can be used to inform the development of design tools that assist users in the creation of ABM visualizations.Visualization, Design, Graphics, Guidelines, Communication, Agent-Based Modeling

    Animated Edge Textures in Node-Link Diagrams: a Design Space and Initial Evaluation

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    International audienceNetwork edge data attributes are usually encoded using color, opacity, stroke thickness and stroke pattern, or some combination thereof. In addition to these static variables, it is also possible to animate dynamic particles flowing along the edges. This opens a larger design space of animated edge textures, featuring additional visual encodings that have potential not only in terms of visual mapping capacity but also playfulness and aesthetics. Such animated edge textures have been used in several commercial and design-oriented visualizations, but to our knowledge almost always in a relatively ad hoc manner. We introduce a design space and Web-based framework for generating animated edge textures, and report on an initial evaluation of particle properties โ€“ particle speed, pattern and frequency โ€“ in terms of visual perception

    Visualizing Magnitude and Direction in Flow Fields

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    In weather visualizations, it is common to see vector data represented by glyphs placed on grids. The glyphs either do not encode magnitude in readable steps, or have designs that interfere with the data. The grids form strong but irrelevant patterns. Directional, quantitative glyphs bent along streamlines are more effective for visualizing flow patterns. With the goal of improving the perception of flow patterns in weather forecasts, we designed and evaluated two variations on a glyph commonly used to encode wind speed and direction in weather visualizations. We tested the ability of subjects to determine wind direction and speed: the results show the new designs are superior to the traditional. In a second study we designed and evaluated new methods for representing modeled wave data using similar streamline-based designs. We asked subjects to rate the marine weather visualizations: the results revealed a preference for some of the new designs

    Dynamic Composite Data Physicalization Using Wheeled Micro-Robots

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    This paper introduces dynamic composite physicalizations, a new class of physical visualizations that use collections of self-propelled objects to represent data. Dynamic composite physicalizations can be used both to give physical form to well-known interactive visualization techniques, and to explore new visualizations and interaction paradigms. We first propose a design space characterizing composite physicalizations based on previous work in the fields of Information Visualization and Human Computer Interaction. We illustrate dynamic composite physicalizations in two scenarios demonstrating potential benefits for collaboration and decision making, as well as new opportunities for physical interaction. We then describe our implementation using wheeled micro-robots capable of locating themselves and sensing user input, before discussing limitations and opportunities for future work

    An Empirical Evaluation of Visual Cues for 3D Flow Field Perception

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    Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena that are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool that can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data that are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies that evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application

    From Analog to Virtual: Visual Stylizations of Humanoid Characters Across Media

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    Visual stylization and its impact on different aspects of the perception of digital human beings are commonly debated. This study investigated how fictional and non-fictional characters are represented in various media from the perspective of digital humanoid character design. Based on Zangwill's theory of Moderate Aesthetic Formalism, this study focused on the formalistic aspect of visual analysis and interpretation of media artifacts ranging from older media such as paintings to newer media, such as animations, interactive video games and mobile apps. This paper also explores several case studies of how humanoid digital characters are represented via visual stylizations across different media. This article underlines the importance of visual stylization as an opportunity to find unique and innovative ways of communicating with visual means

    The role of movement in data visualization: animation as an agent of meaning

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    If we look at data visualizations as signifying machines, in which every element is meaningful, what is the contribution of animation to the construction of meaning? What does motion or animation add in terms of significance to different kinds of graphics? Does it add something in terms of realism? How can animation be an implementer of meaning, dramatizing the sense of data or expressing doubt about the data itself

    ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•œ 3์ฐจ์› ๊ณต๊ฐ„ ๋‚ด ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ฏธ์ˆ ๋Œ€ํ•™ ๋””์ž์ธํ•™๋ถ€ ๋””์ž์ธ์ „๊ณต, 2019. 2. ๊น€์ˆ˜์ •.Speculative visualization combines both data visualization methods and aesthetics to draw attention to specific social, political and environmental issues. The speculative data visualization project proposed in this work explores electronic waste trade and the environmental performance of various nations. Illegal trading of electronic waste without proper disposal and recycling measures has a severe impact on both human health and the environment. This trade can be represented as a network data structure. The overall environmental health and ecosystem vitality of those trading countries, represented by their Environmental Performance Index (EPI), can also give greater insight into this issue. This EPI data has a hierarchical structure. This work explores methods to visualize these two data sets simultaneously in a manner that allows for analytical exploration of the data while communicating its underlying meaning. This project-based design research specifically focuses on visualizing hierarchical datasets with a node-link type tree structure and suggests a novel data visualization method, called the data garden, to visualize these hierarchical datasets within a spatial network. This draws inspiration from networks found between trees in nature. This is applied to the illegal e-waste trade and environmental datasets to provoke discussion, provide a holistic understanding and improve the peoples awareness on these issues. This uses both analytical data visualization techniques, along with a more aesthetic approach. The data garden approach is used to create a 3D interactive data visualization that users can use to navigate and explore the data in a meaningful way while also providing an emotional connection to the subject. This is due to the ability of the data garden approach to accurately show the underlying data while also closely mimicking natural structures. The visualization project intends to encourage creative professionals to create both visually appealing and thought-provoking data visualizations on significant issues that can reach a mass audience and improve awareness of citizens. Additionally, this design research intends to cause further discussion on the role of aesthetics and creative practices in data visualizations.์‚ฌ๋ณ€์  ์‹œ๊ฐํ™”(speculative visualization)๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋ฐฉ๋ฒ•๊ณผ ๋ฏธํ•™์„ ๊ฒฐํ•ฉํ•˜์—ฌ ํŠน์ •ํ•œ ์‚ฌํšŒ, ์ •์น˜ ๋ฐ ํ™˜๊ฒฝ ๋ฌธ์ œ์— ๊ด€์‹ฌ์„ ์œ ๋„ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ œ์•ˆํ•œ ์‚ฌ๋ณ€์  ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ํ”„๋กœ์ ํŠธ๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ๊ตญ๊ฐ€์˜ ์ „์ž ํ๊ธฐ๋ฌผ ๊ฑฐ๋ž˜์™€ ํ™˜๊ฒฝ ์„ฑ๊ณผ๋ฅผ ์‚ดํŽด๋ด…๋‹ˆ๋‹ค. ์ ์ ˆํ•œ ์ฒ˜๋ฆฌ์™€ ์žฌํ™œ์šฉ ์กฐ์น˜๊ฐ€ ์ด๋ค„์ง€์ง€ ์•Š์€ ์ „์žํ๊ธฐ๋ฌผ์˜ ๋ถˆ๋ฒ• ๊ฑฐ๋ž˜๋Š” ํ™˜๊ฒฝ๊ณผ ์ธ๊ฐ„์— ์‹ฌ๊ฐํ•œ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ์ด ๊ฑฐ๋ž˜๋Š” ๋„คํŠธ์›Œํฌ ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ™˜๊ฒฝ์„ฑ๊ณผ์ง€์ˆ˜(EPI)๋ฅผ ํ†ตํ•ด ์ด ๊ฑฐ๋ž˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ตญ๊ฐ€๋“ค์˜ ์ „๋ฐ˜์ ์ธ ํ™˜๊ฒฝ ๋ณด๊ฑด๊ณผ ์ƒํƒœ๊ณ„ ํ™œ๋ ฅ์„ ์‚ดํŽด๋ณด๋Š” ๊ฒƒ์€ ์ด ๋ฌธ์ œ์— ๋” ๊นŠ์€ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ํ™˜๊ฒฝ์„ฑ๊ณผ์ง€์ˆ˜๋Š” ๊ณ„์ธต ๊ตฌ์กฐ๋กœ ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„์ ์œผ๋กœ ํƒ๊ตฌํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๋‘ ๊ฐ€์ง€ ๋ฐ์ดํ„ฐ๋ฅผ ๋™์‹œ์— ์‹œ๊ฐํ™”ํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ํ‘œ๋ฉด์— ๋“œ๋Ÿฌ๋‚˜์ง€ ์•Š๋Š” ๋ฐ์ดํ„ฐ์˜ ์˜๋ฏธ๋ฅผ ์ „๋‹ฌํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ํƒ๊ตฌํ•ฉ๋‹ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ”„๋กœ์ ํŠธ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ๋””์ž์ธ ์—ฐ๊ตฌ๋กœ, ๋…ธ๋“œ ๋งํฌ ์œ ํ˜• ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ํ†ตํ•ด ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ๋ฅผ ์‹œ๊ฐํ™”ํ•˜๋Š” ๊ฒƒ์— ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ž์—ฐ์—์„œ ๋ฐœ๊ฒฌํ•  ์ˆ˜ ์žˆ๋Š” ๋‚˜๋ฌด ๊ฐ„ ๋„คํŠธ์›Œํฌ์—์„œ ์˜๊ฐ์„ ์–ป์–ด ๊ณต๊ฐ„ ๋„คํŠธ์›Œํฌ์—์„œ ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ ์„ธํŠธ๋ฅผ ์‹œ๊ฐํ™”ํ•ฉ๋‹ˆ๋‹ค. ๋ฐ์ดํ„ฐ ์ •์›์ด๋ผ๊ณ  ํ•˜๋Š” ์ด ์ƒˆ๋กœ์šด ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋ฐฉ๋ฒ•์„ ๋ถˆ๋ฒ• ์ „์ž ํ๊ธฐ๋ฌผ ๊ฑฐ๋ž˜์™€ ํ™˜๊ฒฝ ๋ฐ์ดํ„ฐ์— ์ ์šฉํ•˜์—ฌ ํ† ๋ก ์„ ์œ ๋ฐœํ•˜๊ณ  ์ „์ฒด์ ์ธ ์ดํ•ด๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์— ๋Œ€ํ•œ ์‚ฌ๋žŒ๋“ค์˜ ์ธ์‹์„ ๊ฐœ์„ ํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋ณด๋‹ค ๋ฏธ์ ์ธ ์ ‘๊ทผ๊ณผ ๋ถ„์„์  ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๊ธฐ์ˆ ์„ ๋ชจ๋‘ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ๋ฐ์ดํ„ฐ ์ •์›์„ ํ†ตํ•œ ์ ‘๊ทผ์œผ๋กœ ์‚ผ์ฐจ์› ๋Œ€ํ™”ํ˜• ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”๋ฅผ ๋งŒ๋“ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์‹œ๊ฐํ™”๋ฅผ ํ†ตํ•ด ์‚ฌ์šฉ์ž๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์˜๋ฏธ ์žˆ๋Š” ๋ฐฉ์‹์œผ๋กœ ์‚ดํŽด๋ณด๋Š” ๋™์‹œ์— ์ฃผ์ œ์™€ ๊ฐ์„ฑ์ ์ธ ์—ฐ๊ฒฐ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋ฐ์ดํ„ฐ ์ •์› ๋ฐฉ๋ฒ•์ด ๋ฐ์ดํ„ฐ๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ๋ณด์—ฌ์ฃผ๋Š” ๋™์‹œ์— ์ž์—ฐ ๊ตฌ์กฐ๋ฅผ ๋ฉด๋ฐ€ํ•˜๊ฒŒ ๋ชจ๋ฐฉํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๋ณธ ์‹œ๊ฐํ™” ํ”„๋กœ์ ํŠธ๋Š” ์ฐฝ์˜์ ์ธ ์ „๋ฌธ๊ฐ€๋“ค์ด ์ค‘์š”ํ•œ ๋ฌธ์ œ์— ๋Œ€ํ•ด ์‹œ๊ฐ์ ์œผ๋กœ ๋งค๋ ฅ์ ์ด๊ณ  ์ƒ๊ฐ์„ ์ž๊ทนํ•˜๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”๋ฅผ ๋งŒ๋“ค์–ด ๋Œ€์ค‘์—๊ฒŒ ๋„๋‹ฌํ•˜๊ณ  ์‹œ๋ฏผ๋“ค์˜ ์ธ์‹์„ ํ–ฅ์ƒํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ถŒ์žฅํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋ณธ ๋””์ž์ธ ์—ฐ๊ตฌ๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”์—์„œ ๋ฏธํ•™๊ณผ ์ฐฝ์กฐ์ ์ธ ์‹ค์ฒœ์˜ ์—ญํ• ์— ๋Œ€ํ•œ ๋” ๋งŽ์€ ๋…ผ์˜๋ฅผ ์œ ๋„ํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค.Abstract I Table of Contents III List of Figures VI 1. Introduction 1 1.1 Research Background 2 1.2 Research Goal and Method 6 1.3 Terminology 9 2. Hierarchical Relationships: Trees 14 2.1 The History of Tree Diagrams 16 2.1.1 Significance of Trees 16 2.1.2 Aristotles Hierarchical Order of Life 19 2.1.3 Early Religious Depictions of Hierarchical Structures 22 2.1.4 Depicting Evolution 26 2.2 Tree Structures 29 2.3 Tree Layouts 31 3. Complex Relationships: Networks 34 3.1 Attributes of Networks 36 3.1.1 Interdependence and Interconnectedness 38 3.1.2 Decentralization 42 3.1.3 Nonlinearity 45 3.1.4 Multiplicity 46 3.2 Spatial Networks 46 3.3 Combining Tree Structures and Networks 48 4. Design Study Goals and Criteria 51 4.1 Objectives of the Design Study 71 4.2 Data Visualization Approaches 54 4.3 Criteria of Data Visualization 57 4.3.1 Aesthetics 58 4.3.2 Information Visualization Principles 62 4.3.2.1 Visual Cues in Data Visualization 62 4.3.2.2 Gestalt Principles 65 4.3.2.3 Increasing Efficiency of Network Visualizations 67 4.4 Case Study 70 5. Design Study: Data Garden Method 78 5.1 Concept of the Data Garden Structure 79 5.2 Data Garden Tree Structure 84 5.2.1 360ยฐVertical Branches 85 5.2.2 Break Point of the Branches 87 5.2.3 Aligning Hierarchy Levels 89 5.2.3.1 Design 01 โ€“ Extend Method 90 5.2.3.2 Design 02 โ€“ Collapse Method 91 5.2.4 Node Placement Technique 92 5.3 Conveying 3D Information 95 6. Design Study: Visualization Project 98 6.1 Theme 99 6.1.1 E-waste Trade 100 6.1.2 Environmental Performance Index 102 6.2 Visual Design Concept 104 6.3 Assigning Attributes 105 6.4 Visual Design Process 107 6.4.1 Leaf (Node) Design Process 107 6.4.1.1 Leaf Inspiration 107 6.4.1.2 Leaf Design 108 6.4.1.3 Leaf Area Calculation and Alignment 113 6.4.2 Stem (Branch) Design Process 116 6.4.3 Root (Link) Design Process 117 6.5 Interaction Design 118 6.5.1 Navigation 118 6.5.2 User Interface 119 6.5.3 Free and Detail Modes 120 6.5.4 Data Details 121 6.6 Visualization Renders 122 6.7 Exhibition 129 7. Conclusion 131 7.1 Conclusion 132 7.2 Limitations and Further Research 133 Bibliography 135 ๊ตญ๋ฌธ์ดˆ๋ก (Abstract in Korean) 144Docto
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