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Designing Data Visualizations : Representing Informational Relationships.

Author: Julie Steele; Noah Iliinsky
Publisher: Sebastopol : O'Reilly Media, 2011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Data visualization is an efficient and effective medium for communicating large amounts of information, but the design process can often seem like an unexplainable creative endeavor. This concise book aims to demystify the design process by showing you how to use a linear decision-making process to encode your information visually. Delve into different kinds of visualization, including infographics and visual art,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Steele, Julie.
Designing Data Visualizations : Representing Informational Relationships.
Sebastopol : O'Reilly Media, ©2011
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Julie Steele; Noah Iliinsky
ISBN: 9781449317430 144931743X 9781449312282 1449312284
OCLC Number: 775301799
Notes: Analyze Patterns and Consistency.
Description: 1 online resource (110 pages)
Contents: Table of Contents; Preface; How This Book Is Organized; What We Mean When We Say ... ; Figures Used by Permission; See the Color Figures Online; Attributions and Permissions; Safari® Books Online; How to Contact Us; Acknowledgments; Part I. What Will You Design?; Chapter 1. Classifications of Visualizations; Complexity; Infographics versus Data Visualization; Infographics; Data Visualization; Exploration versus Explanation; Exploration; Explanation; Hybrids: Exploratory Explanation; Informative versus Persuasive versus Visual Art; The Designer-Reader-Data Trinity; Informative; Persuasive. Visual ArtChapter 2. Source Trinity: Ingredients of Successful Visualizations; Designer; Why Are You Here?; Reader; You Are Creating This for Other People; They Are Not You; Contextual Considerations for the Reader; Context of Use; Data; Part II. How Should You Design It?; Chapter 3. Determine Your Goals and Supporting Data; Knowledge Before Structure; Avoiding TMI; Chapter 4. Choose Appropriate Visual Encodings; Choosing Appropriate Visual Encodings; Natural Ordering; Color is not ordered; Distinct Values; Redundant Encoding; Defaults versus Innovative Formats; Readers' Context. Titles, tags, and labelsColors; Color blindness; Directional orientation; Compatibility with Reality; Direction and reality; Patterns and Consistency; Selecting Structure; Comparisons Need to Compare; Some Structures Are Just Inherently Bad; Some Good Structures Are Often Abused; Keep It Simple (or You Might Look) Stupid; Chapter 5. First, Place; Position: Layout and Axes; Position Is Your Most Powerful Encoding; Consider placement first; The Meaning of Placement and Proximity; Semantic Distance and Relative Proximity; Absolute Placement; Representation of Physical Space. Logical Relationships versus Physical RelationshipsPatterns and Grouped Objects; Patterns of Organization (and More!); Specific Graphs, Layouts, and Axis Styles; Quantitative and comparative formats; Relational formats; Spatial formats; Appropriate Use of Circles and Circular Layouts; Good uses of circles and circular layouts; Bad uses of circles and circular layouts; Chapter 6. Apply Your Encodings Well; Color; Leverage Common Color Associations; Cognitive Interference and the Stroop Test; Color Theory; Spatial perception of color; RGB versus CMYK; Size; Conveying Size; Comparing Sizes. Text and TypographyUse Text Sparingly; Fonts and Hierarchies; Beware of All Caps; Avoid Drop Shadows; Shape; Cultural Connotations; Icons; Illusions; Lines; When Not to Use Lines; Keys versus Direct Labeling of Data Points; Pitfalls to Avoid; 3D; Pies; Gradients; Drop Shadows; Any Excel Defaults; Conclusion; Appendix A. Additional Resources; Tools?; Reading List?; Appendix B. Checklist; Determine Your Goals and Supporting Data; Consider Your Reader; Select Axes, Layout, and Placement; Evaluate Your Encoding Entities; Reveal the Data's Relationships; Choose Titles, Tags, and Labels.

Abstract:

Data visualization is an efficient and effective medium for communicating large amounts of information. This book aims to demystify the design process for those who are already comfortable with data  Read more...

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