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Data Display Techniques

Data Display Techniques. Christine R. Curran, PhD, RN, CNA October, 2001. Data Versus Information. How does one determine which display format to use: Text, Table, Graph, Other…? How does display content / “ink” affect the amount of information obtained? rounding of numbers

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Data Display Techniques

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  1. Data Display Techniques Christine R. Curran, PhD, RN, CNA October, 2001 (c) Chris Curran, 2001

  2. Data Versus Information • How does one determine which display format to use: Text, Table, Graph, Other…? • How does display content / “ink” affect the amount of information obtained? • rounding of numbers • Labels: when and where • use of white space • How does color affect our ability to “see” information? (c) Chris Curran, 2001

  3. Human Cognitive Processes • Humans want to organize data • The human mind operates by association • Humans process data through data reduction strategies • Chunking of data • Pattern recognition & exceptions to patterns are used to make judgments • Analogy & metaphor are often used in learning & recall of information

  4. Data Displays Should Facilitate • Perception of salient features • Comprehension of information • Recall of the information (c) Chris Curran, 2001

  5. Data Versus Information • Methods used to glean information from the volumes of data available to us: • tools (calculators, computers) • decision support systems • data presentation (c) Chris Curran, 2001

  6. How to Choose a Display Format The data and the type of task drive the choice of display format (c) Chris Curran, 2001

  7. Words Headings Text Numbers Digital Numeric Table Analog Picture Graph Icon Video Types of Data Displays (c) Chris Curran, 2001

  8. Words • Avoid all capital letters • Use labels or symbols rather than a “key” • Use Serif font for text • Use San-serif font for headings (c) Chris Curran, 2001

  9. TITLE Text should be displayed in Serif font. One should avoid all capital letters. Title Text should be displayed in Serif font. One should avoid all capital letters. Text: Samples (c) Chris Curran, 2001

  10. Digital task: symbolic data: discrete, quantitative focus:specific process: analysis display: table Analog task: spatial data: continuous, qualitative focus:holistic process: perception display: graph, icon Properties of Numerical Data Displays (c) Chris Curran, 2001

  11. Principles of Numerical Data Displays • Arrange data to convey meaning • proximity of data • use of white space • navigation • Make patterns and exceptions within the data obvious at a glance (seeing the data) • rounding • labeling & spacing • display format (c) Chris Curran, 2001

  12. Digital Display: Tables • Use in small data sets (20 numbers to be displayed or less) • Used to display numbers (c) Chris Curran, 2001

  13. Rules for Table Displays Ehrenberg, 1977 • Round to 2 significant or effective digits • eliminate leading “0” • trailing “0” does not matter • Put figures to be compared in columns rather than in rows • Add row & column averages (make the main effects explicit) • Order rows & columns by size • Show larger numbers above smaller numbers (c) Chris Curran, 2001

  14. Rules for Table Displays Ehrenberg, 1977 • Spacing & layout • White space is your friend • Use white space to signal the chunks of data • Single spacing guides the eye down the column • Use gaps (white space) between groups (columns or rows) to guide the eye across the data & to cluster data • Data meant to be compared should be close together (c) Chris Curran, 2001

  15. Data Rounding “Anyone who cannot learn to cope with rounding errors will probably not get much out of statistical data” Ehrenberg, 1977, pg. 282 (c) Chris Curran, 2001

  16. Principle The Data should drive the order of the presentation. Displays should not be configured by the structure of the data collection methodology or analysis. (c) Chris Curran, 2001

  17. Table: Example (c) Chris Curran, 2001

  18. Table: Revised Example (c) Chris Curran, 2001

  19. Correlation Matrix: Example (c) Chris Curran, 2001

  20. Correlation Matrix: Example (c) Chris Curran, 2001

  21. Correlation Matrix: Revised Example (c) Chris Curran, 2001

  22. Graphical Data Display: A Form of Decision Support Goals • find relevant data in a dynamic environment • visualize the semantics of the domain • reconceptualize the nature of the problem (Bennett, Toms & Woods, 1993) (c) Chris Curran, 2001

  23. The Power of a Graph Enables one to take in quantitative information in a qualitative way, organize it, and see patterns and structure not readily revealed by other means. (c) Chris Curran, 2001

  24. Graphical Perception The process of visual decoding of quantitative and categorical data from a graph. Cleveland, 1984 (c) Chris Curran, 2001

  25. Analog Display: Graphs • Used to display large datasets • Types of Graphs: Universal - Literal Continuum (c) Chris Curran, 2001

  26. Universal Graph: Example (c) Chris Curran, 2001

  27. Literal Graph (c) Chris Curran, 2001

  28. Graphical Design Concepts & Principles • Semantic Mapping (Roscoe, 1968; Kosslyn, 1989) • Configural Displays (Garner, 1970) • Chunking (Newell & Simon, 1973) • Theory of Graph Comprehension (Pinker, 1981) • 8 Visual Variables (Bertin, 1981) • Emergent Features (Pomerantz, 1981) • Data-Ink Ratio & Small Multiple (Tufte, 1983,1990, 1997) • Elementary Perceptual Tasks (Cleveland & McGill, 1984) • Proximity Compatibility (Wickens, 1986) • Metaphor Graphics (Cole, 1988) • Cognitive Fit (Vessey, 1991) (c) Chris Curran, 2001

  29. Design Principles for Computer Displays (Cole, 1994) • Design for the analog mind and both hemispheres • Design for correct encoding of information (represent the user’s model) • Provide a clear context (c) Chris Curran, 2001

  30. Graphic Design (c) Chris Curran, 2001

  31. Visual Decoding of Graphs Requires Pattern Perception Pattern perception requires: detection visual grouping of a pattern estimation (c) Chris Curran, 2001

  32. Elementary Perceptual Tasks(ordered from most to least accurate) • Position along a common scale • Positions along nonaligned scales • Length, Direction, Angle • Area • Volume, Curvature • Shading, Color Saturation Cleveland & McGill, 1984 (c) Chris Curran, 2001

  33. Position Along a Common Scale (c) Chris Curran, 2001

  34. Position Along Non-Aligned Scales (c) Chris Curran, 2001

  35. Length (c) Chris Curran, 2001

  36. Direction (c) Chris Curran, 2001

  37. Angle (c) Chris Curran, 2001

  38. Area (c) Chris Curran, 2001

  39. Volume (c) Chris Curran, 2001

  40. Curvature (c) Chris Curran, 2001

  41. Shading (c) Chris Curran, 2001

  42. Color Saturation (c) Chris Curran, 2001

  43. 10 10 10 0 0 0 COLOR SATURATION Elementary Perceptual TasksCleveland & McGill, 1984 (c) Chris Curran, 2001

  44. Common Graphs by Elementary Perceptual Task (c) Chris Curran, 2001

  45. Recommendations: Based on Graphical Perception • Parts of a Whole • dot chart • grouped dot chart • bar charts (instead of divided bars or pie charts) • Framed Rectangle Charts (instead of Shaded Statistical Maps Cleveland & McGill, 1984 (c) Chris Curran, 2001

  46. Dot Chart (c) Chris Curran, 2001

  47. Grouped Dot Chart (c) Chris Curran, 2001

  48. Bar Charts (c) Chris Curran, 2001

  49. Grouped Bar Chart (c) Chris Curran, 2001

  50. Divided Bar Chart (c) Chris Curran, 2001

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