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Information Graphics (Draft)
 

Information Graphics (Draft)

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Information Graphics (Draft) Information Graphics (Draft) Presentation Transcript

  • Information Graphics Jeff McNeill University of Hawaii at Manoa 2007 Copyright © Jeff McNeill, 2007 Licensed under Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/
  • Overview
    • This is an overview of information graphics, good, bad and ugly
    • These can be extremely helpful in walkthrough and summary slides
  • List of Information Graphics
    • 2 x 2 chart
    • Bar chart
    • Concept map
    • Diagram
    • Gannt chart
    • Line chart
    • Map
    • Org chart
    • Parallel coordinates
    • Pert chart
    • Process map
    • Scatter plot
    • Table
    • Tag cloud
    • Venn diagram
    • Meaningful elements
      • Color
      • Size
      • Location
      • Connections (lines)
      • Directionality (arrows)
      • Degree of overlap
      • Proximity
      • Order
      • Label
      • Scale
    • Do not use
      • Radar diagram
        • Parallel coordinates instead
      • Pie chart
        • Bar chart instead
  • Information Graphics Descriptions * Included in the Notetaking Toolkit. Drawing illustrating parts and relationships Diagram Individual time assignments (project management) Pert chart Usually 2 dimensional plotting, shows clusters Scatter plot 2 dimensions by 2 measurements 2 x 2 chart* 2+ items with overlapping and non- parts Venn diagram* Shows frequency, centrality, importance of terms Tag cloud The basic structured way of comparing items Table* Shows steps in a process, left-to-right with arrows Process map* For 3 or more dimensions, better than radar diagrams or multiple bar or 2 x 2 charts Parallel coordinates Don’t confuse with concept map, only for orgs Org chart Geographical or any 2d space plotting Map Like bar chart but shows slope between datapoints Line chart* (Project management) shows dependencies & time Gannt chart Shows connections and relationships Concept map* One or more measures, can be comparative Bar chart
  • Graphics Concepts
    • Chartjunk
    • Data-to-ink ratio
    • Colorblindness
  • Notetaking Toolkit
    • This toolkit identifies information graphics which are easy to create on the fly when taking notes
    • These should be mastered first and can be useful in gathering information, not just in presenting
    • Includes the 2 x 2 chart, Concept map, Line chart, Process map, Table, and Venn diagram
  • 2 x 2 Chart*
    • Simplified version of the Line chart
    • Can be used as a Scatter plot overlay
    • It divides each of two dimensions into two levels, usually low and high
    • Quadrants
    • Most desirable
      • Upper right
    * Included in the Notetaking Toolkit. low low high high second dimension first dimension
  • 2 x 2 Chart* Components
    • Components
      • Datapoints
      • X and Y Axes
      • X and Y Axes Labels
      • X and Y Axes Level Labels
      • Partition lines into quadrants
      • Datapoint labels (or legend)
    • Variations
      • Datapoints can be scatterplot along interval scales or simply categories
    low low high high Different Good Good but not different Not good and not different Different but not good Good and different
  • Bar Chart * Included in the Notetaking Toolkit.
  • Concept Map*
    • Hierarchical composition of elements
    • Visualizes connections between elements (concepts and examples)
    • Can be read to form sentences
    • Superior to “mind mapping” (Buzan)
    • From Novak based on Ausubel
    • Similar to process map, which indicates horizontal, time-ordered relationships
    • Useful for component decomposition
    * Included in the Notetaking Toolkit.
  • Concept Map* Components
    • Elements (circles)
    • Element labels (inside element)
    • Relationships (lines w/ arrows)
    • Relationship labels (optional)
    • Vertical placement
      • Indicates hierarchy
      • Use bottom-up arrows for Goldratt reality trees
    • See also Process map
    * Included in the Notetaking Toolkit. Food Bean Nut Peanut Almond Examples Includes
  • http://www.mc.maricopa.edu/dept/d43/glg/Study_Aids/concept_maps/conceptmaps.html
  • http://www.mc.maricopa.edu/dept/d43/glg/Study_Aids/concept_maps/conceptmaps.html
  • Diagram * Included in the Notetaking Toolkit.
  • Gannt Chart
  • Line Chart*
    • Similar to the 2 x 2 and chart plots
    • Like bar chart but with slope
    • Usually uses ratio data (interval w/ zero)
    • Can show relationship between two or more variables on different scales
    * Included in the Notetaking Toolkit. then less now more Choices Time
    • X and Y axes
    • X and Y axes labels
    • One or more lines
    • Data set (optional)
    • Scale indicator labels
    • Scale indicators (optional)
    • Variable labels or legend
    • Projected values (optional) (dotted lines)
    Line Chart* Components * Included in the Notetaking Toolkit. 2005 0 1,000 Choices Time 500 2006 2007 220 310 570 680 580 400 750 250
  • Map
  • Org Chart
    • Typically squares and straight lines
    • Do not use org chart look for non org charts
    • See sociogram (type of concept map)
    • Components include positions and/or persons
    • Hierarchical order
    • Boss and direct reports
    • Support staff off to side
    President Chris Charlie VP Alice Alfa VP Bob Bravo Assistant Don Delta
  • Parallel Coordinates http://www.nbb.cornell.edu/neurobio/land/PROJECTS/Inselberg/ Parallel Coordinates V L F R High Medium High High Virtual World Low Medium Medium High Online Low Low Low Low Classroom Fantastic Robotic Ludic Virtual
  • Radar Diagram (Do Not Use) Radar Diagram V L F R Use parallel coordinates instead http://www.internet4classrooms.com/excel_radar.htm High Medium High High Virtual World Low Medium Medium High Online Low Low Low Low Classroom Fantastic Robotic Ludic Virtual
  • Pert Chart
  • Process Map*
    • Shows parts and steps
    • Similar to GANTT chart, which shows dependencies and a timeline
    * Included in the Notetaking Toolkit. Step 1 Step 2 Step 3
  • Scatter Plot
  • Table*
    • Extremely flexible and useful
    • Can be used whenever there are two or more things to compare/contrast
    • Columns, rows, headers, and data
    • Primary data collection is row
    • Variables and values are columns
    • Center and align when appropriate
    • Headers usually bold
    • Order of elements
      • Time, importance, alphabetical
    * Included in the Notetaking Toolkit.
  • Table* Examples
    • Data collection units are ususally rows
    • Totals go down rows (vs. across columns)
    • Any information can be placed in tables
    • Increases speed and accuracy of understanding and visual comparisons
    * Included in the Notetaking Toolkit. Incorrect Correct Sold Weight Cost 2,000 1,000 50 lbs 100 lbs $2.00 $1.00 Ver 2 Ver 1 3,000 2,000 1,000 Sold Total 50 lbs 100 lbs Weight Ver 2 Ver 1 Version $5,000 $4,000 $2.00 $1,000 $1.00 Sales Cost
  • Tag (Text) Cloud
    • Alphabetical or some other meaningful arrangement
    • Meaningful dimensions
      • Size = frequency
      • Color = time (or other), optional
      • Proximity = similarity
    • Advanced versions become similar to multidimensional cluster plots
  • Tag (Text) Cloud Steve Jobs 2007 Macworld Conference Avg. Words/Sentence: 10.5 Lexical Density : 16.5% Hard Words : 2.9% Gunning Fog Index : 5.5 Bill Gates 2007 Consumer Electronics Show Avg. Words/Sentence: 21.6 Lexical Density : 21.0% Hard Words : 5.11% Gunning Fog Index : 10.7
    • Indicates commonality and difference
    • Overlaps share or combine qualities
    Venn Diagram* Ice Cream Cake Chocolate Chocolate Ice Cream Cake
  • Additional Notes
  • Information Visualization CMSC 838B – Spring 2003 Visual Design Benjamin B. Bederson University of Maryland www.cs.umd.edu/~bederson This presentation adapted from John Stasko
  • Semiotics
    • The study of symbols and how they convey meaning
    • Classic book:
      • J. Bertin, 1983, The Semiology of Graphics
    This presentation taken largely from John Stasko
  • Related Disciplines
    • Psychophysics
      • Applying methods of physics to measuring human perceptual systems
        • How fast must light flicker until we perceive it as constant?
        • What change in brightness can we perceive?
    • Cognitive psychology
      • Understanding how people think, here, how it relates to perception
  • Potential Preattentive Features length width size curvature number terminators intersection closure hue intensity flicker direction of motion binocular lustre stereoscopic depth 3-D depth cues lighting direction
  • Key Perceptual Properties
    • Brightness
    • Color
    • Texture
    • Shape
  • Luminance/Brightness
    • Luminance
      • Measured amount of light coming from some place
    • Brightness
      • Perceived amount of light coming from source
  • Color for Categories
    • Can different colors be used for categories of nominal variables?
      • Yes
      • Ware’s suggestion: 12 colors
        • red, green, yellow, blue, black, white, pink, cyan, gray, orange, brown, purple
  • Color Categories
    • Are there certain canonical colors?
      • Post & Greene ‘86 had people name different colors on a monitor
      • Pictured are ones with > 75% commonality
  • Color for Sequences Can you order these (low->hi)
  • Possible Color Sequences Gray scale Single sequence part spectral scale Full spectral scale Single sequence single hue scale Double-ended multiple hue scale
  • Color Purposes
    • Call attention to specific data
    • Increase appeal, memorability
    • Increase number of dimensions for encoding data
      • Example, Ware and Beatty ‘88
        • x,y - variables 1 & 2
        • amount of r,g,b - variables 3, 4, & 5
  • 1. Graph
    • Graph - Show the relationships between variables’ values in a data table
      • Visual display that illustrates one or more relationships among entities
      • Shorthand way to present information
      • Allows a trend, pattern or comparison to be easily comprehended
  • Issues
    • Critical to remain task-centric
      • Why do you need a graph?
      • What questions are being answered?
      • What data is needed to answer those questions?
      • Who is the audience?
    time money
  • Graph Components
    • Framework
      • Measurement types, scale
    • Content
      • Marks, lines, points
    • Labels
      • Title, axes, ticks
  • Basic Data Types
    • Nominal (qualitative)
      • (no inherent order)
      • city names, types of diseases, ...
    • Ordinal (qualitative)
      • (ordered, but not at measurable intervals)
      • first, second, third, …
      • cold, warm, hot
    • Interval (quantitative)
      • list of numbers
  • Common Graph Formats Line graph Bar graph Scatter plot Y-axis is quantitative variable See changes over consecutive values Y-axis is quantitative variable Compare relative point values Two variables, want to see relationship Is there a linear, curved or random pattern?
  • Graphing Guidelines
    • Independent vs. dependent variables
      • Put independent on x-axis
      • See resultant dependent variables along y-axis
    • If there are two independent variables, often place them along the 2 axes (you choose which) and then the mark may encode the dependent variable
  • 2. Chart
    • Structure is important, relates entities to each other
    • Primarily uses lines, enclosure, position to link entities
    Examples: flowchart, family tree, org chart, ...
  • 3. Map
    • Representation of spatial relations
    • Locations identified by labels
  • Choropleth Map Areas are filled and colored differently to indicate some attribute of that region
  • Cartography
    • Cartographers and map-makers have a wealth of knowledge about the design and creation of visual information artifacts
      • Labeling, color, layout, …
    • Information visualization researchers should learn from this older, existing area
  • 4. Diagram
    • Schematic picture of object or entity
    • Parts are symbolic
    Examples: figures, steps in a manual, illustrations,...
  • Tufte’s Design Principles
    • 1. Tell the truth
      • Graphical integrity
    • 2. Do it effectively with clarity, precision…
      • Design aesthetics
    E. Tufte , The Visual Display of Quantitative Information (1983) E. Tufte , Envisioning Information (1990) E. Tufte , Visual Explanations (1997)
  • 1. Graphical Integrity 2002 2001 2000 1999 1998 500 475 450 Stock market crash?
    • Your graphic should tell the truth about your data
  • Show entire scale 2002 2001 2000 1999 1998 500 250 0
  • Show in context 2000 1990 1980 1970 1960 500 250 0
  • Measuring Misrepresentation
    • Visual attribute value should be directly proportional to data attribute value
    • Height/width vs. area vs. volume
    Size of effect shown in graphic Size of effect in data Lie factor = “ Lie factor” = 2.8
  • 2. Design Principles
    • Maximize data-ink ratio
    Data ink ratio = Data ink Total ink used in graphic = proportion of graphic’s ink devoted to the non-redundant display of data-information
  • Design Principles
    • Avoid chartjunk
      • Extraneous visual elements that detract from message
    don’t be the duck of architecture
  • Design Principles
    • Utilize multifunctioning graphical elements
      • Graphical elements that convey data information and a design function
  • Design Principles
    • Use small multiples
      • Repeat visually similar graphical elements nearby rather than spreading far apart
  • Design Principles
    • Show mechanism, process, dynamics, and causality
      • Cause and effect are key
  • Design Principles
    • Escape flatland
      • Data is multivariate
      • Doesn’t necessarily mean 3D projection
  • Design Principles
    • Utilize layering and separation
  • Design Principles
    • Utilize narratives of space and time
      • Tell a story of position and chronology through visual elements
  • Design Principles
    • Content is king
      • Quality, relevance and integrity of the content is fundamental
      • What’s the analysis task? Make the visual design reflect that
      • Integrate text, chart, graphic, map into a coherent narrative
  • Graph and Chart Tips
    • Avoid separate legends and keys – Put that in the graphic
    • Make grids & labeling faint so that they recede into background
  • Proper Color Use
    • To label
    • To measure
    • To represent or imitate reality
    • To enliven or decorate
  • Color Examples
  • Guides for Enhancing Visual Quality
    • Attractive displays of statistical info
      • have a properly chosen format and design
      • use words, numbers and drawing together
      • reflect a balance, a proportion, a sense of relevant scale
      • display an accessible complexity of detail
      • often have a narrative quality, a story to tell about the data
      • are drawn in a professional manner, with the technical details of production done with care
      • avoid content-free decoration, including chartjunk
  • Graphical Displays Should
    • Show the data
    • Induce the viewer to think about substance rather than about methodology, graphic design the technology of graphic production, or something else
    • Avoid distorting what the data have to say
    • Present many numbers in a small space
    • Make large data sets coherent
    • Encourage the eye to compare different pieces of data
    • Reveal the data at several levels of detail, from a broad overview to the fine structure
    • Serve a reasonably clear purpose: description, exploration, tabulation, or decoration
    • Be closely integrated with statistical and verbal descriptions of a data set