automating the design of graphical presentations of relational information
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Automating the Design of Graphical Presentations of Relational Information Jock MacKinlay Beth Weinstein March 14, 2001 Paper Outline Introduction Expressiveness Effectiveness Composition Implementation

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automating the design of graphical presentations of relational information

Automating the Design of Graphical Presentations of Relational Information

Jock MacKinlay

Beth Weinstein

March 14, 2001

paper outline
Paper Outline
  • Introduction
  • Expressiveness
  • Effectiveness
  • Composition
  • Implementation
introduction
Previously application designers had to anticipate every situation and “predesign” graphic designs

In related work, the BHARAT system, automatically creates 2D graphical designs based on the data type. For example, the system automatically chose to show the data as a line chart if the data was continuous.

Introduction
introduction4
Introduction
  • MacKinlay’s goal was to build a presentation tool (APT) that would create a graphic design that would express relations and their basic properties effectively
  • APT would have the best way to view 2-D data using expressiveness and effectiveness criteria. The paper focuses on 2-D static presentations of relational data (scatter plots, bar charts, etc.)
introduction5
Introduction
  • Three types of data
    • ordinal (Monday, Tuesday, Wednesday)
    • nominal (United States, Mexico, Canada)
    • quantitative (1, 2, 3)
  • Problems could arise when there are multiple and conflicting criteria for a data set
expressiveness criteria
Expressiveness Criteria

identify graphical languages that express the desired information

  • Expressive if
    • include all data in the set
    • include only data from the set
effectiveness criteria
Effectiveness Criteria

identify which graphical languages is most effective at using the output and human capabilities

  • Based on human perceptual capabilities
  • Graphical design interpreted quickly and accurately
  • Cleveland and McGill’s conjectural theory - different graphical designs are interpreted by people with varying accuracy
composition
Composition
  • Merge different encoding techniques not usually combined
implementation
Implementation
  • Partitioning
    • A divide and conquer algorithm
    • Partition on most important element
  • Selection
    • For each partition, a list of graphic design is generated based on expressiveness criteria
    • Then, the list is ordered by the effectiveness criteria
  • Composition
    • Each partition’s graphic design is tested to see if they both can be applied, if not the next most effective graphic design is used
favorite sentence
Favorite Sentence

“…an important responsibility of a user interface is to make intelligent use of human visual abilities and output media whenever it presents information to the user.”

reference notes
Reference Notes
  • MacKinlay - Ph.D. dissertation
  • Cleveland and McGill
  • General, well-cited references
    • Tufte
    • Knuth
critique
Critique
  • Strengths
    • Proves that a graphical design may not be appropriate for all types of data
    • Gives a criteria for perceptual tasks
  • Weaknesses
    • Vague on how extended Cleveland and McGill’s criteria
    • Composition algebra unnecessary
contributions
Contributions
  • Provides a ranking of perceptual tasks for nominal, ordinal, and quantitative data
  • Contributes a new graphical designs by combining perceptual tasks
  • Creates a tool that will create expressive and effective graphical designs based on the data
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