Automating the Design of Graphical Presentations of Relational Information Jock MacKinlay Beth Weinstein March 14, 2001.

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Presentation transcript:

Automating the Design of Graphical Presentations of Relational Information Jock MacKinlay Beth Weinstein March 14, 2001

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 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.)

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 Expressive if include all data in the set include only data from the set identify graphical languages that express the desired information

Expressiveness Criteria

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

Expressiveness Criteria

Effectiveness Criteria

Composition Merge different encoding techniques not usually combined

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 “…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 MacKinlay - Ph.D. dissertation Cleveland and McGill General, well-cited references Tufte Knuth

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 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