Graphics and Graphic Information Processing J. Bertin

1. Graphics and Graphic Information Processing J. Bertin Presented by Fusun Yaman

2. Overview • Introduction • Description of the paper • My favorite sentence • Contributions • Notes on the references • Critique • What happened to this topic

3. Introduction • Section from Graphics and Graphic Information Processing(1977/1981) • Problem addressed in section B • Collection of objects that are described by n characteristics • How to graphically represent this information when usually n > 3

4. Terminology • Information is in Data Table • Objects correspond to cases (A, B, C, D) • Characteristics correspond to variables (income,education, experience)

5. Terminology (continued) • Objects can be • Ordered (0) , like months • Reorderable (), like individuals • Topographic (T), like cities • Characteristics can be • Nominal, like movie titles • Ordinal, like movie ratings • Quantitative, like length of the movie

6. “Impassable barrier” • Image has only 3 dimensions • This barrier is impassable • Le n be number of variables (rows) • n 3 : Use scatter plots • n > 3: Other solutions needed

7. Solutions for n > 3 • Constructing several scatter plots • Sacrificing overall relationship • Constructing a matrix • Overall relationship is discovered by permutations

8. Synoptic • Classifies graphic constructions according to two properties of Data Table • If n is number of characteristics • n > 3 and n 3 • Nature of objects • Ordered , reorderable, topographic

10. Graphics for n 3 • Matrix construction when objects are reorderable

11. Graphics for n 3 • Arrays of curves when objects are ordered

12. Graphics for n 3 • Scatter plots for both reorderable and ordered cases • Third row is represented by the size of the marker (9)

13. Graphics for n 3 • In topographies bi- or tri-chromatic superimposition reveals the overall relation ships

14. Graphics for n > 3 • Objects and characteristics are reorderable () • Reorderable matrix • Objects are ordered, characteristics are reorderable • Image file (2) • Array of curves when slops are meaningful (3) • Ordered objects and characteristics • Collection of tables or maps (4,5) • Use super imposition to discover similar groups

15. Reorderable Matrix • Objects and characteristics are reorderable () • Permutable in x and y • Overall relationship is discovered by permutations • What if characteristics are not nominal?

16. Special Cases for () • Weighted matrix • Areas become meaningful • Applicable to a data table in which row and column totals are meaningful • Limited in dimension • Matrix-file • When one of the dimensions is too large • Constructed similar to image files • Use sorting to discover correlations

17. Image File • Used for ordered objects and reorderable characteristics • One card for each characteristic • Values greater than the mean of that row are darkened

18. Matrix-File • Special case for permutable matrix; one of the dimensions is too big. • Large number of objects across a small number of characteristics. • Constructed similar to image files • Use sorting to discover correlations

19. Matrix-File Example • Ordered by salary, origin, age • Higher salaries are paid to men, who are married, older and who have more childeren then others

20. Graphics for Networks • A network portrays the relationships that exists among the elements of a single component. • can also be represented in matrix form • If this component is • Reorderable: network is transformable on a plane (19) • Ordered: network is transformable on one dimension (20) • Topography: non-transformable; ordered network (21)

21. Utilization of Synoptic • Using synoptic choose the appropriate graphic construction for your data • Deviating from suggested construction leads to loss of information and requires justification • Size limitations

22. My favorite Sentence • “A problem involving n rows does not correspond to n problems involving one row.” • “[Graphics] is a strict and simple system of signs, which anyone can learn to use and which leads to better understanding.”

23. Contributions • Synoptic • Classification scheme for 2D graphical presentation • Permutation Matrix • General solution for more than 3 variables • (In the book) Identifies seven visual variables • Position,size, value, orientation, color, texture and shape

24. References • The book has no reference section! • Semiology of graphics: Diagrams, networks, maps, J. Bertin, 1967 • Identifies basic elements of diagrams • Describes a framework for their design

25. Critique • Strength of the paper • One image summerizes his all theory on graphic construction selection • Weakness of the paper • No 3D discussion • Not easy to follow, lack of examples (in the given section) • Outdated implementation techniques

26. What happened to this topic? • Formed a basis for research in Information Visualization • Graphical constructions and ideas presented in this section are implemented in information visualization tools • Tablelens (matrix file) • Spotfire (scatter plots using seven visual variables)

27. What happened to this topic? • Classification enabled auotomation studies • Automating the design of graphical presentations of relational information, Mackinlay • 1987 NSF report, DeFanti (uses the term visualization) • Extension to 3D graphics • Information Animation Applications in the capital markets, Wright • 1987 NSF report, DeFanti