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


Introduction

Description of the paper

My favorite sentence

Contributions

Notes on the references

Critique

What happened to this topic


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


Information is in Data Table

Objects correspond to cases (A, B, C, D)

Characteristics correspond to variables
(income,education, experience)
A B C D
Income
Education
Experience


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


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


Constructing several scatter plots

Sacrificing overall relationship

Constructing a matrix

Overall relationship is discovered by permutations


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



Matrix construction when objects are reorderable



Arrays of curves when objects are ordered



Scatter plots for both reorderable and ordered cases

Third row is represented by the size of the marker (9)



In topographies bi- or tri-chromatic superimposition reveals the overall relation ships


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


Objects and characteristics are reorderable (

)

Permutable in x and y

Overall relationship is discovered by permutations

What if characteristics are not nominal?

(

)

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


Used for ordered objects and reorderable characteristics

One card for each characteristic

Values greater than the mean of that row are darkened


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


Ordered by salary, origin, age

Higher salaries are paid to men, who are married, older and who have more childeren then others


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)


Using synoptic choose the appropriate graphic construction for your data

Deviating from suggested construction leads to loss of information and requires justification

Size limitations

 “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.”


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
Texture
Position
Color
Size
Orientation
Value
Shape


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

 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


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)


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