graphics and graphic information processing j. bertin

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

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Graphics and Graphic Information Processing J. Bertin. Presented by Fusun Yaman. Overview. Introduction Description of the paper My favorite sentence Contributions Notes on the references Critique What happened to this topic. Introduction. - PowerPoint PPT Presentation

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Page 1: Graphics and  Graphic Information Processing  J. Bertin

Graphics and Graphic Information Processing

J. Bertin

Presented by Fusun Yaman

Page 2: Graphics and  Graphic Information Processing  J. Bertin

Overview

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

Page 3: Graphics and  Graphic Information Processing  J. Bertin

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

Page 4: Graphics and  Graphic Information Processing  J. Bertin

Terminology

Information is in Data Table Objects correspond to cases (A, B, C, D) Characteristics correspond to variables

(income,education, experience)

A B C DIncomeEducationExperience

Page 5: Graphics and  Graphic Information Processing  J. Bertin

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

Page 6: Graphics and  Graphic Information Processing  J. Bertin

“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

Page 7: Graphics and  Graphic Information Processing  J. Bertin

Solutions for n > 3

Constructing several scatter plots Sacrificing overall relationship

Constructing a matrix Overall relationship is discovered by

permutations

Page 8: Graphics and  Graphic Information Processing  J. Bertin

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

Page 9: Graphics and  Graphic Information Processing  J. Bertin
Page 10: Graphics and  Graphic Information Processing  J. Bertin

Graphics for n 3

Matrix construction when objects are reorderable

Page 11: Graphics and  Graphic Information Processing  J. Bertin

Graphics for n 3

Arrays of curves when objects are ordered

Page 12: Graphics and  Graphic Information Processing  J. Bertin

Graphics for n 3

Scatter plots for both reorderable and ordered cases

Third row is represented by the size of the marker (9)

Page 13: Graphics and  Graphic Information Processing  J. Bertin

Graphics for n 3

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

Page 14: Graphics and  Graphic Information Processing  J. Bertin

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

Page 15: Graphics and  Graphic Information Processing  J. Bertin

Reorderable Matrix

Objects and characteristics are reorderable () Permutable in x and y Overall relationship is discovered by permutations

What if characteristics are not nominal?

Page 16: Graphics and  Graphic Information Processing  J. Bertin

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

Page 17: Graphics and  Graphic Information Processing  J. Bertin

Image File

Used for ordered objects and reorderable characteristics

One card for each characteristic

Values greater than the mean of that row are darkened

Page 18: Graphics and  Graphic Information Processing  J. Bertin

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

Page 19: Graphics and  Graphic Information Processing  J. Bertin

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

Page 20: Graphics and  Graphic Information Processing  J. Bertin

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)

Page 21: Graphics and  Graphic Information Processing  J. Bertin

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

Page 22: Graphics and  Graphic Information Processing  J. Bertin

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.”

Page 23: Graphics and  Graphic Information Processing  J. Bertin

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

PositionSizeValue

Texture

Color

OrientationShape

Page 24: Graphics and  Graphic Information Processing  J. Bertin

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

Page 25: Graphics and  Graphic Information Processing  J. Bertin

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

Page 26: Graphics and  Graphic Information Processing  J. Bertin

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)

Page 27: Graphics and  Graphic Information Processing  J. Bertin

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