Extending the dimensionality of flatland with attribute view probabilistic models

Eric Neufeld; Mikelis Bickis; Kevin Grant

doi:10.1117/12.767279

28 January 2008 Extending the dimensionality of flatland with attribute view probabilistic models

Eric Neufeld, Mikelis Bickis, Kevin Grant

Proceedings Volume 6809, Visualization and Data Analysis 2008; 680905 (2008) https://doi.org/10.1117/12.767279
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

In much of Bertin's Semiology of Graphics, marks representing individuals are arranged on paper according to their various attributes (components). Paper and computer monitors can conveniently map two attributes to width and height, and can map other attributes into nonspatial dimensions such as texture, or colour. Good visualizations exploit the human perceptual apparatus so that key relationships are quickly detected as interesting patterns. Graphical models take a somewhat dual approach with respect to the original information. Components, rather than individuals, are represented as marks. Links between marks represent conceptually simple, easily computable, and typically probabilistic relationships of possibly varying strength, and the viewer studies the diagram to discover deeper relationships. Although visually annotated graphical models have been around for almost a century, they have not been widely used. We argue that they have the potential to represent multivariate data as generically as pie charts represent univariate data. The present work suggests a semiology for graphical models, and discusses the consequences for information visualization.

Citation Download Citation

Eric Neufeld, Mikelis Bickis, and Kevin Grant "Extending the dimensionality of flatland with attribute view probabilistic models", Proc. SPIE 6809, Visualization and Data Analysis 2008, 680905 (28 January 2008); https://doi.org/10.1117/12.767279

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available