Paper Info
Title
The Visual Representation of Information Structures
Abstract
It is proposed that research into human perception can be applied in designing ways to represent structured information. This idea is illustrated with four case studies. (1) How can we design a graph so that paths can be discerned? Recent results in the perception of contours can be applied to make paths easier to perceive in directed graphs. (2) Should we be displaying graphs in 3D or 2D space? Research suggests that larger graphs can be understood if stereo and motion parallax depth cues are available. (3) How can heterogeneous information structures be best represented? Experiments show using structured 3D shape primitives make diagrams that are easier to discover and remember. (4) How can causal relationships be displayed? Michotte's work on the perception of causality suggests that causal relationships can be represented using simple animations. The general point of these examples is that data visualization can become a science based on the mapping of data structures to visual representations. Scientific methods can be applied both in the development of theory and testing the value of different representations.
Year
DOI
Venue
2000
10.1007/3-540-44541-2_1
Graph Drawing
Keywords
Field
DocType
information structures,motion parallax depth cue,causal relationship,human perception,visual representation,general point,data visualization,different representation,case study,heterogeneous information structure,data structure,larger graph,scientific method,directed graph,generic point,motion parallax
Information structure,Data structure,Data visualization,Parallax,Computer science,Directed graph,Theoretical computer science,Artificial intelligence,Depth perception,Perception,Visual perception,Distributed computing
Conference
ISBN
Citations 
PageRank 
3-540-41554-8
0
0.34
References 
Authors
3
1
Name
Order
Citations
PageRank
Colin Ware101.35