Title
Representational correspondence as a basic principle of diagram design
Abstract
The timeworn claim that a picture is worth a thousand words is generally well-supported by empirical evidence, suggesting that diagrams and other information graphics can enhance human cognitive capacities in a wide range of contexts and applications. But not every picture is worth the space it occupies. What qualities make a diagram an effective and efficient conduit of information to the human mind? In this article we argue that the best diagrams depict information the same way that our internal mental representations do. That is, “visual thinking” operates largely on relatively sketchy, cartoon-like representations of the physical world, translating sensory input into efficient codes before storing and manipulating it. Effective diagrams will assist this process by stripping away irrelevant detail while preserving or highlighting essential information about objects and their spatial relations. We discuss several examples that illustrate this “Representational Correspondence Principle,” and we consider its implications for the design of systems that use diagrams to represent abstract, conceptual knowledge, such as social networks, financial markets, or web content hierarchies.
Year
DOI
Venue
2005
10.1007/11510154_3
Knowledge and Information Visualization
Keywords
Field
DocType
efficient conduit,human cognitive capacity,diagram design,representational correspondence,human mind,representational correspondence principle,essential information,basic principle,information graphics,effective diagram,best diagram,efficient code,cartoon-like representation,empirical evidence,correspondence principle,social network,financial market,mental representation,spatial relation
Graphics,Spatial relation,Knowledge representation and reasoning,Visualization,Cognitive science,Computer science,Artificial intelligence,Knowledge engineering,Visual thinking,Web content,Distributed computing,Mental representation
Conference
Volume
ISSN
ISBN
3426
0302-9743
3-540-26921-5
Citations 
PageRank 
References 
11
0.70
1
Authors
2
Name
Order
Citations
PageRank
Christopher F. Chabris14710.69
Stephen M. Kosslyn27083.11