Classifying visual knowledge representations: A foundation for visualization research

Jerry Lohse, Henry Rueter, Kevin Biolsi, Neff Walker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An exploratory effort to classify visual representations into homogeneous clusters is discussed. The authors collected hierarchical sorting data from twelve subjects. Five principal groups of visual representations emerged from a cluster analysis of sorting data: graphs and tables, maps, diagrams, networks, and icons. Two dimensions appear to distinguish these clusters: the amount of spatial information and cognitive processing effort. The authors discuss visual information processing issues relevant to the research, methodology and data analyses used to develop the classification system, results of the empirical study, and possible directions for future research.

Original languageEnglish (US)
Title of host publicationProc First 90 IEEE Conf Visualization Visualization 90
PublisherPubl by IEEE
Pages131-138
Number of pages8
ISBN (Print)0818620838
Publication statusPublished - 1990
Externally publishedYes
EventProceedings of the First 1990 IEEE Conference on Visualization - Visualization '90 - San Francisco, CA, USA
Duration: Oct 23 1990Oct 26 1990

Other

OtherProceedings of the First 1990 IEEE Conference on Visualization - Visualization '90
CitySan Francisco, CA, USA
Period10/23/9010/26/90

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Lohse, J., Rueter, H., Biolsi, K., & Walker, N. (1990). Classifying visual knowledge representations: A foundation for visualization research. In Proc First 90 IEEE Conf Visualization Visualization 90 (pp. 131-138). Publ by IEEE.