Classifying visual knowledge representations: a foundation for visualization research
Jerry Lohse, Henry H. Rueter, Kevin J. Biolsi, Neff Walker · IEEE Visualization · 1990
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. >