In this report we describe the concept of the proximity compatibility principle (PCP) and demonstrate its relevance to display design: Displays relevant to a common task or mental operation (close task or mental proximity) should be rendered close together in perceptual space (close display proximity). Different forms of task proximity are discussed, as are the different information-processing mechanisms that underlie the effects of the several different design manipulations of display proximity. Experimental data that support this process-based elaboration of PCP are then reviewed in design contexts relating to aviation, graphs, display layout, and decision aiding.

Although the use of performance efficiency measures (speed, movement economy, errors) and ergonomic assessments are relatively well established, the evaluation of cognitive outcomes is rare. This report makes the case for assessment strategies that include mental workload measures as a way to improve training scenarios and training/operating environments. These mental workload measures can be crucially important in determining the difference between well-intentioned but subtly distracting technologies and true breakthroughs that will enhance performance and reduce stress.

This article provides guidelines for presenting quantitative data in papers for publication. The article begins with a reader-centered design philosophy that distills the maxim “know thy user” into three components: (a) know your users′ tasks, (b) know the operations supported by your displays, and (c) match user's operations to the ones supported by your display. Next, factors affecting the decision to present data in text, tables, or graphs are described: the amount of data, the readers′ informational needs, and the value of visualizing the data. The remainder of the article outlines the design decisions required once an author has selected graphs as the data presentation medium. Decisions about the type of graph depend on the readers′ experience and informational needs as well as characteristics of the independent (predictor) variables and the dependent (criterion) variable. Finally, specific guidelines for the design of graphs are presented. The guidelines were derived from empirical studies, analyses of graph readers′ tasks, and practice-based design guidelines. The guidelines focus on matching the specific sensory, perceptual, and cognitive operations required to read a graph to the operations that the graph supports.

Effect sizes obtained from 39 experiments were used to evaluate the predictions of the basic tasks model of graphical efficacy. This model predicts that performance will be attenuated with graphical displays as a function of the particular specifier, or visual dimension, used to code data values. In this review the basic tasks model predicted performance more accurately than did Tufte's data-ink principle. In addition, variability in effect sizes across studies revealed that the model was more successful at predicting performance in local (focusing) tasks than in global information synthesis tasks. Furthermore, the model was better at predicting performance in tasks requiring the use of physically present rather than remembered graphs. Further differences in effect sizes resulted from variability in the exact specifiers used in experimental graphs. Minimal differences were obtained among graphs that used position, length, or angle as specifiers. However, graphs that used area or volume to represent quantitative values were associated with consistently worse performance than found with other formats.

Researchers have proposed that graphical efficacy may be determined, in part, by the nature of the perceptual interactions that exist between attributes used to create graphical displays, One extreme type of interaction is integrality, in which two or more physical dimensions are represented as a single psychological dimension in the observer. An alternative type of interaction is configurality, in which a global emergent dimension is available to the observer in addition to the component attributes, Thirteen stimulus sets, each composed of attributes commonly used in the design of graphs, were submitted to the performance-based diagnostics of integrality and configurality. Analyses suggest a continuum of configurality among the present stimulus sets, with little evidence for integral graphical attributes. The configural pattern of results was more common when two identical dimensions were paired (homogeneous stimuli) than when two different dimensions were paired (heterogeneous stimuli). However, there was no evidence that pairs of dimensions belonging to a single object (object integration) were any more configural than dimensions belonging to different objects. Object integration was, however, consistently related to inefficient performance in tasks requiring the filtering of one of two component dimensions.How may geometric properties and color be most effectively employed to communicate quantitative information? What, in short, makes a good graphical display? These questions represent the research agenda for what DeSanctis (1984) calls comparative graphics. One approach to comparative graphics has been to systematically study the accuracy with which we can identify and discriminate stimulus levels along continuous physical dimensions, and this information is routinely presented in introductory discussions of display design (e.g., Hutchingson, 1981;McCormick & Sanders, 1982). However, this tradition, which emphasizes the coding of individual quantitative variables as individual physical dimensions, has recently been supplemented by interest in the perceptual interactions that may occur when combinations of such dimensions are used to represent multiple variables. In the present paper, we consider the utility of two notions of attribute interaction-dimensional integrality and dimensional configurality-for the prediction of graphical efficacy.