Guidelines for using multiple views in information visualization

Abstract

A multiple view system uses two or more distinct views to support the investigation of a single conceptual entity. Many such systems exist, ranging from computer-aided design (CAD) systems for chip design that display both the logical structure and the actual geometry of the integrated circuit to overview-plus-detail systems that show both an overview for context and a zoomed-in-view for detail. Designers of these systems must make a variety of design decisions, ranging from determining layout to constructing sophisticated coordination mechanisms. Surprisingly, little work has been done to characterize these systems or to express guidelines for their design. Based on a workshop discussion of multiple views, and based on our own design and implementation experience with these systems, we present eight guidelines for the design of multiple view systems.

The personal cockpit

“…Baldonado et al [15] propose that the cognitive overhead of interpreting a single complex visualization can be reduced by dividing the same information into multiple simpler views that can be observed in parallel. Each set of multiple views may contain only a subset of components from the full data set, however analysts can form mental links by switching their attention among them.…”

“…Each set of multiple views may contain only a subset of components from the full data set, however analysts can form mental links by switching their attention among them. As a caveat, browsing information across multiple views may incur additional costs such as greater required display space, increased memory load and effort for context-switching [15]. However, visual analytic research indicates there are cases when the benefits outweigh the costs [191].…”

“…From this we can assume that it is a best-practice for SAIs to make individual application windows self-contained, such that all of the information required for a particular task is present on a single interface. However, information is sometimes easier to interpret when spread between multiple, simplified visualizations [15,192]. Also, these windows may be interlinked such that manipulating content on one window may affect the information displayed on other windows.…”

Towards Adaptive Information Visualization: On the Influence of User Characteristics

“…We believe this may be attributed to the fact that existing visualizations are designed mostly around the target data set and associated task model, with little consideration for user differences. Both long term user characteristics (e.g., cognitive abilities and expertise) and short term factors (e.g., cognitive load and attention) have often been overlooked in the design of information visualizations, despite studies linking individual differences to visualization efficacy for search and navigation tasks [1,8], for information seeking tasks [7,25], as well as anecdotal evidence of diverse personal visualization preferences [3]. Our long term goal is to explore the possibilities of user-centered visualizations, which understand that different users have different visualization needs and abilities, and which can adapt to these differences.…”

Scattering Points in Parallel Coordinates

“…Visualization techniques in combination can complement each other and help solve challenging problems. A set of guidelines on when and how multiple view systems should be used has been provided by Baldonado et al [5]. In our work we have developed a system that integrates the point (e.g.…”