Toward Systematic Design Considerations of Organizing Multiple Views

TL;DR

This paper reviews multiple-view visualization systems to identify key design considerations for spatial organization, focusing on perception and content, to improve understanding and usability in visual analytics.

Contribution

It systematically analyzes MV layout design by identifying perception and content considerations, providing a foundation for better spatial organization strategies.

Findings

Identifies perception and content as key factors in MV layout design.

Highlights the impact of spatial organization on data understanding.

Provides a systematic framework for analyzing MV layout considerations.

Abstract

Multiple-view visualization (MV) has been used for visual analytics in various fields (e.g., bioinformatics, cybersecurity, and intelligence analysis). Because each view encodes data from a particular perspective, analysts often use a set of views laid out in 2D space to link and synthesize information. The difficulty of this process is impacted by the spatial organization of these views. For instance, connecting information from views far from each other can be more challenging than neighboring ones. However, most visual analysis tools currently either fix the positions of the views or completely delegate this organization of views to users (who must manually drag and move views). This either limits user involvement in managing the layout of MV or is overly flexible without much guidance. Then, a key design challenge in MV layout is determining the factors in a spatial organization that impact understanding. To address this, we review a set of MV-based systems and identify considerations for MV layout rooted in two key concerns: perception, which considers how users perceive view relationships, and content, which considers the relationships in the data. We show how these allow us to study and analyze the design of MV layout systematically.