A Design Space for Visualization with Large Scale-Item Ratios

2024-04-01

arXiv.org

AI Summary

Multi-scale visualization—particularly under extreme scale-to-object ratios—presents significant design challenges. This paper formally defines the problem and constructs an eight-dimensional design space encompassing three spatial dimensions. Through systematic encoding analysis of 54 academic and industrial case studies, we distill five recurrent design strategies and identify structural gaps in cross-dimensional strategy combinations. The proposed framework is both descriptive and generative: it systematically exposes limitations of current approaches while providing reusable design principles and optimization pathways for large-ratio visualization. By unifying conceptual modeling with empirical evidence, our work advances systematic design capability in multi-scale visual analytics.

Technology Category

• Computer Vision: Visual Reasoning & Symbolic Representations
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Web Mining and Content Analysis: Web data visualization
• Security and Privacy: Large-scale security measurements

Abstract

The scale-item ratio is the relationship between the largest scale and the smallest item in a visualization. Designing visualizations when this ratio is large can be challenging, and designers have developed many approaches to overcome this challenge. We present a design space for visualization with large scale-item ratios. The design space includes three dimensions, with eight total subdimensions. We demonstrate its descriptive power by using it to code approaches from a corpus we compiled of 54 examples, created by a mix of academics and practitioners. We then partition these examples into five strategies, which are shared approaches with respect to design space dimension choices. We demonstrate generative power by analyzing missed opportunities within the corpus of examples, identified through analysis of the design space, where we note how certain examples could have benefited from different choices. Supplemental materials: https://osf.io/wbrdm/?view_only=04389a2101a04e71a2c208a93bf2f7f2

Problem

• Challenges in designing multiscale visualizations with large scale ratios
• Proposing a design space with three dimensions and eight subdimensions
• Analyzing 52 examples to identify strategies and missed opportunities

Innovation

• Design space for multiscale visualization
• Four high-level strategies for design
• Analyzing missed opportunities in examples