The Now and Then: Integrating Current and Historical Data in Small Multiple Time Series Visualization

2026-10-06

AI Summary

This study addresses the lack of design guidelines for highlighting current values in small multiples time-series visualizations. Grounded in visual channel theory and iterative design, this work constructs a design space that integrates current and historical data, validating its effectiveness through an online empirical experiment. The findings demonstrate that integrated designs outperform separated layouts, while establishing best practices for size and color encoding in threshold-based tasks. Specifically, the integrated approach improves response times by 28% for non-threshold tasks, and color encoding significantly enhances threshold detection performance. These results provide a theoretical foundation and practical design specifications for facilitating rapid assessment in real-time monitoring scenarios.

Abstract

Small multiple time series visualizations are often used for real-time data monitoring tasks in high-impact domains such as healthcare and manufacturing. Effective design is critical because users rely on these visualizations to monitor data from many entities, such as patients or machines, often while distracted. Users may need to rapidly appraise current values for each entity, monitoring for those that go outside an acceptable range, while also watching temporal trends. However, no design guidelines currently exist for visually emphasizing current values in historical time series represented by small multiples. Via an iterative design process informed by a review of related literature and theory on visual channels and emphasis, we present a design space for glanceable time series small multiple displays. We evaluate this space through two online empirical studies, testing against non-threshold and threshold rapid appraisal tasks. Our results provide insights into merging current value and historical data visualizations for rapid appraisal tasks in time series monitoring. For non-threshold tasks, we found that size encodings on the current value, spatially integrated into the line chart, may provide a good compromise, with 28% response time improvement for tasks involving finding large current values and minimal interference with trend lookup tasks. More generally, integrated designs outperformed separated designs (in which the current value representation is spatially separated from the historical trend line). For threshold tasks, color threshold encodings significantly outperformed shaded band encodings. All supplemental materials are available at https://osf.io/wzf6a.

Problem

• small multiple time series visualization
• real-time data monitoring
• current value emphasis
• rapid appraisal
• design guidelines

Innovation

• Small Multiple Time Series
• Glanceable Visualization
• Visual Encoding
• Integrated Design
• Rapid Appraisal