Beyond One-Size-Fits-All: User Strategies for Simplification Technique and Level Selection in Responsive Line Charts

2026-05-15

AI Summary

This study addresses the limitation of existing responsive line chart simplification methods, which typically employ a uniform algorithm and overlook varying user needs for preserving critical features—such as peaks and trends—across different datasets. Through a within-subjects experiment (N=30) evaluating three conditions (fixed algorithm, multi-algorithm selection, and multi-algorithm with manual point picking) across nine datasets, the research investigates how users select simplification strategies based on data characteristics rather than device type, and examines the impact of interaction complexity on engagement. Findings reveal that users adapt their strategies across datasets, yet increased flexibility does not universally enhance engagement. The results argue that responsive charting tools should balance flexibility and usability by integrating algorithmic diversity, progressive disclosure, and strong default settings.

Abstract

Simplifying line charts for responsive displays typically applies a single algorithm uniformly across devices, despite the availability of multiple techniques that preserve different signal characteristics (e.g., peaks, trends, periodicity). We investigate whether users benefit from algorithmic choice when adapting charts across screen sizes. In a within-subjects study (N=30), participants simplified nine datasets under three conditions: single pre-assigned technique (C1), multiple techniques (C2), and multiple techniques with manual point selection (C3), each with control over simplification level. We found that users adapted technique selections across datasets rather than devices, leveraging dataset-level strategies rather than per-device optimization. Additionally, interaction complexity did not always increase engagement uniformly, suggesting that responsive simplification tools should balance algorithmic flexibility with progressive disclosure and strong defaults. Supplemental materials are available at https://osf.io/yjp76/?view_only=b77b5e97f0cc4f689fbf48ad0d965af3.

Problem

• responsive visualization
• line chart simplification
• user strategies
• algorithm selection
• interactive visualization

Innovation

• responsive visualization
• line chart simplification
• user strategy
• algorithm selection
• progressive disclosure