Toward Supporting Narrative-Driven Data Exploration: Barriers and Design Opportunities

2025-08-06

AI Summary

Narrative-driven data exploration faces core challenges—including contextual discontinuity across views, difficulty in tracing analytical reasoning paths, and insufficient externalization of intermediate interpretations. Method: We conducted a qualitative empirical study with 48 participants, combining in-depth interviews and task-based observations, to code and thematically analyze multi-stage dynamic analytical behaviors. Contribution/Results: The study systematically identifies three critical impediments and derives three design principles for supporting narrative evolution in visual analytics: (1) enforcing cross-view contextual consistency, (2) explicitly tracking reasoning trajectories, and (3) structurally externalizing intermediate interpretations. These principles are operationalized into concrete interaction mechanisms and practical guidelines. The work advances visual analytics systems from static chart presentation toward next-generation tools that actively support dynamic, iterative narrative construction.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning
• Computer Vision: Visual Reasoning & Symbolic Representations

Application Category

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

Abstract

Analysts increasingly explore data through evolving, narrative-driven inquiries, moving beyond static dashboards and predefined metrics as their questions deepen and shift. As these explorations progress, insights often become dispersed across views, making it challenging to maintain context or clarify how conclusions arise. Through a formative study with 48 participants, we identify key barriers that hinder narrative-driven exploration, including difficulty maintaining context across views, tracing reasoning paths, and externalizing evolving interpretations. Our findings surface design opportunities to support narrative-driven analysis better.

Problem

• Barriers in maintaining context across dispersed views
• Challenges in tracing evolving reasoning paths
• Difficulty externalizing dynamic interpretations during exploration

Innovation

• Support evolving narrative-driven inquiries
• Maintain context across dispersed views
• Trace reasoning paths for clarity