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

Fuente: arXiv
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Main Authors: Huang, Oliver, Nobre, Carolina
Format: Preprint
Published: 2025
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author Huang, Oliver
Nobre, Carolina
author_facet Huang, Oliver
Nobre, Carolina
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2508_04920
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Toward Supporting Narrative-Driven Data Exploration: Barriers and Design Opportunities
Huang, Oliver
Nobre, Carolina
Human-Computer Interaction
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.
title Toward Supporting Narrative-Driven Data Exploration: Barriers and Design Opportunities
topic Human-Computer Interaction
url https://arxiv.org/abs/2508.04920