Systemization of Knowledge (SoK): Visualization Insight -- Two Decades of Research, Practice, and Future Directions

Insight generation has long been a primary goal of information visualization. Yet, there remains a lack of a comprehensive review on the research advancements of Visualization Insight. This systematic literature review analyzes nearly two decades of theoretical, empirical, and technological research development of visualization insight. By examining 340 articles from 17 leading journals and conferences in visualization, human–computer interaction, and databases and conducting an in-depth review of 92 papers, we propose a framework illustrating the iterative and collaborative process of generating, exploring, and communicating visualization insights. We then use the framework to analyze and compare the reviewed literature, revealing that (1) Research on visualization insight has evolved from defining insights to formalizing the insight generation process and communicating visualization insights through reports and data stories; (2) Issues like cognitive biases and chart errors hinder the effectiveness of visual discovery; (3) Automation in data fact mining and story generation eases data storytelling, but often lacks the incorporation of domain information, limiting the stories’ impact. Moving forward, we outline five future research directions, aiming to improve insight quality and expand the methods of generating and communicating insights.

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Publication Details

Journal
ACM Computing Surveys
Published
2026-01-14
DOI
https://doi.org/10.1145/3788869
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Systemization of Knowledge (SoK): Visualization Insight -- Two Decades of Research, Practice, and Future Directions

Chen He, Niklas Elmqvist, Mahdi Munshi, Andrea Bellucci
ACM Computing Surveys
Data Visualization and Analytics
article

Systemization of Knowledge (SoK): Visualization Insight -- Two Decades of Research, Practice, and Future Directions

Chen He, Niklas Elmqvist, Mahdi Munshi, Andrea Bellucci
article en

Abstract

Insight generation has long been a primary goal of information visualization. Yet, there remains a lack of a comprehensive review on the research advancements of Visualization Insight. This systematic literature review analyzes nearly two decades of theoretical, empirical, and technological research development of visualization insight. By examining 340 articles from 17 leading journals and conferences in visualization, human–computer interaction, and databases and conducting an in-depth review of 92 papers, we propose a framework illustrating the iterative and collaborative process of generating, exploring, and communicating visualization insights. We then use the framework to analyze and compare the reviewed literature, revealing that (1) Research on visualization insight has evolved from defining insights to formalizing the insight generation process and communicating visualization insights through reports and data stories; (2) Issues like cognitive biases and chart errors hinder the effectiveness of visual discovery; (3) Automation in data fact mining and story generation eases data storytelling, but often lacks the incorporation of domain information, limiting the stories’ impact. Moving forward, we outline five future research directions, aiming to improve insight quality and expand the methods of generating and communicating insights.

ACM Computing SurveysVol. 58(9)
University of Helsinki (FI), Aarhus University (DK), Universidad Carlos III de Madrid (ES)
Openalex Percentile: Top 89%
Data Visualization and Analytics
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