Characterizing Automated Data Insights
Po-Ming Law, Alex Endert, John Stasko
TL;DR
This paper systematically reviews automated data insight tools, proposing a classification of insight types and purposes, and discusses design opportunities to improve these systems.
Contribution
It provides a structured understanding of what constitutes data insights and categorizes their purposes, addressing a gap in current research.
Findings
Proposes 12 types of automated data insights
Identifies four main purposes for automating insights
Discusses design opportunities for future systems
Abstract
Many researchers have explored tools that aim to recommend data insights to users. These tools automatically communicate a rich diversity of data insights and offer such insights for many different purposes. However, there is a lack of structured understanding concerning what researchers of these tools mean by "insight" and what tasks in the analysis workflow these tools aim to support. We conducted a systematic review of existing systems that seek to recommend data insights. Grounded in the review, we propose 12 types of automated insights and four purposes of automating insights. We further discuss the design opportunities emerged from our analysis.
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