What are Data Insights to Professional Visualization Users?

Law, Po-Ming; Endert, Alex; Stasko, John

doi:10.1109/vis47514.2020.00043

Cited by 8 publications

(4 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This semantic content is characteristic of what is often referred to as "insight" in visualization research. Although lacking a precise and agreed-upon definition [20,60,61,76,95], an insight is often an observation about the data that is complex, deep, qualitative, unexpected, and relevant [108]. Critically, insights depend on individual perceivers, their subjective knowledge, and domain-expertise.…”

Section: B [Line Medium Business]mentioning

confidence: 99%

Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Lundgard¹,

Satyanarayan²

2022

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Fig. 1. Visualizations like "Flatten the Curve" (A) efficiently communicate critical public health information, while simultaneously excluding people with disabilities [11, 28]. To promote accessible visualization via natural language descriptions (B, C), we introduce a four-level model of semantic content. Our model categorizes and color codes sentences according to the semantic content they convey.

show abstract

Section: B [Line Medium Business]mentioning

confidence: 99%

Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Lundgard¹,

Satyanarayan²

2022

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…With a different purpose of supporting automation, researchers categorized insight in a bottom-up manner of people reading static charts to build systems that generate the most suitable visualization for a particular type of insight [15,59]. Law et al [33] provided a theoretical characterization of insight through interviewing professional visualization users.…”

Section: Insight Characterizationmentioning

confidence: 99%

“…Compared with Law et al's characterization [33], we adopted Saraiya et al's approach to characterize insight considering its practicality in empirical studies; we used the characteristics that could be applied to generic visualizations. TaggedComments [9] and Com-mentSpace [56] characterized insight in a concrete way, which to our opinion could be dealt with using natural language processing, whereas Saraiya et al's characterization is more abstract, which could benefit from the analysis of interactions and referred entities for automation, though both types of characterization are meaningful for insight management.…”

Section: Insight Characterizationmentioning

confidence: 99%

Characterizing Visualization Insights through Entity-Based Interaction: An Exploratory Study

He¹,

Vuong²

2022

Preprint

View full text Add to dashboard Cite

One of the primary purposes of visualization is to assist users in discovering insights. While there has been much research in information visualization aiming at complex data transformation and novel presentation techniques, relatively little has been done to understand how users derive insights through interactive visualization of data. This paper presents a crowdsourced study with 158 participants investigating the relation between entity-based interaction (an action + its target entity) and the resulting insight. To this end, we generalized the interaction with an existing CO 2 Explorer as entity-based interaction and enabled users to input notes and refer to relevant entities to assist their narratives. We logged interactions of users freely exploring the visualization and characterized their externalized insights about the data. Using entity-based interactions and references to infer insight characteristics (category, overview versus detail, and prior knowledge), we found evidence that compared with interactions, entity references improved insight characterization from slight/fair to fair/moderate agreements. To interpret prediction outcomes, feature importance and correlation analysis indicated that, e.g., detailed insights tended to have more mouse-overs in the chart area and cite the vertical reference lines in the line chart as evidence. We discuss study limitations and implications on knowledge-assisted visualization, e.g., insight recommendations based on user exploration.

show abstract

“…Developers of these systems often use the term "insight" to refer to the automatically-extracted information (e.g., Quick Insights [15] and Automated Insights [1]). However, "insight" is an overloaded term that has been applied from multiple perspectives in the visualization community [23]. In the seminal work about insight-based evaluation, Saraiya et al [31] regard insights as data findings.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Automated Data Insights

Law

Endert

Stasko

2020

2020 IEEE Visualization Conference (VIS)

Self Cite

View full text Add to dashboard Cite

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.

show abstract

What are Data Insights to Professional Visualization Users?

Cited by 8 publications

References 32 publications

Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Characterizing Visualization Insights through Entity-Based Interaction: An Exploratory Study

Characterizing Automated Data Insights

Contact Info

Product

Resources

About