IEEE VIS 2024 Content: DASH: A Bimodal Data Exploration Tool for Interactive Text and Visualizations

DASH: A Bimodal Data Exploration Tool for Interactive Text and Visualizations

Dennis Bromley - Tableau Research, Seattle, United States

Vidya Setlur - Tableau Research, Palo Alto, United States

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Room: Bayshore VI

2024-10-17T14:24:00ZGMT-0600Change your timezone on the schedule page
2024-10-17T14:24:00Z
Exemplar figure, described by caption below
DASH is an interactive bimodal data analysis system that facilitates drag-and-drop analysis between text and visual representations of data. Users can expand on chart marks or text phrases by dragging them to DASH’s text region, or drill down into them by dragging them to DASH’s chart region. Using a modified Lundgard et al semantic hierarchy, DASH helps users create data analyses that combine high-level insights with low-level supporting visualizations.
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Keywords

Semantic levels, LLMs, text generation

Abstract

Integrating textual content, such as titles, annotations, and captions, with visualizations facilitates comprehension and takeaways during data exploration. Yet current tools often lack mechanisms for integrating meaningful long-form prose with visual data. This paper introduces DASH, a bimodal data exploration tool that supports integrating semantic levels into the interactive process of visualization and text-based analysis. DASH operationalizes a modified version of Lundgard et al.’s semantic hierarchy model that categorizes data descriptions into four levels ranging from basic encodings to high-level insights. By leveraging this structured semantic level framework and a large language model’s text generation capabilities, DASH enables the creation of data-driven narratives via drag-and-drop user interaction. Through a preliminary user evaluation, we discuss the utility of DASH’s text and chart integration capabilities when participants perform data exploration with the tool.