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

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arxiv 2408.01011 v2 pith:ADEGS3HW submitted 2024-08-02 cs.HC

classification cs.HC
keywords datadashexplorationintegratingsemantictexttoolbimodal
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

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  1. GistVis: Automatic Generation of Word-scale Visualizations from Data-rich Documents

    cs.HC 2025-02 conditional novelty 6.0 of 10

    GistVis automatically segments text, labels data insights, and generates word-scale visualizations, reducing reader mental load in a 12-person user study.

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