Browsing by Author "Setlur, Vidya"

Now showing 1 - 5 of 5
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    Blocks: Creating Rich Tables with Drag-and-Drop Interaction
    (The Eurographics Association, 2022) Whilden, Allison; Karis, Dirk; Setlur, Vidya; Degtyar, Rodion; Que, Jonathan; Lymperopoulos, Filippos; Agus, Marco; Aigner, Wolfgang; Hoellt, Thomas
    We present Blocks, a formalism that enables the building of visualizations by specifying layout, data relationships, and level of detail (LOD) for specific portions of the visualization. Users can create and manipulate Blocks on a canvas interface through drag-and-drop interaction, controlling the LOD of the data attributes for tabular style visualizations. We conducted a user study to compare how 24 participants employ Blocks and Tableau to complete a target visualization task. Findings from the study suggest that Blocks is a useful mechanism for creating visualizations with embedded microcharts, conditional formatting, and custom layouts. We describe future directions for extending Blocks in visual analysis interfaces.
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    BOLT: A Natural Language Interface for Dashboard Authoring
    (The Eurographics Association, 2023) Srinivasan, Arjun; Setlur, Vidya; Hoellt, Thomas; Aigner, Wolfgang; Wang, Bei
    Authoring dashboards is often a complex process, requiring expertise in both data analysis and visualization design. With current tools, authors lack the means to express their objectives for creating a dashboard (e.g., summarizing data changes or comparing data categories), making it difficult to discover and assemble content relevant to the dashboard. Addressing this challenge, we propose the idea of employing natural language (NL) for dashboard authoring with a prototype interface, BOLT. In this paper, we detail BOLT's design and implementation, describing how the system maps NL utterances to prevalent dashboard objectives and generates dashboard recommendations. Utilizing BOLT as a design probe, we validate the proposed idea of NL-based dashboard authoring through a preliminary user study. Based on the study feedback, we highlight promising application scenarios and future directions to support richer dashboard authoring workflows.
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    From Delays to Densities: Exploring Data Uncertainty through Speech, Text, and Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2024) Stokes, Chase; Sanker, Chelsea; Cogley, Bridget; Setlur, Vidya; Aigner, Wolfgang; Archambault, Daniel; Bujack, Roxana
    Understanding and communicating data uncertainty is crucial for making informed decisions in sectors like finance and healthcare. Previous work has explored how to express uncertainty in various modes. For example, uncertainty can be expressed visually with quantile dot plots or linguistically with hedge words and prosody. Our research aims to systematically explore how variations within each mode contribute to communicating uncertainty to the user; this allows us to better understand each mode's affordances and limitations. We completed an exploration of the uncertainty design space based on pilot studies and ran two crowdsourced experiments examining how speech, text, and visualization modes and variants within them impact decision-making with uncertain data. Visualization and text were most effective for rational decision-making, though text resulted in lower confidence. Speech garnered the highest trust despite sometimes leading to risky decisions. Results from these studies indicate meaningful trade-offs among modes of information and encourage exploration of multimodal data representations.
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    LOKI: Reusing Custom Concepts in Interactive Analytic Workflows
    (The Eurographics Association, 2023) Setlur, Vidya; Beers, Andrew; Hoellt, Thomas; Aigner, Wolfgang; Wang, Bei
    Natural language (NL) interaction enables users to be expressive with their queries when exploring data. Users often specify complex NL queries that involve a combination of grouping, aggregations, and conditionals of data attributes and values. Such queries are often reused several times by users during their analytical workflows. Existing systems offer limited support to save these bespoke queries as concepts that can be referenced in subsequent NL queries, leading to users having to respecify these queries repeatedly. To address this issue, we describe a system, LOKI that allows users to save complex and bespoke queries as reusable concepts and use these concepts in other NL queries and analytics tools. For example, users can save an NL query, ''show me the opportunity amount by customer for open opportunities'' in a sales dataset, as a concept 'followup customers' and reference this custom concept in a query such as ''show me the total opportunity amount for followup customers.'' A qualitative evaluation of LOKI indicates the usefulness of supporting the reuse of custom concepts across various analytical workflows. We identify future research directions around in-situ semantic enrichment and dynamic concept maps for data exploration.
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    Mixing Modes: Active and Passive Integration of Speech, Text, and Visualization for Communicating Data Uncertainty
    (The Eurographics Association, 2024) Stokes, Chase; Sanker, Chelsea; Cogley, Bridget; Setlur, Vidya; Tominski, Christian; Waldner, Manuela; Wang, Bei
    Interpreting uncertain data can be difficult, particularly if the data presentation is complex. We investigate the efficacy of different modalities for representing data and how to combine the strengths of each modality to facilitate the communication of data uncertainty. We implemented two multimodal prototypes to explore the design space of integrating speech, text, and visualization elements. A preliminary evaluation with 20 participants from academic and industry communities demonstrates that there exists no one-size-fits-all approach for uncertainty communication strategies; rather, the effectiveness of conveying uncertain data is intertwined with user preferences and situational context, necessitating a more refined, multimodal strategy for future interface design. Materials for this paper can be found on OSF.