Browsing by Author "Elmqvist, Niklas"

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    InsideInsights: Integrating Data-Driven Reporting in Collaborative Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Mathisen, Andreas; Horak, Tom; Klokmose, Clemens Nylandsted; Grønbæk, Kaj; Elmqvist, Niklas; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Analyzing complex data is a non-linear process that alternates between identifying discrete facts and developing overall assessments and conclusions. In addition, data analysis rarely occurs in solitude; multiple collaborators can be engaged in the same analysis, or intermediate results can be reported to stakeholders. However, current data-driven communication tools are detached from the analysis process and promote linear stories that forego the hierarchical and branching nature of data analysis, which leads to either too much or too little detail in the final report. We propose a conceptual design for integrated data-driven reporting that allows for iterative structuring of insights into hierarchies linked to analytic provenance and chosen analysis views. The hierarchies become dynamic and interactive reports where collaborators can review and modify the analysis at a desired level of detail. Our web-based INSIDEINSIGHTS system provides interaction techniques to annotate states of analytic components, structure annotations, and link them to appropriate presentation views. We demonstrate the generality and usefulness of our system with two use cases and a qualitative expert review.
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    Visualizing for the Non-Visual: Enabling the Visually Impaired to Use Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Choi, Jinho; Jung, Sanghun; Park, Deok Gun; Choo, Jaegul; Elmqvist, Niklas; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    The majority of visualizations on the web are still stored as raster images, making them inaccessible to visually impaired users. We propose a deep-neural-network-based approach that automatically recognizes key elements in a visualization, including a visualization type, graphical elements, labels, legends, and most importantly, the original data conveyed in the visualization. We leverage such extracted information to provide visually impaired people with the reading of the extracted information. Based on interviews with visually impaired users, we built a Google Chrome extension designed to work with screen reader software to automatically decode charts on a webpage using our pipeline. We compared the performance of the back-end algorithm with existing methods and evaluated the utility using qualitative feedback from visually impaired users.