Browsing by Author "Satyanarayan, Arvind"

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    Rich Screen Reader Experiences for Accessible Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Zong, Jonathan; Lee, Crystal; Lundgard, Alan; Jang, JiWoong; Hajas, Daniel; Satyanarayan, Arvind; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Current web accessibility guidelines ask visualization designers to support screen readers via basic non-visual alternatives like textual descriptions and access to raw data tables. But charts do more than summarize data or reproduce tables; they afford interactive data exploration at varying levels of granularity-from fine-grained datum-by-datum reading to skimming and surfacing high-level trends. In response to the lack of comparable non-visual affordances, we present a set of rich screen reader experiences for accessible data visualization and exploration. Through an iterative co-design process, we identify three key design dimensions for expressive screen reader accessibility: structure, or how chart entities should be organized for a screen reader to traverse; navigation, or the structural, spatial, and targeted operations a user might perform to step through the structure; and, description, or the semantic content, composition, and verbosity of the screen reader's narration. We operationalize these dimensions to prototype screen-reader-accessible visualizations that cover a diverse range of chart types and combinations of our design dimensions. We evaluate a subset of these prototypes in a mixed-methods study with 13 blind and visually impaired readers. Our findings demonstrate that these designs help users conceptualize data spatially, selectively attend to data of interest at different levels of granularity, and experience control and agency over their data analysis process.
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    VisuaLint: Sketchy In Situ Annotations of Chart Construction Errors
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hopkins, Aspen K.; Correll, Michael; Satyanarayan, Arvind; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Chart construction errors, such as truncated axes or inexpressive visual encodings, can hinder reading a visualization, or worse, imply misleading facts about the underlying data. These errors can be caught by critical readings of visualizations, but readers must have a high level of data and design literacy and must be paying close attention. To address this issue, we introduce VisuaLint: a technique for surfacing chart construction errors in situ. Inspired by the ubiquitous red wavy underline that indicates spelling mistakes, visualization elements that contain errors (e.g., axes and legends) are sketchily rendered and accompanied by a concise annotation. VisuaLint is unobtrusive-it does not interfere with reading a visualization-and its direct display establishes a close mapping between erroneous elements and the expression of error. We demonstrate five examples of VisualLint and present the results of a crowdsourced evaluation (N = 62) of its efficacy. These results contribute an empirical baseline proficiency for recognizing chart construction errors, and indicate near-universal difficulty in error identification. We find that people more reliably identify chart construction errors after being shown examples of VisuaLint, and prefer more verbose explanations for unfamiliar or less obvious flaws.