Information Studies

Permanent URI for this communityhttp://hdl.handle.net/1903/2249

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Author: search.filters.author.Elmqvist, Niklas

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    Data everyday as community-driven science: Athletes' critical data literacy practices in collegiate sports contexts
    (Wiley, 2022-12-27) Clegg, Tamara L.; Cleveland, Keaunna; Weight, Erianne; Greene, Daniel; Elmqvist, Niklas
    In this article, we investigate the community-driven science happening organically in elite athletics as a means of engaging a community of learners—collegiate athletes, many of whom come from underrepresented groups—in STEM. We aim to recognize the data literacy practices inherent in sports play and to explore the potential of critical data literacy practices for enabling athletes to leverage data science as a means of addressing systemic racial, equity, and justice issues inherent in sports institutions. We leverage research on critical data literacies as a lens to present case studies of three athletes at an NCAA Division 1 university spanning three different sports. We focus on athletes' experiences as they engage in critical data literacy practices and the ways they welcome, adapt, resist, and critique such engagements. Our findings indicate ways in which athletes (1) readily accept data practices espoused by their coaches and sport, (2) critique and intentionally disengage from such practices, and (3) develop their own new data productions. In order to support community-driven science, our findings point to the critical role of athletics' organizations in promoting athletes' access to, as well as engagement and agency with data practices on their teams.
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    Through Their Eyes and In Their Shoes: Providing Group Awareness During Collaboration Across Virtual Reality and Desktop Platforms
    (Association for Computer Machinery (ACM), 2023-04-23) Saffo, David; Batch, Andrea; Dunne, Cody; Elmqvist, Niklas
    Many collaborative data analysis situations benefit from collaborators utilizing different platforms. However, maintaining group awareness between team members using diverging devices is difficult, not least because common ground diminishes. A person using head-mounted VR cannot physically see a user on a desktop computer even while co-located, and the desktop user cannot easily relate to the VR user’s 3D workspace. To address this, we propose the “eyes-and-shoes” principles for group awareness and abstract them into four levels of techniques. Furthermore, we evaluate these principles with a qualitative user study of 6 participant pairs synchronously collaborating across distributed desktop and VR head-mounted devices. In this study, we vary the group awareness techniques between participants and explore two visualization contexts within participants. The results of this study indicate that the more visual metaphors and views of participants diverge, the greater the level of group awareness is needed.
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    Accessible Data Representation with Natural Sound
    (Association for Computer Machinery (ACM), 2023-04-23) Hoque, Md Naimul; Ehtesham-Ul-Haque, Md; Elmqvist, Niklas; Billah, Syed Masum
    Sonification translates data into non-speech audio. Such auditory representations can make data visualization accessible to people who are blind or have low vision (BLV). This paper presents a sonification method for translating common data visualization into a blend of natural sounds. We hypothesize that people’s familiarity with sounds drawn from nature, such as birds singing in a forest, and their ability to listen to these sounds in parallel, will enable BLV users to perceive multiple data points being sonified at the same time. Informed by an extensive literature review and a preliminary study with 5 BLV participants, we designed an accessible data representation tool, Susurrus, that combines our sonification method with other accessibility features, such as keyboard interaction and text-to-speech feedback. Finally, we conducted a user study with 12 BLV participants and report the potential and application of natural sounds for sonification compared to existing sonification tools.
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    Perceptual Pat: A Virtual Human Visual System for Iterative Visualization Design
    (Association for Computer Machinery (ACM), 2023-04-23) Shin, Sungbok; Hong, Sanghyun; Elmqvist, Niklas
    Designing a visualization is often a process of iterative refinement where the designer improves a chart over time by adding features, improving encodings, and fixing mistakes. However, effective design requires external critique and evaluation. Unfortunately, such critique is not always available on short notice and evaluation can be costly. To address this need, we present Perceptual Pat, an extensible suite of AI and computer vision techniques that forms a virtual human visual system for supporting iterative visualization design. The system analyzes snapshots of a visualization using an extensible set of filters—including gaze maps, text recognition, color analysis, etc—and generates a report summarizing the findings. The web-based Pat Design Lab provides a version tracking system that enables the designer to track improvements over time. We validate Perceptual Pat using a longitudinal qualitative study involving 4 professional visualization designers that used the tool over a few days to design a new visualization.