Browsing by Author "Whitley, Kirsten"

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    Evaluating Navigation and Comparison Performance of Computational Notebooks on Desktop and in Virtual Reality
    In, Sungwon; Krokos, Eric; Whitley, Kirsten; North, Christopher L.; Yang, Yalong (ACM, 2024-05-11)
    The computational notebook serves as a versatile tool for data analysis. However, its conventional user interface falls short of keeping pace with the ever-growing data-related tasks, signaling the need for novel approaches. With the rapid development of interaction techniques and computing environments, there is a growing interest in integrating emerging technologies in data-driven workflows. Virtual reality, in particular, has demonstrated its potential in interactive data visualizations. In this work, we aimed to experiment with adapting computational notebooks into VR and verify the potential benefits VR can bring. We focus on the navigation and comparison aspects as they are primitive components in analysts’ workflow. To further improve comparison, we have designed and implemented a Branching&Merging functionality. We tested computational notebooks on the desktop and in VR, both with and without the added Branching&Merging capability. We found VR significantly facilitated navigation compared to desktop, and the ability to create branches enhanced comparison.
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    A Longitudinal Exploration of Sensemaking Strategies in Immersive Space to Think
    Davidson, Kylie; Lisle, Lee; Whitley, Kirsten; Bowman, Douglas A.; North, Christopher L. (IEEE, 2022-09)
    Existing research on immersive analytics to support the sensemaking process focuses on single-session sensemaking tasks. However, in the wild, sensemaking can take days or months to complete. In order to understand the full benefits of immersive analytic systems, we need to understand how immersive analytic systems provide flexibility for the dynamic nature of the sensemaking process. In our work, we build upon an existing immersive analytic system – Immersive Space to Think, to evaluate how immersive analytic systems can support sensemaking tasks over time. We conducted a user study with eight participants with three separate analysis sessions each. We found significant differences between analysis strategies between sessions one, two, and three, which suggest that immersive space to think can benefit analysts during multiple stages in the sensemaking process.
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    Sensemaking in Immersive Space to Think: Exploring Evolution, Expertise, Familiarity, and Organizational Strategies
    Davidson, Kylie Marie (Virginia Tech, 2024-08-20)
    Sensemaking is the way in which we understand the world around us. Pirolli and Card developed a sensemaking model related to intelligence analysis, which involves taking raw, unstructured data, analyzing it, and presenting a report of the findings. With lower-cost immersive technologies becoming more popular, new opportunities exist to leverage embodied and distributed cognition to better support sensemaking by providing vast, immersive space for creating meaningful schemas (organizational structures) during an analysis task. This work builds on prior work in immersive analytics on the concept of Immersive Space to Think (IST), which provides analysts with immersive space to physically navigate and use to organize information during a sensemaking task. In this work, we performed several studies that aimed to understand how IST supports sensemaking and how we can develop additional features to better aid analysts while they complete sensemaking in immersive analytics systems, focusing on non-quantitative data analysis. In a series of exploratory user studies, we aimed to understand how users' sensemaking process evolves during multiple session analyses, which identified how the participants refined their use of the immersive space into later stages of the sensemaking process. Another exploratory user study highlighted how professional analysts and novice users share many similarities in immersive analytic tool usage during sensemaking within IST. In addition to looking at multi-session analysis tasks, we also explored how sensemaking strategies change as users become more familiar with the immersive analytics tool usage in an exploratory study that utilized multiple analysis tasks completed over a series of three user study sessions. Lastly, we conducted a comparative user study to evaluate how the addition of new organizational features, clustering, and linking affect sensemaking within IST. Overall, our studies expanded the IST tool set and gathered an enhanced understanding of how immersive space is utilized during analysis tasks within IST.