Browsing by Author "Borkin, Michelle A."

Now showing 1 - 4 of 4
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    Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Saffo, David; Leventidis, Aristotelis; Jain, Twinkle; Borkin, Michelle A.; Dunne, Cody; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Autonomous unmanned aerial vehicles are complex systems of hardware, software, and human input. Understanding this complexity is key to their development and operation. Information visualizations already exist for exploring flight logs but comprehensive analyses currently require several disparate and custom tools. This design study helps address the pain points faced by autonomous unmanned aerial vehicle developers and operators. We contribute: a spiral development process model for grounded evaluation visualization development focused on progressively broadening target user involvement and refining user goals; a demonstration of the model as part of developing a deployed and adopted visualization system; a data and task abstraction for developers and operators performing post-flight analysis of autonomous unmanned aerial vehicle logs; the design and implementation of DATA COMETS, an open-source and web-based interactive visualization tool for post-flight log analysis incorporating temporal, geospatial, and multivariate data; and the results of a summative evaluation of the visualization system and our abstractions based on in-the-wild usage.
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    Effective Use of Likert Scales in Visualization Evaluations: A Systematic Review
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) South, Laura; Saffo, David; Vitek, Olga; Dunne, Cody; Borkin, Michelle A.; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Likert scales are often used in visualization evaluations to produce quantitative estimates of subjective attributes, such as ease of use or aesthetic appeal. However, the methods used to collect, analyze, and visualize data collected with Likert scales are inconsistent among evaluations in visualization papers. In this paper, we examine the use of Likert scales as a tool for measuring subjective response in a systematic review of 134 visualization evaluations published between 2009 and 2019. We find that papers with both objective and subjective measures do not hold the same reporting and analysis standards for both aspects of their evaluation, producing less rigorous work for the subjective qualities measured by Likert scales. Additionally, we demonstrate that many papers are inconsistent in their interpretations of Likert data as discrete or continuous and may even sacrifice statistical power by applying nonparametric tests unnecessarily. Finally, we identify instances where key details about Likert item construction with the potential to bias participant responses are omitted from evaluation methodology reporting, inhibiting the feasibility and reliability of future replication studies. We summarize recommendations from other fields for best practices with Likert data in visualization evaluations, based on the results of our survey.
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    Process and Pitfalls of Online Teaching and Learning with Design Study ''Lite'' Methodology: A Retrospective Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Syeda, Uzma Haque; Dunne, Cody; Borkin, Michelle A.; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    Design studies are an integral method of visualization research with hundreds of instances in the literature. Although taught as a theory, the practical implementation of design studies is often excluded from visualization pedagogy due to the lengthy time commitments associated with such studies. Recent research has addressed this challenge and developed an expedited design study framework, the Design Study ''Lite'' Methodology (DSLM), which can implement design studies with novice students within just 14 weeks. The framework was developed and evaluated based on five semesters of in-person data visualization courses with 30 students or less and was implemented in conjunction with Service-Learning (S-L).With the growth and popularity of the data visualization field-and the teaching environment created by the COVID-19 pandemic-more academic institutions are offering visualization courses online. Therefore, in this paper, we strengthen and validate the epistemological foundations of the DSLM framework by testing its (1) adaptability to online learning environments and conditions and (2) scalability to larger classes with up to 57 students. We present two online implementations of the DSLM framework, with and without Service-Learning (S-L), to test the adaptability and scalability of the framework. We further demonstrate that the framework can be applied effectively without the S-L component. We reflect on our experience with the online DSLM implementations and contribute a detailed retrospective analysis using thematic analysis and grounded theory methods to draw valuable recommendations and guidelines for future applications of the framework. This work verifies that DSLM can be used successfully in online classes to teach design study methodology. Finally, we contribute novel additions to the DSLM framework to further enhance it for teaching and learning design studies in the classroom.
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    Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Lan, Fangfei; Young, Michael; Anderson, Lauren; Ynnerman, Anders; Bock, Alexander; Borkin, Michelle A.; Forbes, Angus G.; Kollmeier, Juna A.; Wang, Bei; Smit, Noeska and Vrotsou, Katerina and Wang, Bei
    We present a state-of-the-art report on visualization in astrophysics. We survey representative papers from both astrophysics and visualization and provide a taxonomy of existing approaches based on data analysis tasks. The approaches are classified based on five categories: data wrangling, data exploration, feature identification, object reconstruction, as well as education and outreach. Our unique contribution is to combine the diverse viewpoints from both astronomers and visualization experts to identify challenges and opportunities for visualization in astrophysics. The main goal is to provide a reference point to bring modern data analysis and visualization techniques to the rich datasets in astrophysics.