Browsing by Author "Vuillemot, Romain"

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    Boundary Objects in Design Studies: Reflections on the Collaborative Creation of Isochrone Maps
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Vuillemot, Romain; Rivière, Philippe; Beignon, Anaëlle; Tabard, Aurélien; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    We propose to take an artifact-centric approach to design studies by leveraging the concept of boundary object. Design studies typically focus on processes and articulate design decisions in a project-specific context with a goal of transferability. We argue that design studies could benefit from paying attention to the material conditions in which teams collaborate to reach design outcomes. We report on a design study of isochrone maps following cartographic generalization principles. Focusing on boundary objects enables us to characterize five categories of artifacts and tools that facilitated collaboration between actors involved in the design process (structured collections, structuring artifacts, process-centric artifacts, generative artifacts, and bridging artifacts). We found that artifacts such as layered maps and map collections played a unifying role for our inter-disciplinary team. We discuss how such artifacts can be pivotal in the design process. Finally, we discuss how considering boundary objects could improve the transferability of design study results, and support reflection on inter-disciplinary collaboration in the domain of Information Visualization.
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    DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Jaunet, Theo; Vuillemot, Romain; Wolf, Christian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    We present DRLViz, a visual analytics interface to interpret the internal memory of an agent (e.g. a robot) trained using deep reinforcement learning. This memory is composed of large temporal vectors updated when the agent moves in an environment and is not trivial to understand due to the number of dimensions, dependencies to past vectors, spatial/temporal correlations, and co-correlation between dimensions. It is often referred to as a black box as only inputs (images) and outputs (actions) are intelligible for humans. Using DRLViz, experts are assisted to interpret decisions using memory reduction interactions, and to investigate the role of parts of the memory when errors have been made (e.g. wrong direction). We report on DRLViz applied in the context of video games simulators (ViZDoom) for a navigation scenario with item gathering tasks. We also report on experts evaluation using DRLViz, and applicability of DRLViz to other scenarios and navigation problems beyond simulation games, as well as its contribution to black box models interpretability and explain-ability in the field of visual analytics.
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    GROUPSET: A Set-Based Technique to Explore Time-Varying Data
    (The Eurographics Association, 2022) Liu, Liqun; Vuillemot, Romain; Agus, Marco; Aigner, Wolfgang; Hoellt, Thomas
    We introduce GroupSet, a technique to facilitate the exploration of temporal charts using a set-based approach. GroupSet operates in a twofold way: first it classifies temporal data into categories (sets) for each time point, second it enables to explore such membership to categories (sets) over time. This approach enables to reveal temporal similarities of elements by categories (sets) memberships, usually hidden by overplot. We demonstrate the applicability of the technique to two case studies (traffic data and sport data) and report on usability feedback of an interactive prototype implementing the technique. Our code and datasets are published as an open-source project and we expect further research towards efficient set creation and temporal manipulation, which remain under-explored areas in the domain of set visualization and interaction.