VisGap2024 - The Gap between Visualization Research and Visualization Software

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https://diglib.eg.org/handle/10.2312/3607000

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    Towards Sustainable Wildlife Management through Geospatial-Temporal Visual Exploration
    (The Eurographics Association, 2024) Thomasen, Manuel Mounir Demetry; Jørgensen, Mikkel V.; Svendsen, Lukas S.; Sørensen, Esben Bay; Walsh, Gareth; Kusnick, Jakob; Jänicke, Stefan; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
    Amidst increasing human activities disrupting natural ecosystems, there is a pressing need for sustainable wildlife management. This paper introduces a multiple-linked view system, an interactive tool designed to visualize wildlife populations, with a focus on hunting game, to foster discussions and developments towards greater sustainability. Two data sets are used throughout the paper reporting the hunting bag per year in Denmark. National and international reports are used to exemplify the tool's features and usability and to provide insights into the health and trends of huntable species populations. Through userfriendly interfaces featuring geospatial choropleth maps, temporal charts, and sunburst diagrams, the overarching application facilitates the exploration of wildlife population dynamics across species, municipalities, and years. The tool aims to assist policymakers, researchers, and the public in making informed decisions to preserve sustainable wildlife through visual analytics. Our approach's development, design, and usability highlight the potential of interactive visualizations in environmental policy and conservation efforts. The paper discusses the implications of human activities on wildlife, the significance of sustainable management, and how our visualizations contribute to addressing the biodiversity crisis.
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    Visual Scalar Matrix Evaluation: An Application to Thermodynamics
    (The Eurographics Association, 2024) Sohns, Jan-Tobias; Gond, Dominik; Jirasek, Fabian; Hasse, Hans; Leitte, Heike; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
    Modeling and predicting thermodynamic properties of binary mixtures is crucial in chemical engineering. Understanding how the mixture behavior, represented as a scalar matrix, depends on properties of pure substances offers valuable insights into substance interactions. While there is robust support for pattern-based sorting of matrices in general, limited support exists for evaluating patterns against external attributes available in many fields. In this paper, we introduce an interactive software to detect and analyze block patterns in scalar matrices using annotated domain knowledge. Therefore, we revisit canonical matrix patterns, explore their translation to this application, and describe a workflow to fit the matrix ordering. Our interactive software allows users to explore hierarchical aggregation levels, rating them based on additional domain-specific data properties of various type. Using our tool, chemical engineers are able to identify and interpret cluster structures in their mixture data. These insights contribute to the development of improved prediction methods for thermodynamic properties, forming the foundation for modeling and simulation in chemical engineering.
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    VisGap 2024: Frontmatter
    (The Eurographics Association, 2024) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
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    Performance Improvements of Poincaré Analysis for Exascale Fusion Simulations
    (The Eurographics Association, 2024) Pugmire, David; Choi, Jong Y.; Klasky, Scott; Moreland, Kenneth; Suchyta, Eric; Athawale, Tushar M.; Wang, Zhe; Chang, Choong-Seock; Ku, Seung-Hoe; Hager, Robert; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
    Understanding the time-varying magnetic field in a fusion device is critical for the successful design and construction of clean-burning fusion power plants. Poincaré analysis provides a powerful method for the visualization of magnetic fields in fusion devices. However, Poincaré plots can be very computationally expensive making it impractical, for example, to generate these plots in situ during a simulation. In this short paper, we describe a collaboration among computer science and physics researchers to develop a new Poincaré tool that provides a significant reduction in the time to generate analysis results.