EuroVisShort2019

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https://diglib.eg.org/handle/10.2312/2632781

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Browsing EuroVisShort2019 by Subject "Information systems"

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    A Construction Kit for Visual Exploration Interfaces
    (The Eurographics Association, 2019) Keck, Mandy; Groh, Rainer; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    With a continuously increasing amount of data and resources on the internet and in large document collections, effective visual exploration interfaces are becoming more and more important. In recent years, many novel approaches have been proposed for the exploration of complex, multidimensional data sets. However, little guidance is available for designers to create similar solutions and to reuse established patterns. In this paper, we propose a construction kit for visual exploration interfaces. It provides a set of building blocks that can be easily combined with each other. These building blocks can support the designer in the creation of novel visual exploration interfaces but also in the analysis and variation of existing interface solutions. Furthermore, we present a workshop method that evaluates the application of the construction kit for the creation and analysis of visual exploration interfaces.
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    Highly Efficient Controlled Hierarchical Data Reduction techniques for Interactive Visualization of Massive Simulation Data
    (The Eurographics Association, 2019) Dubois, Jérôme; Lekien, Jacques-Bernard; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    With the constant increase in compute power of supercomputers, high performance computing simulations are producing higher fidelity results and possibly massive amounts of data. To keep visualization of such results interactive, existing techniques such as Adaptive Mesh Refinement (AMR) can be of use. In particular, Tree-Based AMR methods (TB-AMR) are widespread in simulations and are becoming more present in general purpose visualization pipelines such as VTK. In this work, we show how TB-AMR data structures could lead to more efficient exploration of massive data sets in the Exascale era. We discuss how algorithms (filters) should be designed to take advantage of tree-like data structures for both data filtering or rendering. By introducing controlled hierarchical data reduction we greatly reduce the processing time for existing algorithms, sometimes with no visual impact, and drastically decrease exploration time for analysts. Also thanks to the techniques and implementations we propose, visualization of very large data is made possible on very constrained resources. These ideas are illustrated on million to billion-scale native TB-AMR or resampled meshes, with the HyperTreeGrid object and associated filters we have recently optimized and made available in the Visualisation Toolkit (VTK) for use by the scientific community.