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Passage à l'échelle pour la visualisation interactive exploratoire de données : approches par abstraction et par déformation spatiale

Abstract : Interactive visualization is helpful for exploring, understanding, and analyzing data. However, increasingly large and complex data challenges the efficiency of visualization systems, both visually and computationally. The visual challenge stems from human perceptual and cognitive limitations as well as screen space limitations while the computational challenge stems from the processing and memory limitations of standard computers.In this thesis, we present techniques addressing the two scalability issues for several interactive visualization applications.To address visual scalability requirements, we present a versatile spatial-distortion approach for linked emphasis on multiple views and an abstract and multi-scale representation based on parallel coordinates. Spatial distortion aims at alleviating the weakened emphasis effect of highlighting when applied to small-sized visual elements. Multiscale abstraction simplifies the representation while providing detail on demand by pre-aggregating data at several levels of detail.To address computational scalability requirements and scale data processing to billions of items in interactive times, we use pre-computation and real-time computation on a remote distributed infrastructure. We present a system for multi-/dimensional data exploration in which the interactions and abstract representation comply with a visual item budget and in return provides a guarantee on network-related interaction latencies. With the same goal, we compared several geometric reduction strategies for the reconstruction of density maps of large-scale point sets.
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Gaëlle Richer. Passage à l'échelle pour la visualisation interactive exploratoire de données : approches par abstraction et par déformation spatiale. Algorithme et structure de données [cs.DS]. Université de Bordeaux, 2019. Français. ⟨NNT : 2019BORD0264⟩. ⟨tel-02453395⟩

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