STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations
Sara Di Bartolomeo, Mirek Riedewald, Wolfgang Gatterbauer, Cody Dunne
摘要
Node-link visualizations are a familiar and powerful tool for displaying the relationships in a network. The readability of these visualizations highly depends on the spatial layout used for the nodes. In this paper, we focus on computing layered layouts, in which nodes are aligned on a set of parallel axes to better expose hierarchical or sequential relationships. Heuristic-based layouts are widely used as they scale well to larger networks and usually create readable, albeit sub-optimal, visualizations. We instead use a layout optimization model that prioritizes optimality - as compared to scalability - because an optimal solution not only represents the best attainable result, but can also serve as a baseline to evaluate the effectiveness of layout heuristics. We take an important step towards powerful and flexible network visualization by proposing Stratisfimal Layout, a modular integer-linear-programming formulation that can consider several important readability criteria simultaneously - crossing reduction, edge bendiness, and nested and multi-layer groups. The layout can be adapted to diverse use cases through its modularity. Individual features can be enabled and customized depending on the application. We provide open-source and documented implementations of the layout, both for web-based and desktop visualizations. As a proof-of-concept, we apply it to the problem of visualizing complicated SQL queries, which have features that we believe cannot be addressed by existing layout optimization models. We also include a benchmark network generator and the results of an empirical evaluation to assess the performance trade-offs of our design choices. A full version of this paper with all appendices, data, and source code is available at osf.io/qdyt9 with live examples at https://visdunneright.github.io/stratisfimal/.
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- On The Reasonable Effectiveness of Relational Diagrams: Explaining Relational Query Patterns and the Pattern Expressiveness of Relational LanguagesWolfgang Gatterbauer, Cody DunneSIGMOD 2024 · 被引用 6 次
- QEVIS: Multi-Grained Visualization of Distributed Query ExecutionQiaomu Shen, Zhengxin You, Xiao Yan, Chaozu Zhang 等IEEE VIS 2023 · 被引用 5 次
- Evaluating and Extending Speedup Techniques for Optimal Crossing Minimization in Layered Graph DrawingsConnor Wilson, Eduardo Puerta, Tarik Crnovrsanin, Sara Di Bartolomeo 等IEEE VIS 2024 · 被引用 3 次
- Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric VisualizationsJohannes Fuchs, Alexander Frings, Maria-Viktoria Heinle, Daniel A. Keim 等IEEE VIS 2024 · 被引用 3 次
- QOVIS: Understanding and Diagnosing Query Optimizer via a Visualization-assisted Approach (Revision)Zhengxin You, Qiaomu Shen, Man Lung Yiu, Bo TangVLDB 2025 · 被引用 1 次
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