STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations

计算机科学 可扩展性 启发式 图形绘制 可视化 模块化设计 节点(物理) 集合(抽象数据类型) 整数规划 分布式计算 理论计算机科学 数据挖掘 程序设计语言 数据库 算法 结构工程 工程类 操作系统
作者
Sara Di Bartolomeo,Mirek Riedewald,Wolfgang Gatterbauer,Cody Dunne
出处
期刊:IEEE Transactions on Visualization and Computer Graphics [Institute of Electrical and Electronics Engineers]
卷期号:28 (1): 324-334 被引量:18
标识
DOI:10.1109/tvcg.2021.3114756
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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