基于多视图协同的时空数据可视分析方法

针对时空数据可视分析中存在的问题,提出了由可视分析模型(VAM)和交互协同模型(ICM)组成的多视图协同可视分析模型,将可视分析过程划分为数据变换、数据分析、可视映射和可视绘制4个过程;以可视分析过程中的参数作为协同主题,利用观察者模式,实现关联视图在交互过程中的协同一致;设计了Web环境下,基于"图数协同"和"图图协同"交互模式的多视图协同可视分析架构;构建了犯罪时空数据可视分析原型系统,并利用系统分析了福州市扒窃案的时空分布规律,对涉案价值较高的扒窃案进行了犯罪模式分析。

Spatio-Temporal Data Visual Analysis Method Based on Multiple-View Collaboration

According to requirements of crime visual analysis,a multi-view collaborative visual analysis model is proposed which contains a Visual Analysis Model (VAM) and a Interactive Collaborative Model (ICM).The corresponding process is divided into four steps which include data transformation,data analysis,visual mapping and visual drawing.Accordingly,the observer pattern is applied to realize the coordination of the related views in this interactive process.Furthermore,the architecture of multiple-view collaboration is designed based on "view-to-data" and "view-to-view" interaction Web patterns.Finally,a prototype system of spatio-temporal data visual analysis for crime in Fuzhou is designed and implemented which is used to analyze the spatiotemporal distribution of pickpocketing and a crime pattern for the high-value cases involving pickpocketing.