DaisyVA:支持信息多面体可视分析的智能交互式可视化平台

DaisyVA:an Intelligent Interactive Visualization Platform for Visual Analysis of Multi-facet Information

针对目前缺乏有效地支持信息多面体可视分析的交互式信息可视化平台的问题,提出并实现了一个面向最终用户的交互式可视化平台DaisyVA.首先建立了一个支持信息多面体可视分析界面模型IMFA,并定义了IMFA的多面体数据模型、可视表征模型和交互控制模型;然后围绕IMFA设计了DaisyVA的体系架构,讨论了基于模型的系统开发机制、核心模块与运行时框架机理,以及DaisyVA组件库;最后将DaisyVA应用于大型集团制造企业物流网络瓶颈的可视分析实例中.实例分析结果表明,DaisyVA能为多面体数据提供统一建模的支持和可扩展可视化算法库的支持、提供多种所需的交互技术并可灵活定制可视分析的交互任务、支持信息多面体间的内在语义关联分析,以及能够为最终用户提供一种简单快速原型方法,因此能够为信息多面体可视分析提供一种有效的支持.

Visual analytics for multi-facet information has become a hot topic recently in research areas related to information visualization and human computer interaction. However, there are few interactive visualization platform and toolkit which can effectively support multi-facet analysis. To address this challenge, this paper presents DaisyVA, an intelligent interactive visualization platform. First, an interface model is established to describe interfaces for multi-facet analysis, which includes three sub-models, data model, visualization model, and control model. Second, the fundamental architecture and key techniques such as model-based prototype generation, runtime framework, and libraries are described. Finally, DaisyVA is applied to a visual analytics application of networked manufacturing enterprise. Experimental results show that DaisyVA is an effective platform to help end-users develop visual analytics applications for multi-facet information.