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VisFlow - Web-based Visualization Framework for Tabular Data with a Subset Flow Model

机译:VisFlow-具有子集流模型的表格数据的基于Web的可视化框架

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Data flow systems allow the user to design a flow diagram that specifies the relations between system components which process, filter or visually present the data. Visualization systems may benefit from user-defined data flows as an analysis typically consists of rendering multiple plots on demand and performing different types of interactive queries across coordinated views. In this paper, we propose VisFlow, a web-based visualization framework for tabular data that employs a specific type of data flow model called the subset flow model. VisFlow focuses on interactive queries within the data flow, overcoming the limitation of interactivity from past computational data flow systems. In particular, VisFlow applies embedded visualizations and supports interactive selections, brushing and linking within a visualization-oriented data flow. The model requires all data transmitted by the flow to be a data item subset (i.e. groups of table rows) of some original input table, so that rendering properties can be assigned to the subset unambiguously for tracking and comparison. VisFlow features the analysis flexibility of a flow diagram, and at the same time reduces the diagram complexity and improves usability. We demonstrate the capability of VisFlow on two case studies with domain experts on real-world datasets showing that VisFlow is capable of accomplishing a considerable set of visualization and analysis tasks. The VisFlow system is available as open source on GitHub.
机译:数据流系统允许用户设计一个流程图,该流程图指定处理,过滤或视觉呈现数据的系统组件之间的关系。可视化系统可能会受益于用户定义的数据流,因为分析通常包括按需绘制多个图并在协调视图之间执行不同类型的交互式查询。在本文中,我们提出了VisFlow,这是一种基于Web的表格数据可视化框架,它采用一种称为子集流模型的特定类型的数据流模型。 VisFlow专注于数据流中的交互式查询,克服了过去的计算数据流系统的交互性限制。特别是,VisFlow应用嵌入式可视化,并在面向可视化的数据流中支持交互式选择,刷入和链接。该模型要求流所传输的所有数据都是某个原始输入表的数据项子集(即表行的组),以便可以将渲染属性明确地分配给该子集以进行跟踪和比较。 VisFlow具有流程图分析的灵活性,同时降低了图表的复杂性并提高了可用性。我们与领域专家在真实数据集上的两个案例研究中展示了VisFlow的功能,这些案例研究表明VisFlow能够完成大量可视化和分析任务。 VisFlow系统可在GitHub上以开源形式获得。

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