ReVize: A Library for Visualization Toolchaining with Vega-Lite

ReVize: A Library for Visualization Toolchaining with Vega-Lite
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ReVize:使用 Vega-Lite 进行可视化工具链的库

DOI:
10.2312/stag.20191375
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发表时间:
2019
期刊:
2014 IEEE International Conference on Big Data (Big Data)
影响因子:
--
通讯作者:
Hans
Hans
中科院分区:
--
文献类型:
--
作者:
Marius Hogräfer;Hans

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近年来,数据可视化工具的领域一直在增长,每种工具都提供了创建和使用可视化的新方法,并且每种工具都提供了一组专门的功能,交互隐喻和用户界面。这意味着一方面,用户在可视化工具方面有广泛的选择。但另一方面,这种选择也可能会锁定用户:一旦做出选择,就很难,有时甚至不可能切换到另一个工具-例如,进一步完善一个工具在另一个工具中的可视化。反过来,用户被迫解决所选工具的任何缺点,因为切换到另一个工具更加麻烦。在本文中,我们介绍了ReVize,一个用于可视化工具链的开源库。ReVize使用Vega-Lite作为一种通用的交换格式,能够为基于Web的工具添加工具链支持。与现有的方法相比,可视化工具链的这种解决方案允许以来回的方式利用多个工具创作可视化,而不需要使用工具的预设顺序。我们通过向三个现有工具(KNIME、ColorBrewer和VisFlow)添加工具链支持来演示ReVize,以便协同使用它们来创作可视化。
The field of tools for data visualization has been growing in recent years, with each tool contributing new ways to create and work with visualizations, and each offering a specialized set of features, interaction metaphors and user interfaces. This means on one hand that users have a wide choice in visualization tools. On the other hand, though, this choice might also lock-in the user: Once made, it becomes difficult and sometimes even impossible to switch to another tool – e.g., to further refine a visualization made in one tool inside another. In turn, users are forced to work around any shortcomings of the chosen tool, as switching to another tool is even more cumbersome. In this paper, we introduce ReVize, an open-source library for visualization toolchaining. ReVize makes use of Vega-Lite as a common exchange format to be able to add toolchain support to web-based tools. In contrast to existing approaches, this solution to visualization toolchaining allows for authoring a visualization with multiple tools in a back-and-forth fashion, without a preset order in which tools are to be used. We demonstrate ReVize by adding toolchain support to three existing tools – KNIME, ColorBrewer, and VisFlow – for using them in concert to author visualizations.
多个独立可视化分析工具的轻量级协调
DOI: 10.5220/0007571101060117
发表时间: 2019
期刊:
影响因子: --
作者:
H. Schulz;M. Röhlig;L. Nonnemann;M. Aehnelt;H. Diener;B. Urban;H. Schumann
通讯作者: H. Schumann