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Timeline and visualization of multiple-data sets and the visualization querying challenge

机译:多个数据集的时间表和可视化以及可视化查询挑战

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Data in its raw form can potentially contain valuable information, but much of that value is lost if it cannot be presented to a user in a way that is useful and meaningful. Data visualization techniques offer a solution to this issue. Such methods are especially useful in spatial data domains such as medical scan data and geophysical data. However, to properly see trends in data or to relate data from multiple sources, multiple-data set visualization techniques must be used. In research with the time-line paradigm, we have integrated multiple streaming data sources into a single visual interface. Data visualization takes place on several levels, from the visualization of query results in a time-line fashion to using multiple visualization techniques to view, analyze, and compare the data from the results. A significant contribution of this research effort is the extension and combination of existing research efforts into the visualization of multiple-data sets to create new and more flexible techniques. We specifically address visualization issues regarding clarity, speed, and interactivity. The developed visualization tools have also led recently to the visualization querying paradigm and challenge highlighted herein.
机译:原始格式的数据可能包含有价值的信息,但是如果无法以有用和有意义的方式将其提供给用户,则大部分价值将丢失。数据可视化技术为该问题提供了解决方案。这样的方法在诸如医学扫描数据和地球物理数据的空间数据域中特别有用。但是,要正确查看数据趋势或关联来自多个源的数据,必须使用多数据集可视化技术。在时间轴范式的研究中,我们将多个流数据源集成到单个可视界面中。数据可视化发生在多个级别上,从以时间轴方式对查询结果进行可视化,到使用多种可视化技术来查看,分析和比较结果数据。这项研究工作的重大贡献是将现有研究工作扩展并组合到多个数据集的可视化中,以创建新的,更灵活的技术。我们专门解决有关清晰度,速度和交互性的可视化问题。所开发的可视化工具最近还导致了此处突出显示的可视化查询范例和挑战。

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