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An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context 被引量:1
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作者 Zhiyuan Zhang Xiaonan Tong +3 位作者 Kevin T. McDonnell Alla Zelenyuk Dan Imre Klaus Mueller 《Tsinghua Science and Technology》 SCIE EI CAS 2013年第2期111-124,共14页
Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a mul... Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multifield visualization problem, where the geo-space provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivariate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixed-window brushing and correlation-enhanced display. We conceived our system with a team of climate researchers, who already made a few important discoveries using it. This demonstrates our system's great potential to enable scientific discoveries, possibly also in other domains where data have a geospatial reference. 展开更多
关键词 geospatial visualization visual analytics information visualization multivariate visualization parallel coordinates coordinated displays linking and brushing
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