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用于在空间多变量分析中平衡全局与细节的分辨率控制

Resolution Control for Balancing Overview + Detail in Spatial, Multivariate Analysis.

作者信息

Chen Jin, Maceachren Alan M

机构信息

GeoVISTA Center and Department of Geography, Pennsylvania State University, 302 Walker Building, University Park, PA16802,

出版信息

Cartogr J. 2008 Nov 1;45(4):261-273. doi: 10.1179/174327708x347764.

Abstract

Parallel coordinates, re-orderable matrices, and dendrograms are widely used for visual exploration of multivariate data. This research proposes an approach to systematically integrate the methods in a complementary manner for supporting multi-resolution visual data analysis with an enhanced overview+detail exploratory strategy. The paper focuses on three topics: (1) dynamic control across resolutions at which data are explored; (2) coordination and color mapping among the views; and (3) enhanced features of each view designed for the overview+detail exploratory tasks. We contend that systematically coordinating the views through user-controlled resolutions within a highly interactive analysis environment will boost productivity for exploration tasks. We offer a case study analysis to demonstrate this potential. The case study is focused on a complex, geographically referenced dataset including public health, demographic and environmental components.

摘要

平行坐标、可重新排序矩阵和树形图被广泛用于多变量数据的可视化探索。本研究提出了一种方法,以互补的方式系统地整合这些方法,以支持采用增强的概览+细节探索策略的多分辨率可视化数据分析。本文关注三个主题:(1)跨探索数据的分辨率进行动态控制;(2)视图之间的协调和颜色映射;(3)为概览+细节探索任务设计的每个视图的增强功能。我们认为,在高度交互式分析环境中通过用户控制的分辨率系统地协调视图将提高探索任务的效率。我们提供了一个案例研究分析来证明这种潜力。该案例研究聚焦于一个复杂的、包含公共卫生、人口统计和环境成分的地理参考数据集。

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