Visual Analytics: Scope and Challenges
Visual Analytics: Scope and Challenges
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DOI：
10.1007/978-3-540-71080-6_6
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发表时间：
2008-01-01
期刊：
影响因子：
--
通讯作者：
Ziegler, Hartmut
中科院分区：
文献类型：
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作者：
Keim, Daniel A.;Mansmann, Florian;Ziegler, Hartmut
在当今的应用中，数据以前所未有的速度产生。虽然收集和存储新数据的能力迅速增长，但分析这些数据量的能力却以较低的速度增长。这种差距给分析过程带来了新的挑战，因为分析师、决策者、工程师或应急响应团队依赖于数据中隐藏的信息。视觉分析的新兴领域侧重于通过在分析过程中通过视觉表示和交互技术整合人类判断来处理这些海量、异构和动态的信息量。此外，正是可视化、数据挖掘和统计学等相关研究领域的结合，使可视化分析成为一个有前途的研究领域。本文旨在概述可视化分析、其范围和概念，解决最重要的研究挑战，并介绍各种应用场景的用例。
In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data rapidly grows, the ability to analyze these data volumes increases at much lower rates. This gap leads to new challenges in the analysis process, since analysts, decision makers, engineers, or emergency response teams depend on information hidden in the data. The emerging field of visual analytics focuses on handling these massive, heterogenous, and dynamic volumes of information by integrating human judgement by means of visual representations and interaction techniques in the analysis process. Furthermore, it is the combination of related research areas including visualization, data mining, and statistics that turns visual analytics into a promising field of research. This paper aims at providing an overview of visual analytics, its scope and concepts, addresses the most important research challenges and presents use cases from a wide variety of application scenarios.