时空模拟数据可视化的多空间分析技术综述 <span></span>

doi:10.1016/j.visinf.2019.08.002

Vis Inf

2019, Vol. 3

Issue (3): 129-139 DOI: 10.1016/j.visinf.2019.08.002

论文

时空模拟数据可视化的多空间分析技术综述

Xueyi Chen^a, Liming Shen^a, Ziqi Sha^a, Richen Liu^a, Siming Chen^b,c, Genlin Ji^a, ChaoTan^a

^aSchool of Computer Science and Technology, Nanjing Normal University, No.1 Wenyuan Road, Qixia District, Nanjing, Jiangsu, PR China ^bFraunhofer Institute for Intelligent Analysis and Information Systems, Germany ^cUniversity of Bonn, Germany

A survey of Multi-space analysis techniques for spatio-temporal simulation data visualization

Xueyi Chen^a, Liming Shen^a, Ziqi Sha^a, Richen Liu^a, Siming Chen^b,c, Genlin Ji^a, ChaoTan^a

全文: PDF

摘要： 数值模拟在不同科学领域的广泛应用创造了各种研究机会。它们通常输出大量的时空模拟数据，按其特征可分为单程、多程、多变量、多模态和多维数据。从数据探索和分析的视角看，我们注意到许多聚焦于时空模拟数据的工作往往采用相似的探索技术，例如针对模拟空间、参数空间、特征空间以及它们的组合而设计的探索方案。然而，目前尚无对这些工作基本共性的系统性综述。在本综述中，我们基于新颖的多空间视角将代表当前水平的工作分为三大类。分类依据的是其采用的相类似的技术：模拟空间中的可视化设计(可视化映射、基于盒形图的可视化概览等)、参数空间分析(可视导航、参数空间投影等)和特征空间中的数据处理(特征定义和提取、模拟数据的采样、简化和聚类等)。

Abstract: The widespread use of numerical simulations in different scientific domains provides a variety of research opportunities. They often output a great deal of spatio-temporal simulation data, which are traditionally characterized as single-run, multi-run, multi-variate, multi-modal and multi-dimensional. From the perspective of data exploration and analysis, we noticed that many works focusing on spatio-temporal simulation data often share similar exploration techniques, for example, the exploration schemes designed in simulation space, parameter space, feature space and combinations of them. However, it lacks a survey to have a systematic overview of the essential commonalities shared by those works. In this survey, we take a novel multi-space perspective to categorize the state-of-the-art works into three major categories. Specifically, the works are characterized as using similar techniques such as visual designs in simulation space (e.g, visual mapping, boxplot-based visual summarization, etc.), parameter space analysis (e.g, visual steering, parameter space projection, etc.) and data processing in feature space (e.g, feature definition and extraction, sampling, reduction and clustering of simulation data, etc.).

Key words: Simulation data visualization Spatio-temporal data visualization Comparative visualization

出版日期: 2019-09-09

通讯作者: Richen Liu E-mail: richen@pku.edu.cn

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引用本文:

Xueyi Chen, Liming Shen, Ziqi Sha, Richen Liu, Siming Chen, Genlin Ji, ChaoTan. A survey of Multi-space analysis techniques for spatio-temporal simulation data visualization. Vis Inf, 2019, 3(3): 129-139.

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http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2019.08.002 或 http://www.zjujournals.com/vi/CN/Y2019/V3/I3/129

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