Big data visual analytics for exploratory earth system simulation analysis

被引：51

作者：

Steed, Chad A. ^{[1
]}

Ricciuto, Daniel M. ^{[1
]}

Shipman, Galen ^{[1
]}

Smith, Brian ^{[1
]}

Thornton, Peter E. ^{[1
]}

Wang, Dali ^{[1
]}

Shi, Xiaoying ^{[1
]}

Williams, Dean N. ^{[2
]}

机构：

[1] Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37831 USA

[2] Lawrence Livermore Natl Lab, Livermore, CA 94550 USA

来源：

COMPUTERS & GEOSCIENCES | 2013年 / 61卷

关键词：

Visualization; Parallel coordinates; Climate; Sensitivity analysis; Data intensive computing; Data mining; Statistical visualization; Multivariate; Big data; PARALLEL; VISUALIZATION;

D O I：

10.1016/j.cageo.2013.07.025

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called "big data" analysis challenges. However, conventional climate analysis techniques are inadequate in dealing with the complexities of today's data. In this paper, we describe and demonstrate a visual analytics system, called the Exploratory Data analysis ENvironment (EDEN), with specific application to the analysis of complex earth system simulation data sets. EDEN represents the type of interactive visual analysis tools that are necessary to transform data into insight, thereby improving critical comprehension of earth system processes. In addition to providing an overview of EDEN, we describe real-world studies using both point ensembles and global Community Land Model Version 4 (CLM4) simulations. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：71 / 82

页数：12

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