Ensemble Visual Analysis Architecture with High Mobility for Large-Scale Critical Infrastructure Simulations

被引:1
|
作者
Eaglin, Todd [1 ]
Wang, Xiaoyu [1 ]
Ribarsky, William [1 ]
Tolone, William [1 ]
机构
[1] Univ N Carolina, Charlotte Visualizat Ctr, Dept Comp Sci, Charlotte, NC 28269 USA
来源
VISUALIZATION AND DATA ANALYSIS 2015 | 2015年 / 9397卷
关键词
Disaster Forecast; Critical Infrastructure Simulation; Visual Analytics; Mobile Interface; VISUALIZATION;
D O I
10.1117/12.2076472
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowhere is the need to understand large heterogeneous datasets more important than in disaster monitoring and emergency response, where critical decisions have to be made in a timely fashion and the discovery of important events requires an understanding of a collection of complex simulations. To gain enough insights for actionable knowledge, the development of models and analysis of modeling results usually requires that models be run many times so that all possibilities can be covered. Central to the goal of our research is, therefore, the use of ensemble visualization of a large scale simulation space to appropriately aid decision makers in reasoning about infrastructure behaviors and vulnerabilities in support of critical infrastructure analysis. This requires the bringing together of computing-driven simulation results with the human decision- making process via interactive visual analysis. We have developed a general critical infrastructure simulation and analysis system for situationally aware emergency response during natural disasters. Our system demonstrates a scalable visual analytics infrastructure with mobile interface for analysis, visualization and interaction with large-scale simulation results in order to better understand their inherent structure and predictive capabilities. To generalize the mobile aspect, we introduce mobility as a design consideration for the system. The utility and efficacy of this research has been evaluated by domain practitioners and disaster response managers.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Large-scale taxi O/D visual analytics for understanding metropolitan human movement patterns
    Jiang, Xiaorui
    Zheng, Chunyi
    Tian, Ya
    Liang, Ronghua
    JOURNAL OF VISUALIZATION, 2015, 18 (02) : 185 - 200
  • [32] Visual software analytics for the build optimization of large-scale software systems
    Alexandru Telea
    Lucian Voinea
    Computational Statistics, 2011, 26 : 635 - 654
  • [33] Visual software analytics for the build optimization of large-scale software systems
    Telea, Alexandru
    Voinea, Lucian
    COMPUTATIONAL STATISTICS, 2011, 26 (04) : 635 - 654
  • [34] BANKSAFE: Visual analytics for big data in large-scale computer networks
    Fischer, Fabian
    Fuchs, Johannes
    Mansmann, Florian
    Keim, Daniel A.
    INFORMATION VISUALIZATION, 2015, 14 (01) : 51 - 61
  • [35] Visual Diagnostics of Parallel Performance in Training Large-Scale DNN Models
    Wei, Yating
    Wang, Zhiyong
    Wang, Zhongwei
    Dai, Yong
    Ou, Gongchang
    Gao, Han
    Yang, Haitao
    Wang, Yue
    Cao, Caleb Chen
    Weng, Luoxuan
    Lu, Jiaying
    Zhu, Rongchen
    Chen, Wei
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2024, 30 (07) : 3915 - 3929
  • [36] Visual Analytics to make sense of large-scale administrative and normative data
    Guarino, Alfonso
    Lettieri, Nicola
    Malandrino, Delfina
    Russo, Pietro
    Zaccagnino, Rocco
    2019 23RD INTERNATIONAL CONFERENCE INFORMATION VISUALISATION (IV): BIOMEDICAL VISUALIZATION AND GEOMETRIC MODELLING & IMAGING, 2019, : 133 - 138
  • [37] InSight2: A Modular Visual Analysis Platform for Network Situational Awareness in Large-Scale Networks
    Kodituwakku, Hansaka Angel Dias Edirisinghe
    Keller, Alex
    Gregor, Jens
    ELECTRONICS, 2020, 9 (10) : 1 - 15
  • [38] SwiftTuna: Responsive and Incremental Visual Exploration of Large-scale Multidimensional Data
    Jo, Jaemin
    Kim, Wonjae
    Yoo, Seunghoon
    Kim, Bohyoung
    Seo, Jinwook
    2017 IEEE PACIFIC VISUALIZATION SYMPOSIUM (PACIFICVIS), 2017, : 131 - 140
  • [39] Visualizing Large-scale and High-dimensional Data
    Tang, Jian
    Liu, Jingzhou
    Zhang, Ming
    Mei, Qiaozhu
    PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'16), 2016, : 287 - 297
  • [40] Visualization Techniques for Studying Large-Scale Flow Fields from Fusion Simulations
    Sauer, Franz
    Zhang, Yubo
    Wang, Weixing
    Ethier, Stephane
    Ma, Kwan-Liu
    COMPUTING IN SCIENCE & ENGINEERING, 2016, 18 (02) : 68 - 77