Human-Centric Situational Awareness and Big Data Visualization
Human-Centric Situational Awareness and Big Data Visualization
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DOI：
10.29007/mq54
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发表时间：
2019-09
期刊：
影响因子：
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通讯作者：
S. Bodempudi;Sharad Sharma;A. Sahu;R. Agrawal
中科院分区：
文献类型：
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作者：
S. Bodempudi;Sharad Sharma;A. Sahu;R. Agrawal
为了有效地分析大数据，需要以人为中心的态势感知和可视化。其中一个挑战是创建一个算法来分析给定的数据，而不需要任何其他数据分析工具的帮助。这项研究旨在确定图形对象（如数据形状）是如何根据分析师的心智模型开发的，从而增强分析师的情境意识。我们改进大数据可视化的方法是双重的，既关注可视化，也关注交互。本文介绍了基于力向模型图的三维数据和图形技术。它是使用Unity 3D游戏引擎开发的。利用不同的数据集进行了试点测试，以检验系统在沉浸式环境和非沉浸式环境下的效率。应用程序能够在数据可视化中成功地处理给定数据集的数据。目前的图可以实时渲染大约200到300个链接节点。
Human-centric situational awareness and visualization are needed for analyzing the big data in an efficient way. One of the challenges is to create an algorithm to analyze the given data without any help of other data analyzing tools. This research effort aims to identify how graphical objects (such as data-shapes) developed in accordance with an analyst's mental model can enhance analyst's situation awareness. Our approach for improved big data visualization is two-fold, focusing on both visualization and interaction. This paper presents the developed data and graph technique based on forcedirected model graph in 3D. It is developed using Unity 3D gaming engine. Pilot testing was done with different data sets for checking the efficiency of the system in immersive environment and non-immersive environment. The application is able to handle the data successfully for the given data sets in data visualization. The currently graph can render around 200 to 300 linked nodes in real-time.