复杂沉浸式可视化的实验设计

D. Clark, B. Turnbull
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引用次数: 1

摘要

与数据分析的替代方法相比,专注于评估复杂可视化方法价值的实验具有挑战性。参与者的先验知识和经验之间的相互作用,各种各样的实验或现实世界数据集以及与显示系统的动态交互在寻求及时,负担得起和统计相关的实验结果时提出了挑战。本文概述了一种混合方法,用于实验复杂的交互式数据分析工具,特别是计算机网络流量分析。该方法包括由专家参与者在自由使用软件平台后完成的结构化调查。该调查收集了与体验相关的客观和主观数据点,目的是对软件性能进行评估,并得到统计上显着的实验结果的支持。这项工作特别适用于网络安全领域的网络分析,也适用于军事网络作战和情报数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experiment Design for Complex Immersive Visualisation
Experimentation focused on assessing the value of complex visualisation approaches when compared with alternative methods for data analysis is challenging. The interaction between participant prior knowledge and experience, a diverse range of experimental or real-world data sets and a dynamic interaction with the display system presents challenges when seeking timely, affordable and statistically relevant experimentation results. This paper outlines a hybrid approach proposed for experimentation with complex interactive data analysis tools, specifically for computer network traffic analysis. The approach involves a structured survey completed after free engagement with the software platform by expert participants. The survey captures objective and subjective data points relating to the experience with the goal of making an assessment of software performance which is supported by statistically significant experimental results. This work is particularly applicable to field of network analysis for cyber security and also military cyber operations and intelligence data analysis.
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