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BONNIE: Building Online Narratives from Noteworthy Interaction Events

机译:Bonnie:从有值得注意的互动事件中建立在线叙述

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After a sensemaking process using a visual analytics application, a major challenge is to filter the essential information that led to a discovery and to communicate the findings to other people. We propose to take advantage of the interaction trace left by the exploratory data analysis, presenting it with a novel visualization to aid in this process. With the trace, the user can choose the desired noteworthy interaction steps and create a visual narrative of his/her own interaction, sharing the acquired knowledge with readers. To achieve our goal, we have developed the BONNIE (Building Online Narratives from Noteworthy Interaction Events) framework. It comprises a log model to register the interaction events and a visualization environment for users to view their own interaction history and to build their visual narratives. This paper presents our proposal for communicating discoveries in visual analytics applications, the BONNIE visualization environment, and an empirical study we conducted to evaluate our solution.
机译:在使用视觉分析应用程序的传感过程之后,主要挑战是过滤导致发现的基本信息并将研究结果传达给其他人。我们建议利用探索性数据分析留下的相互作用痕迹,以新颖的可视化呈现,以帮助辅助该过程。通过跟踪,用户可以选择所需的值得注意的交互步骤,并创建他/她自己的互动的视觉叙述,与读者共享获取的知识。为实现我们的目标,我们开发了Bonnie(从有值得注意的互动事件中建立在线叙述)框架。它包括日志模型,用于注册交互事件和可视化环境,以便用户查看自己的交互历史记录并构建其视觉叙述。本文提出了我们在视觉分析应用程序,Bonnie可视化环境中沟通发现的建议,以及我们进行的实证研究以评估我们的解决方案。

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