邦妮:从值得关注的互动事件中构建在线叙事

V. Segura, J. Ferreira, Simone Diniz Junqueira Barbosa
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引用次数: 1

摘要

在使用可视化分析应用程序进行意义生成过程之后,主要的挑战是过滤导致发现的基本信息,并将发现传达给其他人。我们建议利用探索性数据分析留下的交互痕迹,用一种新颖的可视化方式来帮助这一过程。通过跟踪,用户可以选择想要的值得注意的交互步骤,并创建他/她自己的交互的视觉叙述,与读者分享获得的知识。为了实现我们的目标,我们开发了BONNIE(从值得注意的互动事件中构建在线叙事)框架。它包括一个日志模型,用于注册交互事件和一个可视化环境,供用户查看他们自己的交互历史并构建他们的可视化叙述。本文提出了我们在可视化分析应用程序、BONNIE可视化环境中交流发现的建议,以及我们为评估我们的解决方案而进行的实证研究。
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BONNIE: Building Online Narratives from Noteworthy Interaction Events
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.
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