A typical problem in Visual Analytics is that users are highly trained experts in their application domains, but have mostly no experience in using VA systems. Thus, users often have difficulties interpreting and working with visual representations. To overcome these problems, user assistance can be incorporated into VA systems to guide experts through the analysis while closing their knowledge gaps. Different types of user assistance can be applied to extend the power of VA, enhance the user's experience, and broaden the audience for VA. Although different approaches to visualization onboarding and guidance in VA already exist, there is a lack of research on how to design and integrate them in effective and efficient ways. Therefore, we aim at putting together the pieces of the mosaic to form a coherent whole. Based on the Knowledge-Assisted Visual Analytics model, we contribute a conceptual model of user assistance for VA by integrating the process of visualization onboarding and guidance as the two main approaches in this direction. As a result, we clarify and discuss the commonalities and differences between visualization onboarding and guidance, and discuss how they benefit from the integration of knowledge extraction and exploration. Finally, we discuss our descriptive model by applying it to VA tools integrating visualization onboarding and guidance, and showing how they should be utilized in different phases of the analysis in order to be effective and accepted by the user.
翻译:视觉分析的典型问题是,用户在其应用领域是训练有素的专家,但在使用VA系统方面基本上没有经验,因此,用户往往难以解释和运用视觉演示,因此,用户协助可以纳入VA系统,通过分析指导专家,缩小知识差距;不同种类的用户协助可以用来扩大VA的力量,提高用户的经验,扩大VA的受众。虽然在VA的可视登上和指导方面已经存在不同的做法,但是,对于如何以有效和高效的方式设计和整合这些系统缺乏研究。因此,我们的目标是将马赛克拼图集成成一个连贯的整体,在知识辅助视觉分析模型的基础上,我们为VA提供用户协助的概念模式,将登上视觉和指导过程作为这一方向的两个主要方法加以整合。结果,我们澄清和讨论登上视觉和指导之间的共性和差异,并讨论他们如何从知识集成集成和集成知识提取和探索中获益。最后,我们根据知识辅助视觉分析模型,我们如何在视觉分析中采用不同的分析工具来展示。