Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data is uncertain is still an open research challenge. To address the problem of depicting uncertainty in set visualization, we ask (i) which aspects of set type data can be affected by uncertainty and (ii) which characteristics of uncertainty influence the visualization design. We answer these research questions by first developing a conceptual framework that brings together (i) the information that is primarily relevant in sets (i.e., set membership, set attributes, and element attributes) and (ii) different plausible categories of (un)certainty (i.e., certainty, undefined uncertainty as a binary fact, and defined uncertainty as quantifiable measure). Based on the conceptual framework, we systematically discuss visualization examples of integrating uncertainty in set visualizations. We draw on existing knowledge about general uncertainty visualization and fill gaps where set-specific aspects have not yet been considered sufficiently.
翻译:设置可视化有助于对集型数据的探索和分析。然而,当数据不确定时,各组应如何可视化仍然是一项公开的研究挑战。为了解决在设定可视化中描述不确定性的问题,我们询问:(一) 集型数据有哪些方面会受到不确定性的影响,以及(二) 不确定性的哪些特点会影响可视化设计。我们首先通过开发一个概念框架来回答这些研究问题,该框架将(一) 主要与集(即设定成员、设定属性和元素属性)有关的信息汇集在一起,(二) 不同可信的类别(不确定性(即确定性、未定义的不确定性作为二进制事实,以及界定的不确定性作为量化措施)。我们根据概念框架,系统地讨论将不确定性纳入集成可视化设计中的可视化实例。我们利用关于一般不确定性的可视化的现有知识,填补尚未充分考虑特定问题的空白。