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保持多种视图一致:可视化创作中的约束、验证和异常。

Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring.

出版信息

IEEE Trans Vis Comput Graph. 2018 Jan;24(1):468-477. doi: 10.1109/TVCG.2017.2744198. Epub 2017 Aug 29.

DOI:10.1109/TVCG.2017.2744198
PMID:28866529
Abstract

Visualizations often appear in multiples, either in a single display (e.g., small multiples, dashboard) or across time or space (e.g., slideshow, set of dashboards). However, existing visualization design guidelines typically focus on single rather than multiple views. Solely following these guidelines can lead to effective yet inconsistent views (e.g., the same field has different axes domains across charts), making interpretation slow and error-prone. Moreover, little is known how consistency balances with other design considerations, making it difficult to incorporate consistency mechanisms in visualization authoring software. We present a wizard-of-oz study in which we observed how Tableau users achieve and sacrifice consistency in an exploration-to-presentation visualization design scenario. We extend (from our prior work) a set of encoding-specific constraints defining consistency across multiple views. Using the constraints as a checklist in our study, we observed cases where participants spontaneously maintained consistent encodings and warned cases where consistency was overlooked. In response to the warnings, participants either revised views for consistency or stated why they thought consistency should be overwritten. We categorize participants' actions and responses as constraint validations and exceptions, depicting the relative importance of consistency and other design considerations under various circumstances (e.g., data cardinality, available encoding resources, chart layout). We discuss automatic consistency checking as a constraint-satisfaction problem and provide design implications for communicating inconsistencies to users.

摘要

可视化通常以多个形式出现,无论是在单个显示中(例如,小倍数、仪表板)还是跨越时间或空间(例如,幻灯片、一组仪表板)。然而,现有的可视化设计指南通常侧重于单个视图,而不是多个视图。仅仅遵循这些指南可能会导致有效的但不一致的视图(例如,同一字段在图表之间具有不同的轴域),从而使解释变得缓慢且容易出错。此外,人们对一致性如何与其他设计考虑因素平衡知之甚少,这使得在可视化创作软件中很难纳入一致性机制。我们进行了一项“专家系统”研究,观察了 Tableau 用户在探索到演示的可视化设计场景中如何实现和牺牲一致性。我们扩展了(来自我们之前的工作)一套针对多个视图的一致性的特定编码约束。在我们的研究中,使用这些约束作为清单,我们观察到参与者自发地保持一致编码的情况,并警告忽略一致性的情况。针对这些警告,参与者要么为了一致性而修改视图,要么说明他们认为应该覆盖一致性的原因。我们将参与者的行为和响应分类为约束验证和异常,描绘了在各种情况下(例如,数据基数、可用编码资源、图表布局)一致性和其他设计考虑因素的相对重要性。我们将自动一致性检查视为约束满足问题,并为向用户传达不一致性提供设计启示。

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