Tracking the sensemaking process is a well-established practice in many data analysis tools, and many visualization tools facilitate overview and recall during and after exploration. However, the resulting communication materials such as presentations or infographics often omit provenance information for the sake of simplicity. This unfortunately limits later viewers from engaging in further collaborative sensemaking or discussion about the analysis. We present a design study where we introduced visual provenance and analytics to urban transportation planning. Maintaining the provenance of all analyses was critical to support collaborative sensemaking among the many and diverse stakeholders. Our system, STORYFACETS, exposes several different views of the same analysis session, each view designed for a specific audience: (1) the trail view provides a data flow canvas that supports in-depth exploration + provenance (expert analysts); (2) the dashboard view organizes visualizations and other content into a space-filling layout to support high-level analysis (managers); and (3) the slideshow view supports linear storytelling via interactive step-by-step presentations (laypersons). Views are linked so that when one is changed, provenance is maintained. Visual provenance is available on demand to support iterative sensemaking for any team member.

在许多数据分析工具中，跟踪意义构建过程是一种成熟的做法，许多可视化工具有助于在探索期间和之后进行概览和回忆。然而，为了简单起见，由此产生的交流材料（例如演示文稿或信息图表）通常会省略出处信息。不幸的是，这限制了后来的观众参与进一步的协作意义构建或关于分析的讨论。我们提出了一项设计研究，在该研究中，我们将视觉来源和分析引入了城市交通规划。保持所有分析的来源对于支持众多不同利益相关者之间的协作意义构建至关重要。我们的系统 STORYFACETS 公开了同一分析会话的多个不同视图，每个视图都是为特定受众设计的：(1)轨迹视图提供了一个数据流画布，支持深度探索+出处（专家分析师）；(2)仪表板视图将可视化和其他内容组织成一个空间填充布局，以支持高级分析（管理器）；(3)幻灯片视图通过交互式分步演示（外行）支持线性叙事。视图是相互关联的，因此当一个视图发生变化时，可以保持其出处。视觉来源可按需提供，以支持任何团队成员的迭代意义构建。