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Characterizing Users' Visual Analytic Activity For Insight Provenance

机译：表征用户的视觉分析活动以获取洞察源

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摘要

Insight provenance - a historical record of the process and ratio-nale by which an insight is derived - is an essential requirement in many visual analytics applications. Although work in this area has relied on either manu-ally recorded provenance (for example, user notes) or automatically recorded event-based insight provenance (for example, clicks, drags and key-presses), both approaches have fundamental limitations. Our aim is to develop a new approach that combines the benefits of both approaches while avoiding their deficiencies. Toward this goal, we characterize users' visual analytic activity at multiple levels of granularity. Moreover, we identify a critical level of abstrac-tion, Actions, that can be used to represent visual analytic activity with a set of general but semantically meaningful behavior types. In turn, the action types can be used as the semantic building blocks for insight provenance. We present a catalog of common actions identified through observations of several different visual analytic systems. In addition, we define a taxonomy to categorize actions into three major classes based on their semantic intent. The concept of actions has been integrated into our lab's prototype visual analytic system, HARVEST, as the basis for its insight provenance capabilities.
机译：洞察出处-产生洞察力的过程和比率的历史记录，是许多视觉分析应用程序的基本要求。尽管该领域的工作依赖于手动记录的来源（例如，用户注释）或自动记录的基于事件的洞察来源（例如，单击，拖动和按键），但这两种方法都有根本的局限性。我们的目标是开发一种新方法，该方法结合了这两种方法的优点，同时避免了它们的不足。为了实现这一目标，我们在多个粒度级别上刻画了用户的视觉分析活动。此外，我们确定了一个关键的抽象级别，即动作，可用于表示具有一系列常规但对语义有意义的行为类型的视觉分析活动。反过来，动作类型可以用作洞察出处的语义构建块。我们提供了通过观察几种不同的视觉分析系统而识别出的常见动作的目录。此外，我们定义了一个分类法，根据动作的语义意图将动作分为三大类。动作的概念已集成到我们实验室的原型视觉分析系统HARVEST中，作为其洞察力来源功能的基础。

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