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Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling

机译:支持故事综合:弥合视觉分析与讲故事之间的差距

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摘要

Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques supporting the analysis. Findings and results of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems. However, not only analytical visualizations may be too complex for target audiences but also the information that needs to be presented. Analysis results may consist of multiple components, which may involve multiple heterogeneous facets. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, within which two main challenges lie: information complexity and display complexity. We address this problem by proposing a general framework where data analysis and result presentation are linked by story synthesis, in which the analyst creates and organises story contents. Unlike previous research, where analytic findings are represented by stored display states, we treat findings as data constructs. We focus on selecting, assembling and organizing findings for further presentation rather than on tracking analysis history and enabling dual (i.e., explorative and communicative) use of data displays. In story synthesis, findings are selected, assembled, and arranged in meaningful layouts that take into account the structure of information and inherent properties of its components. We propose a workflow for applying the proposed conceptual framework in designing visual analytics systems and demonstrate the generality of the approach by applying it to two diverse domains, social media and movement analysis.
机译:Visual Analytics通常处理复杂的数据,并使用支持分析的复杂算法,视觉和交互式技术。分析的调查结果和结果通常需要传达给缺乏视觉分析专业知识的受众。这需要以更简单的方式呈现的分析结果,而不是视觉分析系统中通常使用的。然而,不仅对目标受众来说可能过于复杂的分析可视化,而且还需要呈现的信息。分析结果可以由多个组件组成,其可以涉及多个异构刻面。因此,从获得分析结果以传达它们的路径上存在差距,在其中两个主要挑战在于:信息复杂性和显示复杂性。我们通过提出数据分析和结果呈现的一般框架通过故事综合所关联的一般框架来解决这个问题,其中分析师创建和组织故事内容。与以前的研究不同,其中分析发现由存储的显示状态表示,我们将调查结果视为数据构造。我们专注于选择,组装和组织调查结果以获取进一步演示,而不是跟踪分析历史,并启用数据显示的双重(即,探索性和交流)。在故事综合中,选择,组装,并以有意义的布局选择,并考虑其组件的信息和固有属性的有意义的布局。我们提出了一种工作流程,用于在设计视觉分析系统时应用建议的概念框架,并通过将其应用于两个不同的域,社交媒体和运动分析来展示方法的一般性。

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