设计模糊性：雪崩预测中的可视化分析
Designing for Ambiguity: Visual Analytics in Avalanche Forecasting
摘要：
模糊性是一种信息状态，其中多种解释是合理的，是视觉分析（VA）系统中的常见挑战。我们讨论的经验教训，从案例研究设计VA加拿大雪崩预报工具。雪崩预测是一个复杂和协作的基于风险的决策和分析领域，需要对人类报告和不确定数据进行基于经验和知识的解释。在报告的做法，组织背景和个人报告的特殊性的差异，导致各种潜在的解释，必须作为预测的意义制造过程的一部分进行谈判。我们描述了我们的初步研究，使用字形，以支持下歧义的意义构建。模糊性并不是公共雪崩预测所独有的。在许多其他领域，数据的测量和报告方式各不相同，数据中没有明确说明，需要分析师协商多种潜在含义。我们认为，模糊性是不够的可视化研究，将受益于更明确的VA支持。
英文摘要：
Ambiguity, an information state where multiple interpretations are plausible, is a common challenge in visual analytics (VA) systems. We discuss lessons learned from a case study designing VA tools for Canadian avalanche forecasters. Avalanche forecasting is a complex and collaborative risk-based decision-making and analysis domain, demanding experience and knowledge-based interpretation of human reported and uncertain data. Differences in reporting practices, organizational contexts, and the particularities of individual reports result in a variety of potential interpretations that have to be negotiated as part of the forecaster's sensemaking processes. We describe our preliminary research using glyphs to support sensemaking under ambiguity. Ambiguity is not unique to public avalanche forecasting. There are many other domains where the way data are measured and reported vary in ways not accounted explicitly in the data and require analysts to negotiate multiple potential meanings. We argue that ambiguity is under-served by visualization research and would benefit from more explicit VA support.
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