生物医学过程视觉传达的实践和偏好的探索

L. Garrison, M. Meuschke, J. Fairman, N. Smit, B. Preim, S. Bruckner
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引用次数: 13

摘要

生物医学过程的视觉交流从可视化和生物医学插图的不同技术中汲取。然而,将这些技术与它们的目标受众相匹配通常依赖于基于实践的启发式或窄范围的评估。我们提出了一项探索性研究的标准,观众使用时,评估生物医学过程可视化目标沟通。通过一系列专家访谈和焦点小组的设计,我们的研究侧重于五种知名生物医学过程的常见交流场景及其标准视觉表示。我们在一项调查中构建了这些场景,参与者的专业知识涵盖了给定主题的最小知识到专家知识。我们的结果显示,专家和非专业受众之间的抽象偏好经常重叠,具有相似的清晰度优先级和资产满足给定沟通目标的能力。我们还发现,一些说明性的惯例并不像我们想象的那样清晰,例如,发光具有广泛的模糊含义,而其他方法意外地被首选,例如,生物医学插图代替数据驱动的可视化。我们的研究结果表明,在有针对性的可视化设计中,可视化和生物医学插图技术的持续融合有许多机会。•以人为本的计算→可视化设计与评价方法;科学可视化;可视化理论、概念和范式;•计算机应用→生命和医学科学;
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An Exploration of Practice and Preferences for the Visual Communication of Biomedical Processes
The visual communication of biomedical processes draws from diverse techniques in both visualization and biomedical illustration. However, matching these techniques to their intended audience often relies on practice-based heuristics or narrow-scope evaluations. We present an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. Designed over a series of expert interviews and focus groups, our study focuses on common communication scenarios of five well-known biomedical processes and their standard visual representations. We framed these scenarios in a survey with participant expertise spanning from minimal to expert knowledge of a given topic. Our results show frequent overlap in abstraction preferences between expert and non-expert audiences, with similar prioritization of clarity and the ability of an asset to meet a given communication objective. We also found that some illustrative conventions are not as clear as we thought, e.g., glows have broadly ambiguous meaning, while other approaches were unexpectedly preferred, e.g., biomedical illustrations in place of data-driven visualizations. Our findings suggest numerous opportunities for the continued convergence of visualization and biomedical illustration techniques for targeted visualization design. CCS Concepts • Human-centered computing → Visualization design and evaluation methods; Scientific visualization; Visualization theory, concepts and paradigms; • Computer Applications → Life and Medical Sciences;
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