Collaborative Research: HCC: Medium: Design guidelines for dynamic visualizations

合作研究：HCC：Medium：动态可视化的设计指南

• 批准号: 2106537
• 负责人: Camillia Matuk
• 金额: $ 26.74万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106537&HistoricalAwards=false
• 关键词: Collaborative; Research; HCC; Medium; Design

People rely on visualizations to understand and communicate patterns in data, processes in diagrams, or routes within maps, in domains including journalism, education, business, and security. These visualizations are increasingly dynamic, using moving objects or animated patterns to show trends and interactions in the data. In many cases these dynamic displays can help people understand these relationships, but in some cases these dynamic elements can overwhelm people or lead them to incorrect conclusions. Across all of these domains, even expert designers have trouble predicting which displays will work. Through psychology-based experiments and interviews with expert visualization designers, this project will explore the power and limits of dynamic visualization. It will result in a set of guidelines that will enable designers from diverse backgrounds and levels of experience to create more effective displays that lead to better understanding, education, and decisions.To understand how people process and interpret these dynamic displays, the investigators will catalog an abstracted set of intended uses for animation across data displays (e.g., track a value across an axis change in a graph) by interviewing designers of data displays and validating how well their designs meet their stated goals. In collaboration with these designers, the research team will conduct a series of empirical tests of the power and limits of the human visual system to process the intended patterns, with an initial set of experiments that will test the ability of dynamic visualizations to support viewers in seeing statistics, making comparisons, tracking objects, and drawing attention. The investigators will use these findings to generate a practitioner’s guide for designing effective displays for common goals. In ongoing consultations with our team of designers and advisors, the investigators will incorporate their feedback about (a) whether our abstracted displays, tasks, and measures remain relevant to their in-context case studies, and (b) whether our practitioner’s guide is consistent with their expectations and captures rules that should generalize across most case-study contexts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人们依靠可视化来理解和传达数据中的模式、图表中的流程或地图中的路线，包括新闻、教育、商业和安全领域。这些可视化越来越动态，使用移动对象或动画模式来显示数据中的趋势和交互。在许多情况下，这些动态显示可以帮助人们理解这些关系，但在某些情况下，这些动态元素可能会压倒人们或导致他们得出错误的结论。在所有这些领域，即使是专业的设计师也很难预测哪些显示器会工作。通过心理学为基础的实验和专家可视化设计师的采访，这个项目将探索动态可视化的力量和局限性。它将产生一组指导方针，使来自不同背景和经验水平的设计师能够创建更有效的显示，从而更好地理解，教育和决策。为了了解人们如何处理和解释这些动态显示，研究人员将对数据显示中的动画预期用途进行抽象（例如，通过采访数据显示器的设计者并验证他们的设计如何满足他们的既定目标来跟踪图表中跨轴变化的值）。研究团队将与这些设计师合作，对人类视觉系统处理预期模式的能力和局限性进行一系列实证测试，最初的一组实验将测试动态可视化的能力，以支持观众查看统计数据，进行比较，跟踪对象和吸引注意力。研究人员将使用这些发现来生成一个实践者指南，用于为共同目标设计有效的显示器。在与我们的设计师和顾问团队的持续磋商中，调查人员将纳入他们的反馈：（a）我们的抽象展示、任务和措施是否与他们的情境案例研究相关，以及（B）我们的从业者指南是否与他们的期望一致，并捕捉了应该在大多数情况下通用的规则-该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。