Living Dashboards：自动自我更新的可视化仪表盘

中文摘要 AI 辅助

可视化仪表盘是广泛使用的交互式工具，但其展示的动态数据与静态结构之间存在脱节。最终用户无法修改仪表盘以回答新问题。我们引入了“Living Dashboards”（活仪表盘），其视图会根据使用方式而诞生、枯萎、复苏和消亡。活仪表盘无需手动重新配置，而是通过观察交互和自然语言查询，自主地枯萎被忽视的视图，并复苏被再次使用的视图。诸如添加或移除视图等更重大的决策则交由用户处理。我们将该概念形式化为一个四维设计空间，并在基于Web的原型系统Living Dashboard中实现。我们通过一项探索性受试者间研究（N=12），在分析任务上将其与AI支持的基线系统进行比较。使用Living Dashboard的参与者正确回答的任务更多，报告的工作负载更低，并且在可用性上对该系统的评分更高，尽管两种条件在自适应行为之外的方面也存在差异。

英文摘要

Visualization dashboards are widely used interactive tools, but a disconnect exists between the dynamic data they display and their static structure. End-users cannot modify the dashboard to answer new questions. We introduce Living Dashboards, whose views are born, wither, revive, and die in response to how they are used. Rather than requiring manual reconfiguration, a living dashboard observes interaction and natural-language queries to autonomously wither neglected views and revive those used again. More consequential decisions, such as adding or retiring views, are deferred to the user. We formalize the concept as a four-dimensional design space and implement it in Living Dashboard, a web-based prototype. We evaluate it in an exploratory between-subjects study (N = 12) against an AI-supported baseline on analytical tasks. Living Dashboard participants answered more tasks correctly, reported lower workload, and rated the system higher on usability, though the two conditions differed in more than adaptive behavior alone.

发表机构

• Seoul National University（首尔大学）
• Sogang University（西江大学）
• TU Wien（维也纳工业大学）
• VRVis GmbH（VRVis有限责任公司）
• Aarhus University（奥胡斯大学）

机构由 AI 辅助整理，请以论文原文为准。