VAID：视觉分析系统中的视图设计索引
VAID: Indexing View Designs in Visual Analytics System
AI总结：
针对视觉分析系统设计难以查询和复用的问题，本文提出VAID索引结构，通过研讨会收集需求并为高级可视化设计提供分析任务与视觉设计标签，经用户研究验证其有效性。
摘要：
视觉分析（VA）系统已广泛应用于各种应用领域。然而，VA系统在设计上十分复杂，这带来了一个严重的问题：尽管学术界不断设计和实现新的设计，但这些设计难以被后续设计者查询、理解和参考。为了在解决这一问题上迈出重要一步，我们以一种具有表达力且易于访问的方式对VA设计进行索引，将这些设计转化为结构化格式。我们首先与VA设计者开展了一次研讨会研究，以了解用户在VA系统中理解和检索专业设计的需求。此后，我们提出了一种索引结构VAID，用于描述高级和复合的可视化设计，并为其提供关于分析任务和视觉设计的全面标签。VAID的实用性通过用户研究得到了验证。我们的工作为提升专业可视化设计的可访问性和可复用性开辟了新的视角。
英文摘要：
Visual analytics (VA) systems have been widely used in various application domains. However, VA systems are complex in design, which imposes a serious problem: although the academic community constantly designs and implements new designs, the designs are difficult to query, understand, and refer to by subsequent designers. To mark a major step forward in tackling this problem, we index VA designs in an expressive and accessible way, transforming the designs into a structured format. We first conducted a workshop study with VA designers to learn user requirements for understanding and retrieving professional designs in VA systems. Thereafter, we came up with an index structure VAID to describe advanced and composited visualization designs with comprehensive labels about their analytical tasks and visual designs. The usefulness of VAID was validated through user studies. Our work opens new perspectives for enhancing the accessibility and reusability of professional visualization designs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
