STcubeOperator：一种用于分析时空事件数据的框架
STcubeOperator: A Framework for Analyzing Spatiotemporal Event Data
- University of Konstanz（康斯坦茨大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
STcubeOperator是支持复杂探索性工作流的时空事件数据分析框架，将分析任务建模为时空立方体操作，通过开源3D原型实现，经俄乌战争案例及8名专家验证可揭示时空模式、解决特定任务。
AI中文摘要：
时空事件数据分析对于灾害响应、冲突分析或情报调查等领域的明智决策至关重要。然而，空间、时间及多个主题属性的复杂性与相互依赖性，给分析和可视化都带来了重大挑战。尽管时空立方体（STCs）是分析此类数据的强大集成可视化技术，但现有方法往往缺乏对复杂探索性工作流的支持，从而限制了获取有意义见解的能力。我们通过引入STcubeOperator解决了这一缺口，这是一种新颖的框架，它通过时空立方体操作对分析任务进行建模，将其置于可视化、交互和计算选择的背景下，并在交互式视觉分析环境中实现这些操作。通过将分析任务表示为过滤、切分和展平等多个基础操作的序列，我们的方法使分析人员能够从不同视角动态探索数据。我们还提供了一个开源原型，在3D交互式环境中实现这些操作，以促进时空事件数据的基于任务的探索性分析。我们基于俄乌战争中战略与军事行动的真实数据开展案例研究，证明了我们框架的适用性，展示了其揭示时空模式的能力。一项专家用户研究（n=8）展示了如何用我们的框架解决特定任务，突出了我们方法的多功能性，并提供了经验丰富的分析人员在实践中使用哪些操作的宝贵见解。
英文摘要：
The analysis of spatiotemporal event data is essential for informed decision-making in domains such as disaster response, conflict analysis, or intelligence investigations. However, the complexity and interdependence of spatial, temporal, and multiple thematic attributes pose significant challenges for both analysis and visualization. While space-time cubes (STCs) present a powerful integrated visualization technique to analyze this kind of data, existing approaches often lack support for complex exploratory workflows, thus limiting the ability to derive meaningful insights. We address this gap by introducing STcubeOperator, a novel framework that models analysis tasks through space-time cube operations, considering them in context of visualizations, interactions, and computational choices, and implement them in an interactive visual analytics environment. By expressing analysis tasks as a sequence of multiple elementary operations--such as filtering, chopping, and flattening--our approach enables analysts to dynamically explore data from different perspectives. We further provide an open-source prototype implementing the operations in a 3D interactive environment to facilitate task-based exploratory analysis of spatiotemporal event data. We demonstrate the applicability of our framework with a case study based on real-world data on strategic and military operations in the Russia-Ukrainian War, showing its capabilities to reveal spatiotemporal patterns. An expert user study (n=8) shows how specific tasks can be solved with our framework, highlights the versatility of our approach, and provides valuable insights on which operations experienced analysts utilize in practice.
