Civil engineers use numerical simulations of a building’s responses to seismic forces to understand the nature of building failures, the limitations of building codes, and how to determine the latter to prevent the former. Such simulations generate large ensembles of multivariate, multiattribute time series. Comprehensive understanding of this data requires techniques that support the multivariate nature of the time series and can compare behaviors that are both periodic and non-periodic across multiple time scales and multiple time series themselves. In this paper, we present a novel technique to extract such patterns from time series generated from simulations of seismic responses. The core of our approach is the use of topic modeling, where topics correspond to interpretable and discriminative features of the earthquakes. We transform the raw time series data into a time series of topics, and use this visual summary to compare temporal patterns in earthquakes, query earthquakes via the topics across arbitrary time scales, and enable details on demand by linking the topic visualization with the original earthquake data. We show, through a surrogate task and an expert study, that this technique allows analysts to more easily identify recurring patterns in such time series. By integrating this technique in a prototype system, we show how it enables novel forms of visual interaction.

土木工程师使用建筑物对地震力响应的数值模拟来了解建筑物故障的性质、建筑规范的局限性以及如何确定后者以防止前者。这种模拟会生成大量的多元、多属性时间序列。对这些数据的全面理解需要支持时间序列的多元性质的技术，并且可以比较跨多个时间尺度和多个时间序列本身的周期性和非周期性行为。在本文中，我们提出了一种从地震响应模拟生成的时间序列中提取此类模式的新技术。我们方法的核心是使用主题建模，其中主题对应于地震的可解释性和判别性特征。我们将原始时间序列数据转换为主题的时间序列，并使用此可视化摘要来比较地震中的时间模式，通过任意时间尺度的主题查询地震，并通过将主题可视化与原始地震联系起来实现按需详细信息数据。我们通过代理任务和专家研究表明，该技术使分析师能够更轻松地识别此类时间序列中的重复出现的模式。通过将这种技术集成到原型系统中，我们展示了它如何实现新形式的视觉交互。通过替代任务和专家研究，该技术使分析师能够更轻松地识别此类时间序列中的重复出现的模式。通过将这种技术集成到原型系统中，我们展示了它如何实现新形式的视觉交互。通过替代任务和专家研究，该技术使分析师能够更轻松地识别此类时间序列中的重复出现的模式。通过将这种技术集成到原型系统中，我们展示了它如何实现新形式的视觉交互。