  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.
