  The voluminous nature of geospatial temporal data from physical monitors and
simulation models poses challenges to efficient data access, often resulting in
cumbersome temporal selection experiences in web-based data portals. Thus,
selecting a subset of time steps for prioritized visualization and pre-loading
is highly desirable. Addressing this issue, this paper establishes a
multifaceted definition of salient time steps via extensive need-finding
studies with domain experts to understand their workflows. Building on this, we
propose a novel approach that leverages autoencoders and dynamic programming to
facilitate user-driven temporal selections. Structural features, statistical
variations, and distance penalties are incorporated to make more flexible
selections. User-specified priorities, spatial regions, and aggregations are
used to combine different perspectives. We design and implement a web-based
interface to enable efficient and context-aware selection of time steps and
evaluate its efficacy and usability through case studies, quantitative
evaluations, and expert interviews.
