  Composite temporal event sequence visualizations have included sentinel event
alignment techniques to cope with data volume and variety. Prior work has
demonstrated the utility of using single-event alignment for understanding the
precursor, co-occurring, and aftereffect events surrounding a sentinel event.
However, the usefulness of single-event alignment has not been sufficiently
evaluated in composite visualizations. Furthermore, recently proposed
dual-event alignment techniques have not been empirically evaluated. In this
work, we designed tasks around temporal event sequence and timing analysis and
conducted a controlled experiment on Amazon Mechanical Turk to examine four
sentinel event alignment approaches: no sentinel event alignment (NoAlign),
single-event alignment (SingleAlign), dual-event alignment with left
justification (DualLeft), and dual-event alignment with stretch justification
(DualStretch). Differences between approaches were most pronounced with more
rows of data. For understanding intermediate events between two sentinel
events, dual-event alignment was the clear winner for correctness---71% vs. 18%
for NoAlign and SingleAlign. For understanding the duration between two
sentinel events, NoAlign was the clear winner: correctness---88% vs. 36% for
DualStretch---completion time---55 seconds vs. 101 seconds for DualLeft---and
error---1.5% vs. 8.4% for DualStretch. For understanding precursor and
aftereffect events, there was no significant difference among approaches. A
free copy of this paper, the evaluation stimuli and data, and source code are
available at https://osf.io/78fs5
