  Building a visual overview of temporal event sequences with an optimal
level-of-detail (i.e. simplified but informative) is an ongoing challenge -
expecting the user to zoom into every important aspect of the overview can lead
to missing insights. We propose a technique to build a multilevel overview of
event sequences, whose granularity can be transformed across sequence clusters
(vertical level-of-detail) or longitudinally (horizontal level-of-detail),
using hierarchical aggregation and a novel cluster data representation
Align-Score-Simplify. By default, the overview shows an optimal number of
sequence clusters obtained through the average silhouette width metric - then
users are able to explore alternative optimal sequence clusterings. The
vertical level-of-detail of the overview changes along with the number of
clusters, whilst the horizontal level-of-detail refers to the level of
summarization applied to each cluster representation. The proposed technique
has been implemented into a visualization system called Sequence Cluster
Explorer (Sequen-C) that allows multilevel and detail-on-demand exploration
through three coordinated views, and the inspection of data attributes at
cluster, unique sequence, and individual sequence level. We present two case
studies using real-world datasets in the healthcare domain: CUREd and
MIMIC-III; which demonstrate how the technique can aid users to obtain a
summary of common and deviating pathways, and explore data attributes for
selected patterns.
