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have different expectations about content and visual-
izations, they defined different user groups, each with
their own set of layouts.
Regarding the more complex use cases, we plan
to conduct a user evaluation in future. While small
multiples in general have proven to be effective in
many situations (Archambault et al., 2011), it is un-
known how well they cooperate with multiple views.
Through small multiples of multiple views, users can
examine more complex relationships. For instance,
when a multiple view layout of one node reveals a
relationship between two data dimensions, how can
users perceive trends between multiple nodes within
that relationship? How does the influence of a de-
fects size on its position change as the temperature
of the melting charge increases? The influence may
be higher at higher melting temperatures. We plan
to publish a systematic expert and user evaluation to
study the strengths and weaknesses of our approach
in detail.
8 CONCLUSIONS AND FUTURE
WORK
In this paper, we have presented IPFViewer, a sys-
tem for visual analysis of hierarchical ensemble data.
Through the combination of small multiples with
multiple views and combining multiple hierarchical
levels, users can create multiple aggregated and non-
aggregated visualizations. Since layouts are user gen-
erated, the system is very flexible and can support
various analysis tasks. While we presented some ex-
amples to show the usefulness of our approach, the
full potential remains to be proven in a comprehen-
sive user evaluation. Newly developed high-density
displays and display grids are an especially useful ad-
dition to our system. The number of ensemble mem-
bers and the views themselves can be scaled to fit the
visible screen area. In future work, we will extend the
capabilities in areas of uncertainty visualization and
data aggregation.
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