  Visual information displays are typically composed of multiple visualizations
that are used to facilitate an understanding of the underlying data. A common
example are dashboards, which are frequently used in domains such as finance,
process monitoring and business intelligence. However, users may not be aware
of existing guidelines and lack expert design knowledge when composing such
multi-view visualizations. In this paper, we present semantic snapping, an
approach to help non-expert users design effective multi-view visualizations
from sets of pre-existing views. When a particular view is placed on a canvas,
it is "aligned" with the remaining views -- not with respect to its geometric
layout, but based on aspects of the visual encoding itself, such as how data
dimensions are mapped to channels. Our method uses an on-the-fly procedure to
detect and suggest resolutions for conflicting, misleading, or ambiguous
designs, as well as to provide suggestions for alternative presentations. With
this approach, users can be guided to avoid common pitfalls encountered when
composing visualizations. Our provided examples and case studies demonstrate
the usefulness and validity of our approach.
