  Business process models abstract complex business processes by representing
them as graphical models. Their layout, solely determined by the modeler,
affects their understandability. To support the construction of understandable
models it would be beneficial to systematically study this effect. However,
this requires a basic set of measurable key visual features, depicting the
layout properties that are meaningful to the human user. The aim of this
research is thus twofold. First, to empirically identify key visual features of
business process models which are perceived as meaningful to the user. Second,
to show how such features can be quantified into computational metrics, which
are applicable to business process models. We focus on one particular feature,
consistency of flow direction, and show the challenges that arise when
transforming it into a precise metric. We propose three different metrics
addressing these challenges, each following a different view of flow
consistency. We then report the results of an empirical evaluation, which
indicates which metric is more effective in predicting the human perception of
this feature. Moreover, two other automatic evaluations describing the
performance and the computational capabilities of our metrics are reported as
well.
