  Drawing principles, or aesthetics, are important in graph drawing. They are
used as criteria for algorithm design and for quality evaluation. Current
aesthetics are described as visual properties that a drawing is required to
have to be visually pleasing. However, most of these aesthetics are originally
proposed without consideration of graph structure information. Therefore their
ability in visually revealing graph structural features are not guaranteed and
indeed mixed results have been reported in the literature regarding their
impact on user graph comprehension. In this paper, we propose to derive
aesthetics based on graph internal structural features. Further, graphs are
often evaluated based on controlled experiments with simple perception tasks to
avoid possible confounding factors caused by complex tasks. This leaves their
value in supporting complex tasks unevaluated. To fill this gap, we also
discuss the possibility of applying evaluation methodologies used in the
Cognitive Load Theory research for graph evaluation.
