  Real-world multilayer networks can be very large and there can be multiple
choices regarding what should be modeled as a layer. Therefore, there is a need
for their effective storage and manipulation. Currently, multilayer network
analysis software use different data structures and manipulation operators. We
aim to categorize operators in order to assess which structures work best for
certain operator classes and data features. In this work, we propose a
preliminary taxonomy of layer and data manipulation operators. We also design
and execute a benchmark of select software and operators to identify potential
for optimization.
