  Neural networks are a prevalent and effective machine learning component, and
their application is leading to significant scientific progress in many
domains. As the field of neural network systems is fast growing, it is
important to understand how advances are communicated. Diagrams are key to
this, appearing in almost all papers describing novel systems. This paper
reports on a study into the use of neural network system diagrams, through
interviews, card sorting, and qualitative feedback structured around
ecologically-derived examples. We find high diversity of usage, perception and
preference in both creation and interpretation of diagrams, examining this in
the context of existing design, information visualisation, and user experience
guidelines.
  This interview study is used to derive a framework for improving existing
diagrams. This framework is evaluated through a mixed-methods experimental
study, and a ``corpus-based'' approach examining properties of published
diagrams linking the framework to citations. The studies suggest that the
framework captures aspects relating to communicative efficacy of scholarly NN
diagrams, and provides simple steps for their implementation.
