Network Science as the Dual of Statistics

If statistics is concerned with the collection, management, analysis, presentation, and interpretation of data, then so is network science.
The distinction lies neither in a universal network theory nor the complex systems of certain application domains but
(i) an incidence structure relating the units of observation and
(ii) a corresponding focus on dependencies among observations.
While not mainstream, this view clears away some of the smoke and mirrors obscuring the close relationship between statistics and network science.

Ulrik Brandes is a newly appointed Professor for Social Networks at ETH Zurich.
Previously, he was Professor for Algorithmics at the Universities of Passau (2002-2003) and Konstanz (2003-2017).
His interests circle around the analysis, visualization, and modeling of networks, and he often engages in interdisciplinary research to which he brings a computer science perspective.
He is a co-creator of the visone software and the GraphML file format, and an advocate of the positional approach to network analysis.