  We consider the problem of automatically generating networks from data of
collaborating researchers. The objective is to apply network analysis on the
resulting network layers to reveal supplemental patterns and insights of the
research collaborations. In this paper, we describe our data-to-networks
method, which automatically generates a set of logical network layers from the
relational input data using a linkage threshold. We, then, use a series of
network metrics to analyze the impact of the linkage threshold on the
individual network layers. Moreover, results from the network analysis also
provide beneficial information to improve the network visualization. We
demonstrate the feasibility and impact of our approach using real-world
collaboration data. We discuss how the produced network layers can reveal
insights and patterns to direct the data analytics more intelligently.
