  Dynamic-mode decomposition (DMD) is a versatile framework for model-free
analysis of time series that are generated by dynamical systems. We develop a
DMD-based algorithm to investigate the formation of "functional communities" in
networks of coupled, heterogeneous Kuramoto oscillators. In these functional
communities, the oscillators in the network have similar dynamics. We consider
two common random-graph models (Watts--Strogatz networks and Barab\'asi--Albert
networks) with different amounts of heterogeneities among the oscillators. In
our computations, we find that membership in a community reflects the extent to
which there is establishment and sustainment of locking between oscillators. We
construct forest graphs that illustrate the complex ways in which the
heterogeneous oscillators associate and disassociate with each other.
