  The arrangements of particles and forces in granular materials have a complex
organization on multiple spatial scales that ranges from local structures to
mesoscale and system-wide ones. This multiscale organization can affect how a
material responds or reconfigures when exposed to external perturbations or
loading. The theoretical study of particle-level, force-chain, domain, and bulk
properties requires the development and application of appropriate physical,
mathematical, statistical, and computational frameworks. Traditionally,
granular materials have been investigated using particulate or continuum
models, each of which tends to be implicitly agnostic to multiscale
organization. Recently, tools from network science have emerged as powerful
approaches for probing and characterizing heterogeneous architectures across
different scales in complex systems, and a diverse set of methods have yielded
fascinating insights into granular materials. In this paper, we review work on
network-based approaches to studying granular matter and explore the potential
of such frameworks to provide a useful description of these systems and to
enhance understanding of their underlying physics. We also outline a few open
questions and highlight particularly promising future directions in the
analysis and design of granular matter and other kinds of material networks.
