In this note, we consider certain structural aspects of estimation and control over relative sensing networks (RSNs). In this venue, using tools from basic algebraic graph theory-namely, the incidence matrix and cut and cycle spaces of a connect graph-we examine transformations among relative sensing topologies for a networked system. These transformations are parameterized for noise-free as well as noisy networks and their utility in the context of network-centric robust control and control reconfigurations is explored.