Disentangling spatial and non-spatial effects in real networks

Over the last fifteen years, Network Science has facilitated the identification of universal and unexpected patterns across systems belonging to deeply different research fields, such as biology, economics and physics. A fruitful cross-fertilization among these disciplines, leading to the introduction of novel multidisciplinary tools, has been made possible by the fact that many real complex systems can be formally abstracted as networks or graphs, irrespective of their specific nature. In so doing, several details of the original system are discarded and the emphasis is put on the study of the topological properties of the underlying 'network backbone'. While this process facilitates the detection of key structural properties in real complex systems, it can also obscure other important levels of organization that involve non-topological factors. A key example is the spatial organization of networks.