Data is being collected and generated at a rate never seen before in human history and this is no different in the energy sector. Despite the frightening volume of data, it can quite often be difficult to find what you need or to find the connectives in the data sources that form representative structures of the domain.
The apparently naive representation of a complex system as a collection of binary relations between indistinguishable units has since long proved to be a powerful tool for understanding dynamical systems. An important feature of interconnected systems is their ability to exchange information efficiently [1]. Assuming that the efficiency of a communication decreases as the distance between sender and receiver increases, one can easily quantify the communication efficiency of a networked system by the harmonic average of shortest-path distances.
Recently, complexity scientists have suggested understanding complex systems from an information processing perspective [1–4], and the natural way to do so is to think of information processing pathways as functions transforming inputs to outputs. By combining a small number of building blocks in different ways, very many functions can be obtained [5].