Defining a Graph
Supply chains are networks. The art world is a network. Ecosystems are networks. Networks are spatial, temporal and dynamic. MACRO-EYES advisory board member Stefanie Jegelka, PhD is an expert on graph neural networks. A graph is a structure that consists of entities [think: people] and the connections between entities [think: friendships]. A graph can consist of drugs, or even molecules; connections can be observed through the interactions that occur (and the adverse effects that may result) when a patient is prescribed more than one medication. It is difficult to describe mathematically the multiple connections between entities and how the links change in time and across space.
What if there’s no map? In many of the environments in which MACRO-EYES works, we know we’re dealing with a network – which if optimized, could save lives and resources – but no one knows exactly how it works end-to-end. Change is the constant in many of the systems that matter to MACRO-EYES. Each participant has a partial view and available data reflects this. It may be a network of networks. How then do the different layers of the network interact? There may be models of how the network should work, but ignoring the friction and ambiguity of how events unfold on the ground can be dangerous.