Emerging Architectures for Global System Science

Michela Milano, Pascal Van Hentenryck

Abstract: Our society is organized around a number of (interdependent) global systems. Logistic and supply chains, health services, energy networks, financial markets, computer networks, and cities are just a few examples of such global, complex systems. These global systems are socio-technical and involve interactions between complex infrastructures, man-made processes, natural phenomena, multiple stakeholders, and human behavior. For the first time in the history of manking, we have access to data sets of unprecedented scale and accuracy about these infrastructures, processes, natural phenomena, and human behaviors. In addition, progress in high-performancing computing, data mining, machine learning, and decision support opens the possibility of looking at these problems more holistically, capturing many of these aspects simultaneously. Global System Science (GSS) (Jaeger et al. 2013) is the evidence-based study of such complex systems. Its goal is to identify fundamental concepts that help structure problems, identify phenomena, and organize actions. GSS looks at systems holistically, studying their main components and how they interact. In particular, GSS jointly studies