Abstract
The effectiveness and resilience of air transportation, as a complex socio-technical system, can be adequately analyzed using tools of Network Science, a recently developed academic field that studies components and interactions among them. Network Science, together with another recently emerged field, Data Science, leverages the scalable and realistic analysis of air transportation. The goal of this chapter is to design, implement, and disseminate an open-source framework for the analysis of air transportation networks, their performance, and their resilience. First, the chapter derives a framework for modeling air transportation networks based on freely available datasets. Second, we provide an overview on how to estimate the resilience of such a complex system, with methods developed in the Network Science community. Third, we perform experiments on global air transportation, reporting on critical roles of its elements. Our framework, implemented in Python, makes it easy for other transportation researchers to get started in the area of air transportation network resilience, by having a gold standard as reference. Moreover, since our framework and its underlying data are freely available, we hope that it can push the state-of-the-art in air transportation network resilience analysis.
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