Building a Knowledge Base for the Model

In this chapter, after summarising the key conceptual challenges related to the measurement of asylum migration, we briefly outline the history of recent migration flows from Syria to Europe. This case study is intended to guide the development of a model of migration route formation, used throughout this book as an illustration of the proposed model-based research process. Subsequently, for the case study, we offer an overview of the available data types, making a distinction between the sources related to the migration processes, as well as to the context within which migration occurs. We then propose a framework for assessing different aspects of data, based on a review of similar approaches suggested in the literature, and this framework is subsequently applied to a selection of available data sources. The chapter concludes with specific recommendations for using the different forms of data in formal modelling, including in the uncertainty assessment.

Uncertainty and Complexity: Towards Model-Based Demography

This chapter focuses on the broad methodological and philosophical underpinnings of the Bayesian model-based approach to studying migration. Starting from reflections on the uncertainty and complexity in demography and, in particular, migration studies, the focus moves to the shifting role of formal modelling, from merely describing, to predicting and explaining population processes. Of particular importance are the gaps in understanding asylum migration flows, which are some of the least predictable while at the same time most consequential forms of human mobility. The well-recognised theoretical void of demography as a discipline does not help, especially given the lack of empirical micro-foundations in formal modelling. Here, we analyse possible solutions to theoretical shortcomings of demography and migration studies from the point of view of the philosophy of science, looking at the inductive, deductive and abductive approaches to scientific reasoning. In that spirit, the final section introduces and extends a research programme of model-based demography.

Applying Formal Modelling to the Specification and Testing of SDN Network Functionality

<p>Software Defined Networks offers a new paradigm to manage networks, one that favors centralised control over the distributed control used in legacy networks. This brings network operators potential efficiencies in capital investment, operating costs and wider choice in network appliance providers. We explore in this research whether these efficiencies apply to all network functionality by applying formal modelling to create a mathematically rigourous model of a service, a firewall, and using that model to derive tests that are ultimately applied to two SDN firewalls and a legacy stateful firewall. In the process we discover the only publicly available examples of SDN firewalls are not equivalent to legacy stateful firewalls and in fact create a security flaw that may be exploited by an attacker.</p>

Applying Formal Modelling to the Specification and Testing of SDN Network Functionality

<p>Software Defined Networks offers a new paradigm to manage networks, one that favors centralised control over the distributed control used in legacy networks. This brings network operators potential efficiencies in capital investment, operating costs and wider choice in network appliance providers. We explore in this research whether these efficiencies apply to all network functionality by applying formal modelling to create a mathematically rigourous model of a service, a firewall, and using that model to derive tests that are ultimately applied to two SDN firewalls and a legacy stateful firewall. In the process we discover the only publicly available examples of SDN firewalls are not equivalent to legacy stateful firewalls and in fact create a security flaw that may be exploited by an attacker.</p>

Social Media and Well-being: A Methodological Perspective

Due to the methodological challenges inherent in studying social media use (SMU), as well as the methodological choices that have shaped research into the effects of SMU on well- being, clear conclusions regarding relationships between SMU and well-being remain elusive. We provide a review of five methodological developments poised to provide increased understanding in this domain: (1) the use of longitudinal and experimental designs; (2) the adoption of behavioural (rather than self-report) measures of SMU; (3) a shift away from aggregate use; (4) the emergence of an idiographic media effects paradigm; and (5) the use of formal modelling and machine learning. We focus on how these advances stand to bring us closer to understanding relations between SMU and well-being.