Showing papers by "Tom McDermott published in 2016"

Integrated Community Resilience, A Model Based Systems Engineering Approach

Abstract: This paper presents a model-based systems engineering framework used to integrate physical, socio-ecological, and psychological factors of community resilience in urban areas. The research results represent the first year of a multi-year project. However, both the modeling methodology and our approach to model social factors of community resilience are novel. We first applied a sociotechnical-modeling framework to capture social factors of community sustainability and resilience in the context of urban infrastructure renewal. Two system constructs, standard of living and subjective well-being, were linked to environmental, infrastructure, economic, and institutional factors to represent the human capital aspects of community resilience at multiple scales. The framework produced a system metamodel that was used to identify causal relationships between individual micro-scale indicators of both infrastructure and social program development and the aggregate effects of human capital development. The system metamodel was then used to define an initial data model that will be used to structure an executable metamodel in later phases of research. The executable metamodel will support cross-disciplinary modeling of the socio-ecological (objective) and psychological (subjective) factors of community resilience. The long-term goal is to define a full set of evaluation factors and computer based decision analysis tools that support macro-scale decision criteria for social, behavioral, and economic decision-making in complex urban infrastructures.

Analysis of political and trade decisions in international gas markets: A model-based systems engineering framework

Abstract: By taking a model-based systems engineering (MBSE) approach, a framework can be developed for long-term exploration of a complex adaptive system in multiple contexts. The framework uses MBSE tools to define the complex system architecture and modern internet state transfer and structured data format standards to integrate natural language descriptions, datasets, and models. These can constitute a knowledge architecture that can be used as a long-term research tool. The long-term goal is a framework that captures conceptual models of the complex system, data sets and relationships, dynamic models and simulations, and decision analytics within a common environment. This paper presents a scenario in which we evaluate links between transformations of complex natural gas systems and analyze political intervention into the Russian-European natural gas markets. In this example, we specifically examine geographical, physical (cross-border infrastructure), and commercial value streams through the prism of network analyses. This is one context of a more general model of international gas relationships and flows at multiple levels. The resulting framework provides insight into dynamic behaviors at multiple levels of the system, such as the emergence of infrastructure network and intricate relationships of strong corporate ties and knowledge networks, along with possible strategies for political and economic intervention. The primary goal of an MBSE approach is to capture interrelationships in the complex system at varying levels of abstraction, which enables a common reference for diverse models and datasets.

System-Level Experimentation: Social Computing and Analytics for Theory Building and Evaluation

Abstract: This paper introduces the concept of shared data experimentation platforms as a means to transform access to and sharing of social science research data. Such platforms are becoming a central component of biomedical research, and are expanding into other fields. We discuss a framework for the development of data analytic experimentation platforms in the social sciences. Social situations are inherently complex adaptive systems that a difficult to generalize without explicitly documenting both the phenomena and related context. We introduce the concept of a “campaign of experiments” that focuses on purposeful exploration of social phenomena in order to evaluate generalizable, reproducible, and repeatable theory. We also propose sociotechnical systems analysis methods to define the appropriate conceptual models of social situations, which can then be used to structure the experimentation data in a form that promotes reuse and replication. We discuss challenges and opportunities associated with an experimentation platform concept, methodologies that can support development of such