CDI-Type II Collaborative Research: Understanding social networks, complex systems

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This project creates a multidisciplinary research virtual organization (SOCNET) of historians, geographers, computer scientists, and mathematicians to share historical social science data and develop geographically integrated frameworks to address complex, dynamic, nonlinear systems and social networks.Through multidisciplinary collaboration, SOCNET will fuse qualitative and quantitative data to connect humans, events, and environments, and through such connections form historical narratives within and across geographic spaces. The project's ultimate goal is to better infuse computational thinking into the historical social sciences through computational innovation and narrative knowledge creation to revolutionize research outcomes in these disciplines with a shift to Geographically-Integrated History. SOCNET's developments in Dynamics GIS (geographic information systems) and related information technologies will provide the backbone for understanding complex historical social systems with three components that define the geographically-integrated history paradigm: (1) the history of any place is shaped in significant ways by the way the place is connected to other places and by the changes in these connections over time; (2) historical periods are complex, dynamic, nonlinear systems that are spatially large, and in more recent centuries, global in extension, and these systems sometimes become unstable, leading to a phase transition, bifurcation, and the organization of new systems; and (3) within such systems, people and places are connected by social networks in a self-organizing fashion. Focusing on the first global age (1400-1800), SOCNET will transform historical research with computational thinking on (1) new means for the representation of data for organizing, storing, manipulating, and recovering them for exploration using computational tools; (2) new spatial-temporal GIS for the visualization and analysis of real world dynamics; (3) new tools for data harmonization and text mining; (4) new approaches to the use of information that is vague, uncertain, and incomplete and of qualitative data within a computational context; (5) new forms of modeling to represent the inferences of domain experts; and (6) new metaphors beyond the map and animation-based visualization for temporal GIS. Collaborative protocols, tools, models, data structures, and algorithms developed in the project will be shaped and presented in web-based educational materials to provide interested researchers and their students with easy access. Beyond the historical social sciences and geographic information science, SOCNET will promote innovations in computer science, mathematical modeling and simulation, environmental sciences, medical research, and transportation studies. Collaborating computer scientists and mathematicians will develop innovative computational concepts and tools to better capture the dynamism of overlapping, multi-dimensional social networks within a complex, nonlinear system. In solving the difficulties associated with using historical information within a computational environment, SOCNET will further promote the idea of 'spatial turn' within history and the historical social sciences. Because of the higher percentage of women and minorities among majors in the historical social sciences, the project will attract such students into a technologically rich educational and employment environment. The project will support the development of an existing Master's in geographically-integrated history, a forthcoming interdisciplinary Ph.D. in Social and Environmental Dynamics, a future M.S. in Computer Science and Computational Sciences, and a new interdisciplinary degree program in Geoinformatics, providing students educational emphases on geographic information science and technology to seek better understanding of dynamic human and environmental systems.