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A geospatial data science investigation to describe, analyze, model and simulate global human development patterns and processes. |
Global, near present-time, high-resolution data is openly accessible to construct scientific descriptions of human development. In this course you will use data describing populations, governments, and both the natural and built environments in order to construct a close-to-reality description of your selected region or country. You will then intersect a selected dimension of human development as an initial boundary for investigating a contextually relevant research question. While development is often thought of as a “missing ingredient” that is needed to improve the well being of people or the output of firms, in this course human development is defined as the ability to enlarge people’s choices, capabilities and freedoms and is understood as an emergent property from our complex and adapting economic and social system. Data science methods are used to construct close-to-reality descriptions of human development processes in order to identify interactions, describe co-evolving agents, recognize the conditions prevalent for emergence, understand the significance of scale and ultimately begin to establish a framework for analyzing human development’s multitude of seemingly intractable, wicked problems.