Rethinking the ABCs: Agent-Based Models and Complexity Science in the age of Big Data, CyberGIS, and Sensor Networks

Tuesday Sep 27   08:30 AM to 05:30 PM (9 hours)

A broad scope of concepts and methodologies from complexity science – including Agent-Based Models, Cellular Automata, network theory, and scaling relations – has contributed to a better understanding of spatial/temporal dynamics of complex geographic patterns and process.

Recent advances in computational technologies such as Big Data, Cloud Computing and CyberGIS platforms, and Sensor Networks (i.e. the Internet of Things) provides both new opportunities and raises new challenges for ABM and complexity theory research within GIScience.  Challenges include parameterization of complex models with volumes of georeferenced data, scaling model applications to realistic, exploring challenges in their deployment across cloud computing platforms, and validating their output using real-time data; as well as measure the impact of simulation on knowledge, information and decision-making.

The scope of this workshop is to explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.

McGill University
Université de Montréal
Pennsylvania State University
Ph.D. Candidate in GIScience
University of Michigan

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