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Research Network for Computational Modeling in the Social and Ecological Sciences (CoMSES Net)

Computer network

Important challenges of scientific infrastructure have slowed the spread of computational modeling into research domains where it could be most profitably used. Building on a successful, National Science Foundation-funded pilot program, we propose to establish a scientific research collaboration network to confront and begin to mitigate these issues.

The often non-linear, non-intuitive and even surprising relationships and consequences that emerge from complex interactions between human social practice and the biophysical environment make it imperative that scientific models – including their underlying assumptions, algorithmic processes, logical consistency and connections with empirical data – be transparent and quantitative. For this reason, computational modeling in general and agent-based modeling (ABM) in particular are important tools for research in socioecological sciences (SES). National Science Foundation programs like CNH explicitly encourage quantitative modeling and computational thinking as important approaches for research on the recursive interrelationships between society and environmental change.

Important challenges of scientific infrastructure have slowed the spread of computational modeling into research domains where it could be most profitably used – including constraints on disseminating modeling-related research through existing scientific channels, lack of frameworks that permit researchers engaged in modeling to build on each other's work, the lack of a common descriptive language for models and difficulties in evaluating the quality and applicability of modeling-related research. Building on a successful, National Science Foundation-funded pilot program, we propose to establish a scientific research collaboration network to confront and begin to mitigate these issues.

This network will serve as a coordinated community of practice and a conduit to expedite knowledge exchange for computational modeling in SES; it also will seek to grow scientific infrastructure so as to better serve research that uses computational modeling by:

  • establishing an interactive, online archive for computational models (including for review of models associated with publications) and associated standard data testbeds for model evaluation;
  • promoting a common standard for model description; 
  • developing educational curricula for embedding modeling and computational thinking in the normal practice of social and natural science; and 
  • establishing a new e-journal dedicated to publishing research in the social and natural sciences that involves computational modeling, as well as studies of modeling methods and empirical evaluation. 

This network will include scientists and institutions with an established record of computational modeling in research on coupled natural and human, and actively seek young researchers who wish to gain new expertise in this field.

 

Funding Source:
National Science Foundation – Directorate for Geosciences 

Team Members:

Michael Barton, Arizona State University School of Human Evolution and Social Change
Marco Janssen, Arizona State University School of Sustainability
Lilian Alessa, University of Alaska, Anchorage, Environment and Natural Resources Institute
Allen Lee, Arizona State University