CNH: RCN: A Research Network for Computational Modeling in the Socioecological Sciences

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This project establishes a scientific research collaboration network to support and expand the development and use of computational modeling in the social and life sciences. The COMSES (COmputational Modeling for SocioEcological Science) network aims to be broadly inclusive of social and natural scientists using (and desiring to use) advanced modeling to study coupled natural and human, or 'socioecological systems' (SES). 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. Yet ABM remains little used or understood in the broader scientific communities involved in the science of coupled natural and human systems. Rather, it is widely perceived as inaccessible to social and natural scientists in spite of the fact that ABM has existed as a potential research tool for nearly two decades. The primary goal of the COMSES network is to serve as a coordinated community of practice and a conduit to expedite knowledge exchange for computational modeling in SES. The network will build on the NSF-funded OpenABM Consortium http://www.openabm.org. It 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 and providing standard tools and data for model evaluation;- promoting a common standard for describing models;- developing educational curricula for embedding modeling and computational thinking in the interdisciplinary study of social and natural sciences.- establishing a new e-journal dedicated to publishing research in the social and natural sciences that involves computational modeling, and studies of modeling methods and empirical evaluation.Through the development of exemplar curricula and training opportunities, the project will endeavor to stimulate new interdisciplinary learning opportunities for students at multiple levels who represent the next generation of scientists. With the ever-increasing importance of information technology and related cybertools in today's world, training in advanced modeling techniques and their application in the social sciences will broadly benefit students' careers. Many of the environmental challenges that we face in the 21st century may also be considered social problems because they affect our quality of life and can only be addressed by human actions. The COMSES network has the potential to transform the social and natural sciences in profound ways by developing computational tools and expertise that will help us to gain a much deeper understanding of the relationships between humans and their environment, and allow us to better predict the likely effects of future policies and decisions.