In line with one of the major themes of this conference, we explore the opportunities and challenges that geo-computational tools offer to support public engagement, deliberation and decision-making to address complex problems that link human, socioeconomic and biophysical systems at a variety of different spatial and temporal scales (e.g., climate change, resource depletion, and poverty). Modelers and data scientists have shown increasing interest in the intersection between science and policy, acknowledging that, for all the computational advances achieved to support policy and decision-making, these approaches remain frustratingly foreign to the public they are meant to serve. On one hand, there is a persistent gap in the public’s understanding of and reasoning about complex systems, resulting in unintended and undesirable consequences. On the other hand, there is significant public skepticism about the knowledge generated by the modeling community and its ability to inform policy and decision-making.
We invite theoretical, methodological, and empirical papers that explore advances in geo-computational approaches, including part or all the process to address complex problems: from data collection and analysis, to the development and use of models, to supporting action with data analysis and modeling. We are interested in any work that contributes towards the overall goal of supporting public engagement and action around complex problems, including—but not limited to—the following topics:
Please e-mail the abstract and key words with your expression of intent to Moira Zellner ([email protected]) by October 25, 2017. Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at:
http://annualmeeting.aag.org/AAGAnnualMeeting/Call_for_Submissions/Submit_an_Abstract/AAGAnnualMeeting/How_to_Submit_an_Abstract.aspx?hkey=2ddb8b77-96dd-483f-950a-086823af2336
An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.