HR00112220038: GATASD: Generalized Algebraic Techniques Advancing Scientific Discovery

James Fairbanks, PhD

Project Summary

Scientists and policymakers are frequently faced with novel situations that can only be addressed by new models and simulations. Common tasks requiring custom models include making accurate forecasts to predict medical care needs, estimating uncertainty for logistics planning, and analyzing possible interventions to develop policy prescriptions. Moreover, these models must be adaptable and extensible in response to changing scientific knowledge and real-world conditions. Scientists instantiate their knowledge of scientific phenomena in many forms including descriptions of qualitative understanding, tabulations of facts and figures, quantitative mathematical models, and computational simulations. GATASD aims to address these diverse instantiations of scientific knowledge across many domains of expertise and frameworks of models. We will provide a unified treatment of these heterogeneous knowledge representations based on algebraic abstractions that can be implemented in generic software yet adapted to the specialized structures found in different scientific disciplines including Epidemiology and Space Weather (SW).


Fonseca LL, Laubenbacher R “Generating ODE Approximations of Agent Based Models for Control Purposes.” Invited oral presentation in the minisymposium “Boolean networks and related modeling frameworks – Part I: Model Design and Analysis” organized by Claus Kadelka (Iowa State University), 12th European Conference on Mathematical and Theoretical Biology (ESMTB & SMB), Heidelberg, Germany, September 19-23, 2022.