Four Guiding Principles for Modeling Causal Domain Knowledge: A Case Study on Brainstorming Approaches for Urban Blight Analysis
This work addresses urban blight analysis for planning and policy-making researchers, but it is incremental as it builds on existing causal modeling approaches.
The paper tackled the problem of integrating domain knowledge in urban blight analysis by introducing four rules for modeling causal domain knowledge, revealing significant deviations from causal modeling guidelines in existing cognitive maps.
Urban blight is a problem of high interest for planning and policy making. Researchers frequently propose theories about the relationships between urban blight indicators, focusing on relationships reflecting causality. In this paper, we improve on the integration of domain knowledge in the analysis of urban blight by introducing four rules for effective modeling of causal domain knowledge. The findings of this study reveal significant deviation from causal modeling guidelines by investigating cognitive maps developed for urban blight analysis. These findings provide valuable insights that will inform future work on urban blight, ultimately enhancing our understanding of urban blight complex interactions.