Four Guiding Principles for Modeling Causal Domain Knowledge: A Case Study on Brainstorming Approaches for Urban Blight Analysis

TL;DR

This paper introduces four principles for modeling causal domain knowledge in urban blight analysis, revealing deviations from guidelines and offering insights to improve understanding of urban decay interactions.

Contribution

It proposes four rules for effectively modeling causal domain knowledge and evaluates their application in urban blight analysis.

Findings

Significant deviations from causal modeling guidelines were found in cognitive maps.

Insights gained can inform future urban blight research.

Enhanced understanding of complex urban blight interactions.

Abstract

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.