Falahatkar, Hawjin. Fast, Victoria.2023-08-102023-08-102023-07-14https://hdl.handle.net/1880/116845https://dx.doi.org/10.11575/PRISM/41687A significant hurdle to employing data-driven and computational methods in urban design for people-place relation analysis is when the research is driven not by in-depth knowledge and theory of the field, but by data, which could lead to data autocracy. This paper aims to develop a feminist-driven framework for computational urban design to map, measure, and analyze gender-inclusive features of urban places. The framework suggests that data requirements for a computational urban design assessment need to be initially determined from domain theory patterns. The results demonstrate that the integration of multi-type, multi-scale, and multi-source datasets is needed to address all gender-inclusive features of urban places. Finally, we conclude that by adopting a theory-driven approach, it is possible to define a research system through which the re-searcher can control the data flow, guide the research path, and benefit from opportunities of geospatial big data and data-driven methods for conducting computational urban design.enAttribution-NonCommercial-NoDerivatives 4.0 InternationalArticle10.17605/OSF.IO/6YR5V