Co-creating data ecosystems with urban informal communities for justice and transformation
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Artificial Intelligence and Earth Observation offer powerful tools for advancing urban science; however, they risk perpetuating social and epistemic injustices when data misrepresent deprived urban areas, such as slums and informal settlements. In response, this study introduces the IDEAMAPS Data Ecosystem, a transdisciplinary framework for co-creating justice-oriented urban data. An innovative digital collaboration platform and an interactive process support the co-creation of AI-based urban models grounded in communities' priorities and assets. In partnership with local authorities, data scientists, and global experts, our methodology enables a more precise and action-oriented multidimensional characterisation of deprived areas. Evaluations across the study sites in Nairobi, Lagos, and Kano demonstrate that community-grounded data ecosystems transform both the accuracy and the politics of modelling urban informality. These findings show how community involvement can systematically enhance urban models, thereby bolstering participatory urban regeneration initiatives.
