An Original Investigation into the Theoretical Basis for Data-Driven Urban Planning in Nigerian Megacities

Nigerian megacities including Lagos, Kano, and Ibadan are growing at rates that outpace conventional planning capacity, and developing an original theoretical framework for data-driven urban planning that accounts for the specific governance, infrastructure, and informality characteristics of these cities represents a significant contribution to urban data science. This study developed an original theoretical framework for data-driven urban planning in Nigerian megacities. A constructive theoretical methodology was employed, drawing on systematic review of smart city and urban data science theory (74 publications from 2019 to 2024), empirical case analysis of data-driven planning initiatives in Lagos, Kano, and Ibadan, and structured consultations with 35 urban planners, data scientists, and local government officials. Case analysis confirmed that existing smart city frameworks inadequately theorise the role of informal settlements constituting 60 to 80 percent of Nigerian megacity built environments, the data vacuum created by absent addressing systems and incomplete cadastral records, and the political economy of urban data capture in contexts of weak property rights enforcement. The original Nigerian Megacity Data-Driven Planning Framework proposes four planning data dimensions: formal infrastructure data (utilities, roads, cadastre), informal settlement data (remote sensing and participatory mapping), mobility data (survey and digital trace), and socioeconomic data (census and administrative records). Original theoretical contributions include the Data-Formality Interface Model explaining how planning decisions must navigate formal and informal urbanism evidence simultaneously. Expert review by 20 urban planning and data science scholars confirmed the framework's original contribution.

Keywords: data-driven urban planning, Nigerian megacities, smart city theory, informality, original framework