Multisectoral data lakehouse for climate-resilient agriculture and sustainable food securityin Nigeria

Abstract

Nigeria, the most populous country in sub-Saharan Africa, faces multifaceted, overlapping problems of economic instability, security concerns, and an acute energy deficit, further aggravated by the ever-increasing impacts of climate change on its agricultural systems, a primary source of livelihood for millions.  These hydra-headed challenges require a scientific, data-driven, informed response. The paper examines how principles from the physical sciences, particularly in data management, modelling, analytics, and systems integration, can be applied to promote efficient energy resource distribution for climate-resilient agriculture (CRA), thereby boosting the economy and ensuring long-term food security. A mixed-methods approach, combining literature reviews, AI tools, case studies of climate adaptation projects, ontology-driven data harmonisation, and stakeholder consultations, was used in the research. Findings revealed that an integrated National Climate–Water-Agriculture Data Lakehouse can significantly enhance climate-resilient agriculture and energy resource sharing, thereby improving the economy and food security. The hybrid Semantic Machine learning Framework provide accurate food security analytics and predictions.   The initiative becomes a scientific laboratory and a decision-support ecosystem, transforming siloed databases into actionable insights that policymakers, researchers, and practitioners can use to enhance the economy. The paper concludes that a multisectoral ontology-driven National Climate-Water-Agriculture Data Lakehouse transforms physical science data into practical tools for climate-resilient agriculture by connecting laboratories to farmlands and datasets to decision-making, thereby enabling evidence-based agricultural governance and smart-agriculture to increase food production and boost the economies of the major and small-holding farmers in the face of emerging climatic chaos compounded by security concerns.