Data for famine and extreme emergencies: challenges and opportunities

High-quality data are a pre-requisite for the development of models-whether of famine or food and nutrition-related emergencies. We highlighted challenges, related to data in famines or near-famine emergencies, including data availability, quality, timeliness, and sharing; the misuse of data could be a real threat for applying new advanced data analytic tools, such as artificial intelligence and machine learning. We also explored promising opportunities, such as democratization of data related to famine. With growing demands for real-time assessment and modeling of famine and extreme emergencies, it is increasingly important to understand how predictive models and emerging data-integration technologies are affected by biased, incomplete, inconsistent, or outdated data. As we push for addressing data constraints, we call for ethical data democratization to minimize the risks of data misuse, weaponization, and politization and to enable famine modeling for collective efforts to enhance early warning, real-time analysis, and response.