Digital platform as a tool for data management of the potato production system in Colombia

• Digital platform improves data management in potato production systems in Colombia. • Integrates data science, modeling, and visualization for yield forecasting. • Supports evidence-based decisions with tools for edaphic, climatic, and phytosanitary data. • Platform democratizes information for stakeholders across the potato supply chain. Effective data management remains one of the main challenges in modern agriculture, requiring the integration of data science, information systems, and modeling approaches within digital platforms that support evidence-based decision-making. This study aimed to apply data science tools and multifocal modeling techniques to develop an open-access digital platform designed to integrate, manage, and analyze information from potato production systems in Colombia. The methodological framework consisted of a sequence of data science processes designed to organize, clean, and visualize datasets collected by the FEDEPAPA–FNFP extension program, encompassing soil physicochemical properties, phytosanitary records, climatic variables, yield data and academic trends. Modeling was conducted at the level of climatic clusters and production semesters using multiple models, including Generalized Linear Models (GLM), Least Absolute Shrinkage and Selection Operator (LASSO), and Automated Machine Learning (AutoML). The results demonstrate the successful integration of agronomic, phytosanitary, and climatic information into the first version of an open-access digital platform featuring six interactive modules. One of these modules incorporates the proposed modeling framework for potato yield forecasting, enabling users to explore model outputs and data relationships in a user-friendly environment. The other modules include visualization tools for managing land resources, plant health, climate, and academic trends. The platform provides a foundation for the application of analytical and predictive tools across multiple aspects of potato production, fostering more informed decision-making among producers, researchers, and policymakers. Our work represents a significant step toward the democratization of agricultural information and the advancement of data-driven management practices in Colombia’s potato sector.