Identifying Digitalisation patterns in Spanish livestock farming through open data use. A proposal of best practice management

Digitalization in Spanish livestock farming is a key factor for efficiency, sustainability, and competitiveness. This study identified digitization patterns using open data and proposed best-practice strategies to support the sector's digital transition and targeted public policies. An open-access dataset from the Spanish Ministry of Agriculture (MAPA, 2024) covering 603 farms was analysed. Twenty-three variables describing production systems, digital technologies, and training were processed, and principal component and hierarchical cluster analyses were applied. Five factors explaining 62.85% of the total variability were identified, leading to three farm types: Smallholders (34.83%) with minimal digitalization; Family farms (27.69%) with low technological adoption; and Commercial farms (37.48%) with intermediate digitalisation. Digitalisation was positively associated with farm size, training, and regional technological development, while a gender gap emerged, with most women-managed farms in low-digitalisation clusters. The study showed the value of open data for identifying digitalisation patterns and provided evidence-based foundations for digital transition through a best-practice framework to accelerate Smart Farming across farm profiles. For smallholders, basic digitisation packages and subsidised rural connectivity are prerequisites for the uptake of digital tools and collection of operational data in structurally constrained contexts. For family farms, integrated management platforms (ERP-type solutions) and targeted training in data management and decision-support are essential to improve production organisation and strengthen digital competencies. For larger commercial operations, the results highlight the need to promote interoperability among IoT devices, sensor networks, and farm management software, and indicate that AI-based predictive analytics and smart alert systems can enhance monitoring and overall operational efficiency.