  Data-driven advances have resulted in significant improvements in dairy
production. However, the meat industry has lagged behind in adopting
data-driven approaches, underscoring the crucial need for data standardisation
to facilitate seamless data transmission to maximise productivity, save costs,
and increase market access. To address this gap, we propose a novel data
schema, Livestock Event Information (LEI) schema, designed to accurately and
uniformly record livestock events. LEI complies with the International
Committee for Animal Recording (ICAR) and Integrity System Company (ISC)
schemas to deliver this data standardisation and enable data sharing between
producers and consumers. To validate the superiority of LEI, we conducted a
structural metrics analysis and a comprehensive case study. The analysis
demonstrated that LEI outperforms the ICAR and ISC schemas in terms of design,
while the case study confirmed its superior ability to capture livestock event
information. Our findings lay the foundation for the implementation of the LEI
schema, unlocking the potential for data-driven advances in livestock
management. Moreover, LEI's versatility opens avenues for future expansion into
other agricultural domains, encompassing poultry, fisheries, and crops. The
adoption of LEI promises substantial benefits, including improved data
accuracy, reduced costs, and increased productivity, heralding a new era of
sustainability in the meat industry.
