Farm Animal Welfare

Pig Welfare and Welfare Data Science

Data science approaches to pig welfare analysis are identifying new insights from large datasets. Understanding the potential and limitations of welfare data science guides its application.

Key Facts

Large-scale farm welfare data can identify risk factors not visible in individual farm analysis
Machine learning models predict welfare outcomes from management and environmental variables
Data from multiple farms enables benchmarking and outlier identification
Data science requires high-quality standardised welfare data which is often lacking
Privacy and competitive concerns limit data sharing that would enable more powerful analysis

Welfare Considerations

Welfare data science has significant potential to identify new welfare insights and drive improvement at scale. Realising this potential requires improved data quality, standardisation, and sharing.

What You Can Do

Support organisations developing welfare data science approaches
Advocate for welfare data sharing standards that enable analysis at scale
Learn about welfare data science and its potential applications
Support investment in welfare monitoring technology that generates quality data