Interoperability by Design for a Collectively Governed Datasphere

This paper by Kassy Raymond, Datasphere Initiative Fellow 2021-22, presents a database framework using livestock population data from four data sources as a case study.

Livestock population data is crucial for estimating climate change impact, nutrition, livestock biomass, antimicrobial resistance, and the burden of animal disease on humans and animals. However, differing classification systems and naming conventions pose challenges to data interoperability and discoverability.

This study discusses variability in species naming conventions using the Datasphere concept and offers suggestions to improve the interoperability of livestock population data from national and international government sources.