This chapter explores the critical role of data sharing and standardised metadata in advancing home cage monitoring (HCM) research. It examines the scientific, ethical, and computational advantages of sharing HCM data, particularly in the context of enhanced research quality in accordance with the 3Rs principles (Replacement, Reduction, Refinement). Challenges hindering widespread data sharing, including cultural, incentive, technical, and governance issues, are discussed. Strategies for effective data sharing, such as data storage solutions, FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, and the use of controlled vocabularies and ontologies, are presented. The chapter envisions a future where federated networks of interoperable HCM platforms enable advanced data/metadata integration and analysis powered by advanced computational tools. These systems would yield valuable insights into biomedical research, animal behaviour, and welfare in an AI-ready field.