Findable, Accessible, Interoperable and Reusable (FAIR) data sharing has gained considerable attention due to its undeniable benefits for the scientific community, and interest from the livestock industry. In animal science, a wide spectrum of datasets are generated by diverse disciplines, including omics data (genomic, transcriptomic, proteomic and metabolomic), functional information (e.g. genome annotation, ChIP-seq and ATAC-seq) and phenotype data (e.g. production traits, nutrition, product quality, body composition and behaviour). Although omics data, particularly sequence data, are routinely deposited in publicly accessible repositories, the sharing of phenotype data remains rare, less standardised and often overlooked. Integrating phenotype data into existing genomic platforms would improve access to, and discovery and reuse of, livestock data. It would also facilitate the integration of phenotype and omics layers and promote the adoption of common standards, vocabularies and best practices for data management. This integration would allow researchers to improve genome annotation, generate new hypotheses, perform cross-study analyses and design studies with greater statistical power. It could achieved through displaying linked phenotype information and variation data in the genome browser Ensembl for example, which is currently available for humans via the G2P plug in for the Variant Effect Predictor (VEP). However, because data submission to the public repositories is currently fragmented this is difficult to achieve. Sequence data are deposited in repositories such as most commonly for Europe to the European Nucleotide Archive (ENA) and globally to the National Center for Biotechnology Information (NCBI), while phenotype datasets may be scattered across Zenodo, Dryad, or Figshare. Genotype data from SNP arrays are often inaccessible due to commercial or privacy concerns, and linking records (e.g. nucleic acid sequences from ENA) to individual phenotypes remains challenging. Metadata is often sparse, which further reduces reusability. The lack of unified standards and inconsistent application of ontologies result in heterogeneous data descriptions that hinder integration. Integrating phenotype data into existing public repositories through a standardised submission pathway would address these challenges directly, creating a more coherent, comprehensive and sustainable ecosystem for sharing data in European animal science and globally.