IntroductionThe BREATHE Health Data Research Hub is a consortium of five academic institutions and several industry partners seeking to facilitate and accelerate respiratory science initiatives and outcomes. Unlocking organisational, jurisdictional, and scientific challenges, such as differing and inherent complexities with data standards, incongruous governance, and disparate data access mechanisms for over 100 diverse UK datasets are key aims. Objectives and ApproachCentral to the data effort is the UK Secure eResearch Platform (SeRP UK), and its flagship tenancy, the SAIL Databank. Onboarding datasets, making them remotely available to the respiratory research community, is a key approach. Datasets targeted range from population cohort studies, to respiratory trials data, routine healthcare datasets, and specialist ‘omics data. Partnerships with national safe havens and providers such as eDRIS and NHS Digital will enable BREATHE to expedite and improve wider sharing of datasets for the respiratory science. Data improvements focus on datasets from primary, secondary, and tertiary care from national healthcare systems, ‘respiratorising’ these datasets and increasing utility for academic and industry respiratory scientists. Incorporating dataset metadata and access permutations into national cataloguing systems at HDR UK, standardising metadata, and interoperability for in-scope datasets form a concerted data quality improvement effort. ResultsFacilitating data sharing through initiatives such as BREATHE will increase visibility and accessibility for datasets within respiratory science, whilst addressing national cultural and governance issues to data sharing. BREATHE data sharing processes will allow for team science to be undertaken in a highly collaborative manner and allow for best practise in data collection and sharing to flow to nationwide datasets in respiratory science. Conclusion / ImplicationsCollaborative hubs with scientific domain expertise can be created and leveraged to accelerate data sharing and data science within the scientific area. These collaborative efforts can however be translated to other disease-specific efforts, and indeed disease agnostic platform solutions.