The need for collaborative and transparent sharing of COVID-19 clinical trial and large-scale observational study data to accelerate scientific discovery and inform clinical practice is critical. Responsible data-sharing requires addressing challenges associated with data privacy and confidentiality, data linkage, data quality, variable harmonization, data formats, and comprehensive metadata documentation to produce a high-quality, contextually rich, findable, accessible, interoperable, and reusable (FAIR) dataset. This communication explores the experiences and lessons learned from sharing National Heart Lung and Blood Institute (NHLBI) COVID-19 clinical trial (including adaptive platform trials) and cohort study datasets through the NHLBI BioData Catalyst® (BDC) ecosystem, focusing on the challenges and successes of harmonizing these datasets for broader research use. Our findings highlight the importance of establishing standardized data formats, adopting common data elements and creating and maintaining robust data governance structures that address common challenges (i.e., data privacy and data-sharing limitations resulting from informed consent). These efforts resulted in a set of comprehensive and interoperable datasets from 5 clinical trials and 13 cohort studies that will enable downstream reuse in analyses and collaborations. The principles and strategies outlined, derived through experience with consortia data, can lay the groundwork for advancing collaborative and efficient data sharing.