Continuous improvement in data governance is essential for fostering data interoperability and ensuring data quality across the organization. This involves a comprehensive approach that goes beyond mere policy alignment to address the complexities of data management and utilization. Firstly, continuous improvement requires conducting thorough assessments to identify areas where data interoperability and quality can be enhanced. This entails analysing data exchange processes, assessing the compatibility of data formats and structures, and evaluating the accuracy, completeness, and consistency of data. Subsequently, initiatives should focus on implementing changes that promote interoperability and improve data quality. This may include establishing data standards and protocols for data exchange, harmonizing data schemas and vocabularies, and implementing data validation mechanisms to ensure data quality. Collaboration among different stakeholders is crucial for the success of these initiatives. Domain-specific groups should work together to define common data management practices, facilitate data sharing and integration, and address interoperability challenges across data spaces, operational domains and functional areas. Additionally, change management efforts are necessary to embed data interoperability and quality principles into the organizational culture. This involves raising awareness about the importance of data governance, providing training and support to staff, and fostering a culture of data stewardship and accountability. Continuous monitoring and evaluation mechanisms should be established to track progress and measure the impact of data governance initiatives on interoperability and data quality.