EcoTransit Global, a consortium of engineering firms from Japan, Germany, and the United States, is collaborating on the development of a next-generation sustainable transportation vehicle. The project involves diverse stakeholders, including design engineers focused on precision, manufacturing teams prioritizing efficiency, regulatory bodies demanding compliance, and marketing divisions emphasizing customer satisfaction. Each group has unique data requirements and quality expectations. The Japanese team insists on meticulous data lineage and traceability, the German team prioritizes data consistency and standardization, while the US team focuses on agile data accessibility and real-time reporting. How should EcoTransit Global establish a data governance framework that effectively balances the diverse data quality needs and priorities of all stakeholders, ensuring high-quality data throughout the project lifecycle, from initial design to post-market support?