The mechanism for addressing the relationships among data is interoperability, which is of great importance for data integrity and integration through data structure standards. Enhancing data quality and standardizing data structures facilitate improved data interoperability. The standardization of data structures simultaneously promotes data quality and interoperability. We focus on introducing the framework, general requirements, and key points of the data structure standard system. Specifically, we established a standard data structure system and recommended modules and information tables for individual-level data as the structural unit for research and real-world data involving humans within the framework. We propose best practice recommendations to enhance data interoperability and introduce a data quality assessment solution that targets datasets and databases to help determine data value. This assists in guiding the collection and processing of valuable data in the medical field.