Abstract: Data management and sharing have been widely conducted and made substantial progress in China. The best practices of data publishing and quality control are worth analyzing. Based on scientific quality and technical quality, from the perspectives of peer review, technical review, and curatorial review, this paper analyzed best practices of quality control of several multi-disciplinary data repositories and centers in China. The analysis showed that building metadata models, developing standards and quality control systems, and releasing detailed data review guidelines are effective ways to control data quality from the scientific and technical perspective. Additionally, registration, certification, and being indexed by databases are the intuitive indicators of quality control. Furthermore, providing users with guidance on “Fair Use” at the stage of data sharing and communication is conducive to improving overall data quality control from the perspectives of data management and dissemination. Comparing the best practices of data publishing quality control at home and abroad, it is necessary to conduct in-depth explorations on issues in the future, such as intellectual property rights, rights distribution, metrics, and quality assurance and quality control related to data publishing, so as to achieve sustainable development of data sharing and publishing in China.