Mingting Zhu ¹ Weibin Zhang ^2* Chongli Xu ^1*

• ¹ Xiamen University, Xiamen, China
• ² Anhui University of Finance and Economics, Bengbu, Anhui Province, China

While global marine science data sharing plays a crucial role in advancing scientific research and knowledge dissemination, it also brings with it two major ethical conflicts, those between individual interests and the public interest, and those between data privacy and data sharing, which are rooted in conflict of interest. In the context of globalization and rapid technological progress, current ethical governance frameworks are inadequate in regulating these conflicts. On the one hand, governance cannot meet the needs of rapidly evolving technologies; on the other hand, the complexity and diversity of stakeholders involved in governance make it more difficult. By introducing the theory of legal hierarchy and innovatively proposing the theory of ethical hierarchy, which classifies the ethical principles to be followed according to their importance and applicability, the priority and scope of application between different ethical principles can be clearly defined, so that various stakeholders can make the right ethical choices. Using research methods such as literature review, case studies and comparative analysis, we propose to construct an ethical governance framework that consists of a stakeholder consultation and communication network in terms of governance structure, and clarifies the ethical responsibilities of each party in data sharing in terms of governance measures. This framework not only provides a platform for communication and cooperation among different stakeholders, but also helps to balance the interests of different stakeholders and improve the level and extent of global marine science data sharing. coloured soluble organic matter, etc.), information on the marine dynamic environment (seawater temperature, sea surface wind field, sea surface height, waves, currents, ocean gravity field, etc.), as well as marine biology, marine chemistry, seabed geology, marine biology, marine chemistry, seabed geology, sediment, underwater topography, sea ice, seawater pollution and other marine environmental information. The main means of obtaining marine natural science data include actual observations, ocean remote sensing observations and ocean numerical modelling. Therefore, ocean natural science big data can be divided into actual ocean measurement data, ocean remote sensing data and ocean model data.