Research on the Right Identification and Right Description Standard of Service Data Based On ODRL

This article mainly solves the problem of standardization of ownership and rights description of the main stakeholders in the field of data circulation in the field of data governance: combining the status quo of data protection and ownership identification, starting with the logical relationship between data and information, deconstructs the service data for subject ownership identification; combs the relevant laws and regulations of data protection, and defines the rights of each subject. In order to realize the structure and machine-readable of the right language, we should refer to the ODRL information model of W3C to build the right description standard of service data, describe the application of the standard in the actual transaction scenario, and build the hierarchical right transfer model in the process of data transaction. 1 Research background Data has become the new oil in the era of digital economy [1] , and there is infinite value behind the cleaned data. The development and utilization of big data has become an inevitable trend. Both the government and enterprises take the rational use of data assets as an important part of strategic planning. Service data is a kind of data type closely related to economy and personal life. It is produced in all service processes, generated and gradually accumulated under the joint action of consumers and service providers, and controlled by service providers in practice, which has become its unique business competitive advantage. Because of its multi-agent, multi-dimensional, dynamic uncertainty and other characteristics, service data has not yet been defined clearly and generally, lack of legal framework to regulate, especially lack of the definition of the scope of the rights of stakeholders, coupled with the complex composition of service data, involving the identification of personal information rights, making the use and circulation of data a very difficult legal problem. Although personal data transactions have been legalized in the United States, Japan and other countries [2] , up to now, there has not been a unified standard for data confirmation, and the flow of data compliance has been hindered. Data will create more value only if it is circulated, and data innovation is the key factor for market growth and job creation. How to find a balance between the protection of personal data and the free flow of data, better and more secure mining the value behind big data, has