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Integration Management and Reuse of Research Data in the Next Generation University IR Resources
| Open Access
- DU Pingping, LI Yuke, ZHANG Xueyuan, MU Yafeng
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2023, 35(5):
51-63.
DOI: 10.13998/j.cnki.issn1002-1248.23-0159
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[Purpose/Significance] In 2021, the Ministry of Education of China issued the "Norms for the Construction of Digital Campuses in Higher Education Institutions (Trial)", which mentioned that universities should attempt to form a new model of academic exchange and resource sharing through the construction of institutional repositories (IRs). The construction of knowledge resources in university IRs is gradually developing towards the next generation IRs. Research data resources are an important component of the future resources. From the perspective of the generation, acquisition, and existence of information resources in universities, the institutional resources in universities primarily consist of resources generated by "industry, academia, research and application" activities, including teaching resources, scientific research resources, design resources, scientific activity resources, etc., which are specifically reflected in the activity process such as scholar resources, research activity resources, research process resources, and research achievements resources. Research data resources are studied as the research object in this article. [Method/Process] This paper analyzes the formation mechanism of institutional knowledge resources, and conduct research on the integration, management and reuse of research data resources, including: 1) internal factors of research data, data generation, source, type, structure, and dependency mode; 2) research on external elements of data, such as data standards, unique identifiers, data registration, data protocols, data rights, data reuse, and data sharing Through the study of internal and external factors, the influencing factors, functions and roles, responsibilities and rights, permissions and attribution of data integration management and data reuse were sorted and interpreted and feasible methods were designed for research data management, collection, implementation, and registration. In order to ensure the effectiveness of data management, a series of standards and schemes have been developed, such as data type and format standards, metadata schemes, and data guardianship demand survey templates. The purpose is to achieve data discovery, interoperability, and reuse through continuous monitoring of scientific data. The basic rules of reuse are mainly divided into: 1) reuse: the concept of reuse, reuse, sharing, and incomplete equivalence in reuse; 2) sharing: possible to be used; 3) protocol usage: discussion about how to use it; and 4) rights use: complying with the data copyright agreement. [Results/Conclusions] Through research courses, the development and implementation of favorable data management and reuse strategies have clarified the data objects, management set management services, and data reuse permissions of research data in university IRs. We have clarified the current situation and urgent issues to integrate research data into the long-term preservation, management, and sharing and reuse system of knowledge resources in university IRs. We have defined the responsibilities, management mechanisms, standardized business processes, permission attributes, data exchange platforms, data registration, and data reuse of research data subjects by category, region, and field, and provided some suggestions and guarantee measures for the establishment of a data management center in China.