Subjects: Library Science,Information Science >> Library Science submitted time 2023-11-06
Abstract: The evaluation of discipline construction effect is so important to the strategy formulation, program implementation and development path of discipline construction. ESI data can be used as one of the dynamic monitoring data to objectively evaluate the effectiveness of university discipline construction. The paper constructs an objective evaluation model of discipline construction effectiveness based on ESI highly cited papers. Taking H University as a case, the paper analyzes the tracking data of 30 ESI highly cited papers of H University in the past five years through bibliometrics and statistics methods. It finds that H University has achieved remarkable results in discipline construction, with teachers, students, faculties and departments making efforts. Dominant disciplines’ construction is outstanding, but some disciplines’ construction is slow. In the future, the university can adjust development path from the system mechanism, professional layout, team construction, etc., and promote more disciplines to become world-class disciplines.
Peer Review Status:Awaiting Review
Subjects: Library Science,Information Science >> Information Science submitted time 2023-09-21
Abstract: Purpose/significance By using the uniqueness and linkability of linked data, the paper tries to discover and correlate academic relationship of institutional repository entities,in order to realize institutional repository resources semantic aggregating. Method/process It analyzes the types and characteristics of the entity academic relationship and linked data requirements, then puts forward academic relationship association methods. Finally it uses the data of Hohai University Institutional Repository to conduct an empirical study. Results/Conclusion The paper builds the method of discovering entity academic relationships based on linked data. It finds out the academic relationships of empirical data and points out its application value. This method can realize semantic associating of institutional repository resources, and provide knowledge retrieval service based on linked data, which can meet user's knowledge needs.