图书情报知识 ›› 2019, Vol. 0 ›› Issue (1): 32-43.doi: 10.13366/j.dik.2019.01.032

• 专题·科研数据利用与服务 • 上一篇    下一篇

融合多源异构教育大数据的高校科研服务系统设计研究

余鹏,李艳,万晨   

  • 出版日期:2019-01-10 发布日期:2019-01-10

The System Design of University Scientific Research Service Integrating Multi-source Heterogeneous Education Big Data

  • Online:2019-01-10 Published:2019-01-10

摘要:

\[目的/意义\] 创新高校科研服务应用模式,提升科研管理水平及效率。\[研究设计/方法\] 首先,剖析教育大数据融合中的相关问题,构建面向高校科研用行为视角的多源异构教育大数据维度视图;其次,以科研对象的个性化需求作为切入点,设计了融合多源异构教育大数据的科研服务平台,分析了高校科研应用服务的大数据工作流程;最后,以科研全量数据实践体系、高校科研应用五类典型服务场景为例,给出了相关应用实践。\[结论/发现\] 实现了科研数据的深度分析与挖掘,为当前高校科研管理方法提供新思路。\[创新/价值\] 为科学提升高等院校个性化科研服务质量,客观评价科研个体及团队研究水平,辅助分析科研个体及团队优势与不足,科学指导决策者提升管理效率提供一定的方法指导。

关键词: 高校科研服务系统, 多源异构教育大数据, 科研用户行为, 科研全量数据

Abstract:

\[Purpose/Significance\] This paper aims to innovate the scientific research service mode in universities and improve the management efficiency of scientific research. \[Design/Methodology\] Firstly, the paper analyzes the relevant problems in the integration of educational big data, and constructs a multi-source heterogeneous education big data dimension version based on the perspective of university researchers' behavior. Secondly, from the perspective of researchers’individualized demands, this study designs a scientific research service platform integrating multisource heterogeneous education data, and also explores the big data workflows of university scientific research service. Finally, taking scientific research full-data practicing system and five typical scenarios of scientific research application service as examples, the relevant application practices are provided. \[Findings/Conclusion\] This study analyzes and explores scientific data. It also shed a light on scientific research management in universities. \[Originality/Value\] This research could provide some theoretical guidance for universities to improve the quality of individualized scientific research service, evaluate the research of individuals and teams, assist to analyze the advantages and disadvantages of individuals and teams, and guide decision-makers to improve efficiency of scientific research management.

Keywords: University scientific research service system, Multi-source heterogeneous education big data, Scientific research users’behavior, Scientific research full data