Literature Review of Scientific Data Competence: the Connotation, Framework and Influencing Factors

[Purpose/Significance] As the basis of the evaluation and promotion of scientific data competence, it is necessary to clarify the research situation of the connotation, the framework systems and the influencing factors of scientific data competence. [Method/Process] This study uses literature resear...

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Bibliographic Details
Main Author: CHI Yuzhuo
Format: Article
Language:zho
Published: Editorial Department of Journal of Library and Information Science in Agriculture 2020-01-01
Series:Nongye tushu qingbao xuebao
Subjects:
Online Access:http://nytsqb.aiijournal.com/fileup/1002-1248/PDF/1002-1248-2020-1-23.pdf
Description
Summary:[Purpose/Significance] As the basis of the evaluation and promotion of scientific data competence, it is necessary to clarify the research situation of the connotation, the framework systems and the influencing factors of scientific data competence. [Method/Process] This study uses literature research methods to collect data from both Chinese and international databases, and analyzes the research progress in four aspects: the connotation, the performance dimensions, the frameworks and the influencing factors. [Results/Conclusions] Much research has been devoted to the connotation of scientific data competence, and Chinese and international researchers' understandings are basically the same. The representative framework systems of scientific data competence are generally oriented to the process of scientific data behaviors, and put forward requirements on the users in the aspects of scientific data awareness, scientific data knowledge, scientific data skills and scientific data ethics. There are many overlaps in the top level of indicators and different emphasis on the granularity in the sub-level of scientific data frameworks. The scientific data competence is influenced by subjective factors of scientific data users, the quality of scientific data, the culture of scientific data and the standards and norms of scientific data. The research needs further theoretical integration and empirical methods should be used to further explore the influencing factors from the perspective of improving the data-intensive scientific research environment.
ISSN:1002-1248