Subjects: Library Science，Information Science >> Utilization of Information submitted time 2024-04-01
Abstract： Purpose/significance By utilizing the Data Citation Index (DCI) database, this article explores the reuse features and influencing factors of scientific data in the field of high-energy physics. These findings serve as a point of reference and support, facilitating the promotion of data sharing and citation standardization in China. Moreover, these contribute to the augmentation of both value and influence of scientific data. Method/process This article adopt statistical regression methods to analyze the basic and citation features of the DCI database. For the reuse features and influencing factors, the analysis includes three dimensions: scientific data attribute features, reuse features, and correlation between attribute and reuse features. Result/conclusion The research findings reveal that the publication volume of scientific data in the field of high-energy physics is exhibiting an increasing trend. However, the proportion of missing data fields is relatively high. The reuse of high-energy physics scientific data is significantly influenced by publication modes and disciplinary categories. These result in the extremely uneven distribution of citation frequency. High-level scientific data are more likely to be reused. Moreover, the standardization of scientific data sharing and citation needs further enhancement. Finally, we propose an optimization and improvement path for high-energy physics science data reuse based on this findings.
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Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/Significance] By studying the characteristics and laws of knowledge diffusion of scientific datasets, this paper explores the practical role of scientific datasets in the development of discipline fields, so as to provide references for scientific and technological evaluation and management policy-making of scientific datasets. [Method/Process] Taking the datasets of GEO database and the full-text data of reused dataset in PubMed Central Database as the analysis objects, this paper analyzed the knowledge diffusion characteristics of scientific datasets by using content analysis method combined with knowledge diffusion indicators such as diffusion breadth, diffusion intensity and diffusion speed. [Result/Conclusion] The results show that the breadth and intensity of knowledge diffusion of scientific datasets are increasing day by day. Reusing data can accelerate the speed of knowledge diffusion, and China’s position in the field of global scientific data is improving.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/Significance] This paper analyzes the use characteristics of scientific datasets from the perspective of quantitative analysis and content analysis, quantitatively evaluates the impact of scientific datasets on discipine development, and provides references for scientific data management services and policy research.[Method/Process] Methods of text mining and bibliometric were used to analyze the full-text literature in PubMed Central, this study comprehensively investigated the use of scientific datasets from 7 aspects such as time distribution and use intensity, and on this basis, evaluated the actual impact of scientific datasets on discipline development.[Result/Conclusion] The research results show that the influence of scientific datasets on scientific research in the biomedical field is increasing with each passing day. Data publishing and high-level journals promote the opening and sharing of scientific datasets. The use of scientific datasets is concentrated in the second half of the paper and there are few formal references. The corresponding standards and specifications need to be further strengthened.
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