Analysis of the characteristics of Japanese institutional repositories using IRDB data
DOI:
https://doi.org/10.51094/jxiv.331Keywords:
IRDB, Departmental Bulletin Paper, institutional repositoriesAbstract
This paper is an analysis of the characteristics of Japanese institutional repositories from NII's IRDB data using PANDAS, a library for data analysis in Python. The data revealed that Japanese institutional repositories have significant characteristics in their departmental bulletin paper (Kiyou), and I extracted the characteristic institutions.Conflicts of Interest Disclosure
The authors declare no conflicts of interest associated with this manuscript.Downloads *Displays the aggregated results up to the previous day.
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References
寺田学, 辻真吾, 鈴木たかのり, 福島真太朗: Python によるあたらしいデータ分析の教科書翔泳社(2022).
大園隼彦, 片岡朋子, 高橋菜奈子, 田口忠祐, 林豊, 南山泰之: “JPCOAR スキーマの策定：日本の学術成果の円滑な国際的流通を目指して.”情報管理, vol. 60, no. 10, 2017,pp. 719–29
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Submitted: 2023-03-12 07:15:13 UTC
Published: 2023-03-22 06:33:42 UTC
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Information Sciences
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Copyright (c) 2023
Wataru Ono
This work is licensed under a Creative Commons Attribution 4.0 International License.
