Characteristic Analysis of Data Description in Highly Cited Research Data

Kai, Naoto; Shimbaru, Toshiki

IIAI Letters on Institutional Research, 2022, 1, 10

Number of Access:419（2025-10-30 01:12 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/88672

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Title
Characteristic Analysis of Data Description in Highly Cited Research Data
Creator
NRID
1000090940148 1000090940148
ORCID
0000-0003-3540-3689 0000-0003-3540-3689
researchmap permalink
jr055 jr055
Scopus Author ID
57200498627 57200498627
CreatorName
Kai, Naoto
CreatorName
Shimbaru, Toshiki
Subject
Research data
Reuse
Data description
Citation
Abstract
The publication and utilization of not only evidence data of research results but also many other data associated with research activities are attracting attention as a new indicator for improving research efficiency and evaluating researchers. With the spread of open science, data repositories and data journals for research data have gradually begun to be recognized, and an environment that encourages the reuse of such research data will be further developed in the future. In this study, we focused on data description, which is important for getting an overview of research data. By clarifying the characteristics of data descriptions of highly cited research data, we hope to increase the number of citations, which will lead to the evaluation of researchers and, ultimately, to the evaluation of universities. Specifically, we will analyze the part-of-speech composition ratio of data descriptions and compare the characteristics of the highly cited research data with the low-cited research data.
Publisher
International Institute of Applied Informatics
Source Title
IIAI Letters on Institutional Research
Volume (Issue)
1
Page
10
Date of Issued
2022-08-25
Language
English
Handle URL
https://hdl.handle.net/11094/88672
eISSN
21859922
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.52731/lir.v001.010
Access Rights
open access
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article