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ISSN : 1013-0799

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Vol.41 No.3

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Analysis of Research Trends in Data Curation Using Text Mining Techniques

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2024, v.41 no.3, pp.85-107
https://doi.org/10.3743/KOSIM.2024.41.3.085
Jaeeun Choi (Ewha Womans University)
Choi, J. (2024). Analysis of Research Trends in Data Curation Using Text Mining Techniques. Journal of the Korean Society for Information Management, 41(3), 85-107, https://doi.org/10.3743/KOSIM.2024.41.3.085

Abstract

This study analyzes trends in data curation research. A total of 1,849 scholarly records were extracted from Scopus and WoS, with 1,797 papers selected after removing duplicates. Titles, keywords, and abstracts were analyzed through keyword frequency analysis, LDA topic modeling, and network analysis. Frequent keywords like ‘research’ and ‘information’ suggest that data curation is widely applied in medical research, biomedical research, data management, and infrastructure. LDA modeling identified five main topics: improving medical data quality, enhancing big data management, managing scientific data and repositories, annotating and modeling medical data, and gene/protein database research. Network analysis showed that ‘analysis’ was central in global discussions, while ‘gene’ and ‘system’ were locally central. These findings highlight the importance of data curation in various research areas.

keywords
데이터 큐레이션, 연구동향, 토픽 모델링, LDA, 네트워크분석
Submission Date
2024-08-14
Revised Date
2024-08-29
Accepted Date
2024-09-03

Journal of the Korean Society for Information Management

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