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Enhancing findability and searchability of research data: Metadata conversion and registration in institutional repositories
- Source :
- Data Science Journal, Vol 23, Pp 40-40 (2024)
- Publication Year :
- 2024
- Publisher :
- Ubiquity Press, 2024.
-
Abstract
- This paper outlines our practice to enhance the findability and searchability of research data through metadata conversion from the Space Physics Archive Search and Extract (SPASE) schema to a more generic schema, the Japan Consortium for Open Access Repository (JPCOAR) schema, and its registration in institutional repositories. Traditionally, earth and space science research data have been organized using the SPASE schema. Although the SPASE schema is comprehensive, its usage has been restricted to highly professional databases, limiting broader accessibility and impeding cross-disciplinary research. We discuss a case study at Nagoya University where 284 metadata records were converted from SPASE to JPCOAR, and illustrate the process and benefits of this conversion. This approach significantly improved the visibility and usability of metadata across various platforms like the Institutional Repositories DataBase (IRDB), the Data Catalog Cross-Search System, and Google Dataset Search, extending access to a wider range of users beyond the highly professional scientific community. This approach also aligns with national policies in Japan on research data management and simplifies metadata handling for researchers. Future direction includes expanding this conversion and registration model to other universities and institutions by leveraging the ubiquity of the SPASE schema in the earth and space science fields. Our practice may be useful in other research fields. This initiative aims to improve the overall findability of research data, to foster cross-disciplinary collaboration, and to enhance the value of research data itself and of creators and managers of the data.
Details
- Language :
- English
- ISSN :
- 16831470
- Volume :
- 23
- Database :
- Directory of Open Access Journals
- Journal :
- Data Science Journal
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.be33d75c0a0348a4888d5a736816cdc1
- Document Type :
- article
- Full Text :
- https://doi.org/10.5334/dsj-2024-040