Library and Information Science

Library and Information Science ISSN: 2435-8495
三田図書館・情報学会 Mita Society for Library and Information Science
〒108‒8345 東京都港区三田2‒15‒45 慶應義塾大学文学部図書館・情報学専攻内 c/o Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
Library and Information Science 88: 49-71 (2022)

原著論文Original Article

JAPAN/MARC書誌レコードからNCR2018エレメントベースのメタデータへの変換Conversion of JAPAN/MARC Bibliographic Records to NCR2018 Element-based Metadata

慶應義塾大学文学部School of Library and Information Science, Keio University ◇ 〒108–8345 東京都港区三田2–15–45 ◇ 2–15–45 Mita, Minatoku, Tokyo 108–8345

受付日:2022年8月4日Received: August 4, 2022
受理日:2022年10月25日Accepted: October 25, 2022
発行日:2022年12月30日Published: December 30, 2022




Purpose: For reconstructing the JAPAN/MARC (JPMARC) bibliographic records created by the National Diet Library in accordance with the Nippon Cataloging Rules, 2018 ed. (NCR2018) into metadata that is composed of NCR2018 entities and their elements, the purpose of this study is to develop the necessary schema-level mapping and tools that make use of it, and then to perform data conversion. This will contribute to a considerable increase of the NCR2018 data examples available as learning content.

Methods: We developed our own mapping to convert and reconstruct the JPMARC data while basically considering all the data elements in the JPMARC format for mapping. Based on this policy, appropriate methods were introduced to solve the individual mapping issues. In addition, we implemented a tool to perform data conversion based on the mapping.

Results: The characteristics of the mapping and conversion tool are as follows: 1) separate the mapping from the subsequent adjustment process, 2) introduce qualifiers to NCR elements in the mapping and utilize them in the subsequent adjustment process, 3) adopt the JPMARC data element unit as a combination of “field tag, indicator, and subfield code” and in some cases “material designation” is also combined for more accurate mapping, 4) mapping is divided into two levels with priority, and 5) the provenance information of each value is recorded. Furthermore, the mapping was divided into patterns of cardinality, and a detailed examination of the remaining issues was conducted. The implemented tool performed data conversion of 87,000 records, thereby resulting in a vast amount of metadata in line with the NCR2018 structure.

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