| Project/Area Number |
17K00452
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Library and information science/Humanistic social informatics
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| Research Institution | Keio University |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 典拠データ / 典拠コントロール / エージェント / 著作 / メタデータ / 情報組織化 / 表現形 / 図書館情報学 |
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| Outline of Final Research Achievements |
With the aim of further enhancing authority control in library catalogs, (a) we examined and verified ways to virtually integrate domestic authority data for agents such as persons and corporate bodies into more comprehensive authority data. In addition, (b) in order to extract information related to works from existing bibliographic data and form comprehensive authority data, we tried a method to judge whether the extracted data represents a given work by applying machine learning. (c) With the intention of developing a metadata schema that can appropriately represent and manage integrated authority data, we examined various existing metadata vocabularies and schemas for authority data, and also tried to the mapping and merge of multiple models and vocabularies.
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| Academic Significance and Societal Importance of the Research Achievements |
図書館目録における典拠コントロールの一層の充実をめざして、わが国の実情に合致し、かつ必要性が高い事項に焦点を当て、有効な方策の提案とその検証を実施した。大きくは、(a)従来から実施されてきているが、国内において複数の典拠データが存在するエージェントの典拠データに関わる課題の解決と、(b)これまで殆ど実績がない著作の典拠コントロールの適用に伴う課題の解決に分けて、有効な方策の提案とその検証を実施した。これらによって、図書館目録が抱える大きな課題の解決に、研究レベルとはいえ、ある程度の見通しをつけることができたものと考える。
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