2023 Fiscal Year Final Research Report
Metadata profiles based usability and accessibility enhancements for LOD datasets
| Project/Area Number |
21K12579
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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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| Review Section |
Basic Section 90020:Library and information science, humanistic and social informatics-related
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| Research Institution | University of Tsukuba |
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Principal Investigator |
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | メタデータ / メタデータスキーマ / セマンティックWeb / Linked Open Data |
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| Outline of Final Research Achievements |
Metadata creators are experts in their domain and may not have experience or knowledge of metadata schema design, and it is difficult to combine metadata terms such as properties and classes defined in metadata vocabulary definitions appropriately in LOD datasets simply by referring to those vocabulary definitions. It is difficult to adequately combine and structure metadata terms such as properties and classes defined in these vocabularies in an LOD dataset. Therefore, in order to increase the use of LOD datasets, this study considers it necessary to support the selection of appropriate metadata terms and the design of highly usable metadata models, and has set the following two research objectives
1) To propose a domain-specific metadata term selection support model.
2) To propose a metadata model evaluation support model based on the FAIR principle.
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| Free Research Field |
情報科学
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| Academic Significance and Societal Importance of the Research Achievements |
LODデータセットの作成では，コミュニティの目的に特化した独自のメタデータ語彙に加えて，既存のメタデータ語彙を組み合わせて利用している．しかしながら，LODデータセットのドメインに適切なメタデータ記述項目を表現するための適切なプロパティやクラスといったメタデータタームの選択と，それらメタデータタームを組み合わせてメタデータ記述のための制約を与えた構造の作成は，作成者の知識や経験に依るところが大きい．本研究では，LODデータセットの利活用性向上を目的として，ドメインに適切なメタデータターム選択手法とメタデータモデルの評価手法を明らかにし，そのための支援環境の構築をおこなった．
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