Development of a system for efficient content-based retrieval to analyze large volumes of climate data

• Material Type: 記事
• Title: Development of a system for efficient content-based retrieval to analyze large volumes of climate data
• Author/Editor: Yujin Nakagawa; Yosuke Onoue; Shitnaro Kawahara
• Publication, Distribution, etc.: 日本 : Springer Nature
• Publication Date: 2020-02-26
• Publication Date (W3CDTF): 2020-02-26
• Periodical title: Progress in earth and planetary science
• No. or year of volume/issue: 7(9)
• Volume: 7(9)
• ISSN (Periodical Title): 2197-4284
• ISSN-L (Periodical Title): 2197-4284
• Text Language Code: eng
• DOI: 10.1186/s40645-019-0315-9; https://doi.org/10.1186/s40645-019-0315-9
• Persistent ID (NDL): info:ndljp/pid/11467733; https://dl.ndl.go.jp/pid/11467733
• Collection: 障害者向け資料
• Collection (Materials For Handicapped People:1): テキストデータ
• Collection (particular): 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• Acquisition Basis: オンライン資料収集制度
• Date Accepted (W3CDTF): 2020-03-23T18:58:42+09:00
• Date Captured (W3CDTF): 2020-03-23
• Format (IMT): application/pdf
• Access Restrictions: 国立国会図書館内限定公開
• Service for the Digitized Contents Transmission Service: 図書館・個人送信対象外
• Availability of remote photoduplication service: 可
• Periodical Title (URI): https://progearthplanetsci.springeropen.com/articles
• Periodical Title (Persistent ID (NDL)): info:ndljp/pid/11467724; https://dl.ndl.go.jp/pid/11467724
• Data Provider (Database): 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• Summary, etc.: Analyses of large ensemble data on future climate are significantly useful for the probabilistic future projection of climate change in various interdisciplinary fields. However, the data volume of the Database for Policy Decision making for Future climate change or d4PDF, which is a mega-ensemble dataset, exceeds ∼ 3 PB, which is too large to download to local computers. To allow users for retrieve and downloading necessary data, we developed a user-friendly system called “System for Efficient content-based retrieval to Analyze Large volume climate data” (SEAL) under the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT). Conventional web-based retrieval systems allow retrievals using metadata associated with a data file itself. In contrast, SEAL allows the users to retrieve the necessary data by using metadata associated with contents, such as physical values, of a data file. We confirmed that SEAL can reduce data sizes and total time required for obtaining necessary data to less than 0.5% and 1%, respectively, compared to conventional web-based retrieval systems.; 大規模な気候シミュレーションデータを効率的に探索・取得するシステム(SEAL)を開発 --都道府県単位の将来予測も簡単表示、温暖化適応策検討にも貢献--. 京都大学プレスリリース. 2020-03-03.
• DOI: 10.1186/s40645-019-0315-9; https://doi.org/10.1186/s40645-019-0315-9
• Access Restrictions: インターネット公開
• Rights (production): © The Author(s). 2020. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
• Related Material (URI): http://hdl.handle.net/2433/245880; http://id.ndl.go.jp/digimeta/11467733; https://dl.ndl.go.jp/pid/11467733; http://link.springer.com/content/pdf/10.1186/s40645-019-0315-9.pdf; http://link.springer.com/article/10.1186/s40645-019-0315-9/fulltext.html
• Is Referenced By: d4PDFの直接ダウンスケーリングによる伊勢湾におけるL2想定高潮の将来変化; https://cir.nii.ac.jp/crid/1390571415710547072; アンサンブル気候予測データベースd4PDFによる岐阜県の豪雨発生要因の将来変化; https://cir.nii.ac.jp/crid/1390571704642824576; 区分的渦位逆変換法による台風の指向流ベクトルの温暖化影響評価; https://cir.nii.ac.jp/crid/1390869150138365312
• Data Provider (Database): 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• Original Data Provider (Database): 学術機関リポジトリデータベース; https://irdb.nii.ac.jp; 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; CiNii Articles
• Bibliographic ID (NDL): 11467733; http://id.ndl.go.jp/bib/11467733
• NAID: 120006800723