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Using Structured Metadata to Manage Forestry Research Information: A New Approach

利用結構化的後設資料管理林業研究資訊:一種新途徑

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摘要


研究計劃資訊的保存與森林調查資訊的標準化是森林經營上非常重要的基礎工作。台灣林業試驗所與美國維吉尼亞大學共同合作開發的生態資訊管理系統讓不嫻熟複雜的資訊技術之研究人員,可建置與獲取相關的研究資訊並可做更深入的研究課題。本研究利用美國長期生態研究網發展的生態後設資料語言做為資料文件化的標準,並採用貝有儲存、複製、查詢、驗證、移轉與認證籌功能之資料目錄系統。截至2006年底,林業試驗所資料目錄伺服器已儲存了208份資料文件,做為本論文的評估數據。結果顯示林業研究項目的多樣化,亦證明這套後設資料標準不僅適用生態研究,也適用於林業研究。這套系統可做為林業研究之資料管理的新途徑,研究人員因而可建立、儲存、存取研究資料,本系統已達到研究計劃與資料保存的基本要求。此外,本系統在資料品質的控管上已能對資料型態、資料範圍與空間分布做到基本的檢核功能,並能提供研究人員經由此系統而接修正檢驗出的錯誤。

關鍵字

林業 資訊管理 後設資料 品質保證 資料

並列摘要


Documentation of field datasets and preservation of project information are important for resolving forest management problems. The Taiwan Forestry Research Institute (TFRI), Taipei, Taiwan and the University of Virginia. Charlottesville, VA, USA collaborated to conduct information management research and to develop a system to help scientists acquire and document large numbers of datasets and other research information, without requiring researchers to develop knowledge of information technologies. We chose the Ecological Metadata Language (EML) as the standard to document all research data, and set up a Metacat (metadata catalog) server for TFRI. The Metacat server manages all modules of an EML document database, which are able to store, replicate, query, validate, transform, and authenticate documents, as well as manage user access. In total, 208 EML documents had been created and evaluated by the end of 2006. These EML documents reflect the diversity of forestry research in Taiwan. Although the EML standard is more suitable for biological and ecological fields, EML has been adapted by the broad forest science community, including forest utilization research. The Metacat system should be useful to the forestry community for creating, storing, managing, and retrieving research data. Thus, the system meets the basic requirement of scientists to develop a data legacy. Our tools allow researchers to automate basic quality assurance processes (i.e., data type. data range, and spatial distribution) and correct mistakes found by the system.

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