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Organizing scientific data sets: Studying similarities and differences in metadata and subject term creation.

机译:组织科学数据集:研究元数据和主题词创建方面的异同。

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摘要

BACKGROUND: According to Salo (2010), the metadata entered into repositories are "disorganized" and metadata schemes underlying repositories are "arcane". This creates a challenging repository environment in regards to personal information management (PIM) and knowledge organization systems (KOSs). This dissertation research is a step towards addressing the need to study information organization of scientific data in more detail.;METHODS: A concurrent triangulation mixed methods approach was used to study the descriptive metadata and subject term application of information professionals and scientists when working with two data sets (the bird data set and the hunting data set). Quantitative and qualitative methods were used in combination during study design, data collection, and analysis.;RESULTS: A total of 27 participants, 11 information professionals and 16 scientists took part in this study. Descriptive metadata results indicate that information professionals were more likely to use standardized metadata schemes. Scientists did not use library-based standards to organize data in their own collections. Nearly all scientists mentioned how central software was to their overall data organization processes. Subject term application results suggest that the Integrated Taxonomic Information System (ITIS) was the best vocabulary for describing scientific names, while Library of Congress Subject Headings (LCSH) was best for describing topical terms. The two groups applied 45 topical terms to the bird data set and 49 topical terms to the hunting data set. Term overlap, meaning the same terms were applied by both groups, was close to 25% for each data set (27% for the bird data set and 24% for the hunting data set). Unique terms, those terms applied by either group were more widely dispersed.;CONCLUSIONS: While there were similarities between the two groups, it is the differences that were the most apparent. Based on this research it is recommended that general repositories use metadata created by information professionals, while domain specific repositories use metadata created by scientists.
机译:背景:根据Salo(2010)的说法,输入存储库的元数据是“杂乱无章”的,而存储库下面的元数据方案是“ arcane”。这在个人信息管理(PIM)和知识组织系统(KOS)方面创建了一个具有挑战性的存储库环境。本论文的研究是朝着更详细地研究科学数据的信息组织的需要迈出的一步。方法:同时三角剖分混合方法用于研究信息专业人员和科学家的描述性元数据和主题词应用,当两个人一起工作时数据集(鸟类数据集和狩猎数据集)。在研究设计,数据收集和分析过程中结合使用了定量和定性方法。结果:共有27名参与者,11名信息专业人员和16名科学家参加了这项研究。描述性元数据结果表明,信息专业人员更可能使用标准化的元数据方案。科学家们没有使用基于图书馆的标准来组织自己馆藏中的数据。几乎所有科学家都提到了中央软件在其整体数据组织过程中的表现。主题词应用结果表明,综合分类信息系统(ITIS)是描述科学名称的最佳词汇,而国会图书馆主题词(LCSH)则是描述主题术语的最佳词汇。两组将45个主题词应用于鸟类数据集,并将49个主题词应用于狩猎数据集。术语重叠,意味着两组都使用了相同的术语,每个数据集接近25%(鸟类数据集为27%,狩猎数据集为24%)。独特的术语,两组中使用的那些术语散布得更广泛。结论:虽然两组之间存在相似之处,但最明显的区别是。基于此研究,建议一般存储库使用信息专业人员创建的元数据,而特定领域的存储库使用科学家创建的元数据。

著录项

  • 作者

    White, Hollie C.;

  • 作者单位

    The University of North Carolina at Chapel Hill.;

  • 授予单位 The University of North Carolina at Chapel Hill.;
  • 学科 Information Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 199 p.
  • 总页数 199
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:43:25

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