Enhancing scholarly use of digital libraries: A comparative survey and review of bibliographic metadata ontologies

Jacob Jett, Terhi Nurmikko-Fuller, Timothy W. Cole, Kevin R. Page, J. S. Downie
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引用次数: 15

Abstract

The HathiTrust Research Center (HTRC) is engaged in the development of tools that will give scholars the ability to analyze the HathiTrust digital library's 14 million volume corpus. A cornerstone of the HTRC's digital infrastructure is the workset - a kind of scholar-built research collection intended for use with the HTRC's analytics platform. Because more than 66% of the digital corpus is subject to copyright restrictions, scholarly users remain dependent upon the descriptive accounts provided by traditional metadata records in order to identify and gather together bibliographic resources for analysis. This paper compares the MADSRDF/MODSRDF, Bibframe, schema.org, BIBO, and FaBiO ontologies by assessing their suitability for employment by the HTRC to meet scholars' needs. These include distinguishing among multiple versions of the same work; representing the complex historical and physical relationships among those versions; and identifying and providing access to finer grained bibliographic entities, e.g., poems, chapters, sections, and even smaller segments of content.
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加强数字图书馆的学术应用:书目元数据本体的比较调查与回顾
HathiTrust研究中心(HTRC)致力于开发工具,使学者能够分析HathiTrust数字图书馆的1400万卷语料库。HTRC数字基础设施的基石是工作集,这是一种学者构建的研究集合,旨在与HTRC的分析平台一起使用。由于超过66%的数字语料库受到版权限制,学术用户仍然依赖传统元数据记录提供的描述性描述,以便识别和收集书目资源进行分析。本文比较了MADSRDF/MODSRDF、Bibframe、schema.org、BIBO和FaBiO本体,评估了它们是否适合HTRC使用,以满足学者的需求。这包括区分同一作品的多个版本;代表了这些版本之间复杂的历史和物理关系;识别并提供对更细粒度的书目实体的访问,例如诗歌、章节、章节,甚至更小的内容片段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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