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Towards the creation of integrated authority files in the domain of science and technology: an Italian use case

机译:致力于创建科学技术领域的集成授权文件:一个意大利用例

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摘要

Over the years, different organizations have developed and shared a number of authority files with normalized personal names (e.g. Virtual International Authority File - VIAF),inviting others to use these sources as a ?common language? and contributing to improved interoperability among resources/systems. Nevertheless, numerous data providers continue to create and to take advantage of locally developed authority lists mined from the resources managed in local repositories and not aligned with external trustworthy sources. These authority lists often remain locked in local databases inhibiting sharing, re-use and interoperability of their data. This paper aims to present a use case on the creation of integrated and dynamic local authority files referring to the personal names of important Italian scientists and academics to be used within a federate Digital Library about Science and Technology. Terminology extraction techniques have been applied to a corpus of 400 documents in the National Centre of Electronic Calculationu27s archive. This resulted in an authority list of 700 personal names that was further aligned with VIAF and other authorities, such as Library of Congress Classification, via a manual mapping process, thus ensuring its interoperability and retrieval of bibliographic data and topics for each name. Future work will include the creation of CNUCE subject headings based on the list of keywords extracted from the CNUCE corpus and mapping to the Nuovo Soggettario and to LCSH.
机译:多年来,不同的组织已经开发并共享了许多具有规范化个人名称的授权文件(例如,虚拟国际授权文件-VIAF),邀请其他组织将这些来源用作“通用语言”?并有助于改善资源/系统之间的互操作性。尽管如此,许多数据提供者仍在继续创建并利用从本地存储库中管理的资源中挖掘出来的,与外部可信赖来源不符的本地开发权限列表。这些权限列表通常保持在本地数据库中,从而阻止了其数据的共享,重复使用和互操作性。本文旨在提出一个使用案例,说明创建集成的动态地方当局文件的过程,这些文件引用重要的意大利科学家和学者的个人名称,以供联邦科学技术数字图书馆使用。术语提取技术已应用于国家电子计算中心档案中的400个文档的语料库。这产生了700个个人姓名的权限列表,该列表通过手动映射过程进一步与VIAF和其他权限(例如国会图书馆分类)保持一致,从而确保了其互操作性以及检索每个姓名的书目数据和主题。未来的工作将包括基于从CNUCE语料库中提取的关键字列表创建CNUCE主题标题,并将其映射到Nuovo Soggettario和LCSH。

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