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Lessons Learned in Building Linked Data for the American Art Collaborative

机译:建立美国艺术合作组织链接数据的经验教训

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Linked Data has emerged as the preferred method for publishing and sharing cultural heritage data. One of the main challenges for museums is that the defacto standard ontology (CIDOC CRM) is complex and museums lack expertise in semantic web technologies. In this paper we describe the methodology and tools we used to create 5-star Linked Data for 14 American art museums with a team of 12 computer science students and 30 representatives from the museums who mostly lacked expertise in Semantic Web technologies. The project was completed over a period of 18 months and generated 99 mapping files and 9,357 artist links, producing a total of 2,714 R2RML rules and 9.7M triples. More importantly, the project produced a number of open source tools for generating high-quality linked data and resulted in a set of lessons learned that can be applied in future projects.
机译:链接数据已成为发布和共享文化遗产数据的首选方法。博物馆的主要挑战之一是事实上的标准本体(CIDOC CRM)很复杂,博物馆缺乏语义Web技术方面的专业知识。在本文中,我们描述了用于为14个美国艺术博物馆创建5星级链接数据的方法和工具,该团队由12名计算机科学专业的学生和30名来自博物馆的代表组成,他们大多缺乏语义Web技术方面的专业知识。该项目历时18个月,并生成了99个映射文件和9,357个艺术家链接,总共生成了2,714个R2RML规则和970万个三元组。更重要的是,该项目开发了许多用于生成高质量链接数据的开源工具,并产生了一系列可用于未来项目的经验教训。

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