RDA与关联数据

RDA and Linked Data

作为新一代编目规则,RDA在应用模型、书目记录的结构、术语和编目规则等方面与其前一个版本AACR2相比,有很大变化。RDA首先区分书目对象相关实体,再确定各类实体所需描述的属性,以及各类实体、属性、取值等要素之间的关系,并对各类规范取值词表进行规定。这种基于概念模型的描述特别适合利用语义网技术来实现。关联数据是语义网的一个简化方案,以RDA编目的书目数据用关联数据发布,能使RDA的潜力发挥到极致。不久的将来,具有语义的书目数据在互联网上将不断增多,书目数据的普遍关联将指日可待。

RDA is the upgraded version of AACR2. The most significant difference between RDA and AACR2 is the record structure and the terminology. RDA is a content standard with the main purpose of describing the properties and relations among the entities in the intellectual and artistic creations. Linked Data is a simple resolution of Semantic Web which is using the same RDF data model and RDF-based encoding schema to model the real world. The implementation of the Linked Data is based on the existing web technologies such as HTTP and URI. The best practices of Linked Data which were introduced by Tim Bemers-Lee have become known as the four Linked Data principles. The DCMI/RDA Workgroup has set up an all-in-one registry to host RDA vocabularies and schema to support dereference as the Linked Data. This would benefit both readers and librarians at the most and bring the data value to its full potential. 3 figs. 3 tabs. 16 refs.