关联数据发布技术及其实现——以Drupal为例  

The Current Technologies and Tools for Linked Data:A Case of Drupal

作　　者：夏翠娟[1] 刘炜[2] 赵亮[2] 张春景[2] 徐昊[2] 朱雯晶[2] 

机构地区：[1]上海图书馆系统网络中心研究开发部 [2]上海图书馆

出　　处：《中国图书馆学报》2012年第1期49-57,共9页Journal of Library Science in China

基　　金：国家社科基金项目"关联数据的理论和应用研究"(编号:11BTQ041)的研究成果之一

摘　　要：关联数据是一种轻量级的语义网实现技术,其重要价值在于通过RDF数据模型,将网络上的非结构化数据和采用不同标准的结构化数据转换成遵循统一标准的结构化数据,以便机器理解。文章梳理了关联数据的实现方式,目前关联数据的发布模式有:静态发布、批量存储、调用时生成、事后转换(D2R),发布关联数据的工具包括:VoID词表、前端转换工具、OWL及SKOS相关工具、Web services、Web应用框架、CMS及RDFa。并详细介绍了开源CMS平台Drupal。Drupal作为一直关注语义网技术的开源CMS平台,其高度模块化的架构为实现关联数据的发布打下了良好的基础,RDF、SPARQL、SPARQL_Endpoint及其周边模块构成了一套较为成熟的关联数据发布与消费的框架,最后利用该框架实现将"中国历史纪年和公元纪年对照表"发布成关联数据。Linked Data is a lightweight implementation of Semantic Web technology based on RDF data model. With Linked Data, the unstructured data on the web can be transferred to structured data for machine understanding. Common examples of publishing models include static publishing, bulk storage, Real-time generation, and post-conversion （D2R）. Most often used tools to publish linked data are VoID vocabulary, front-end conversion tool, OWL and SKOS tools, Web services, Web application framework, CMS and RDFa. Drupal, a popular open-source Content Management System, is also one of the tools with highly modular architecture most critical to Linked Data implementation. The main modules such as RDF, SPARQL, SPARQL_Endpoint and other surrounding modules compose the architecture of publishing and consuming Linked Data. Finally, building on the architecture of Drupal, ＂Chronological tables of Chinese history and the corresponding western calendar＂ was published into Linked Data. 1 tab. 5 figs. 21 refs.

关 键 词：关联数据 内容管理系统 语义网 DRUPAL 

分 类 号：G254[文化科学—图书馆学] TP391[自动化与计算机技术—计算机应用技术]