文章基本信息

标题：J-GLOBAL knowledge
本地全文：下载
作者：木村考宏 ; 川村隆浩 ; 渡邊勝太郎等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2016
卷号：31
期号：2
页码：N-F73_1-12
DOI：10.1527/tjsai.N-F73
出版社：The Japanese Society for Artificial Intelligence
摘要：In order to develop innovative solutions in science and technology, Japan Science and Technology Agency (JST) has built J-GLOBAL knowledge (JGk), which provides papers, patents, researchers' information, technological thesaurus, and scientific data as Linked Data, which have been accumulated by JST since 1957. The total size of all datasets is about 15.7 billion triples, and the JGk website provides a SPARQL endpoint to access part of the datasets. This paper describes several issues on schema design to construct a large-scale Linked Data, and construction methods, especially for linking to external datasets, such as DBpedia Japanese. Finally, we describe performance problems and the future works.
关键词：linked data;LOD;RDF;schema design;science and technology information