Visualizing How-Provenance Explanations for SPARQL Queries

COMPANION OF THE WORLD WIDE WEB CONFERENCE, WWW 2023(2023)

引用 0|浏览18
暂无评分
摘要
Knowledge graphs (KGs) are vast collections of machine-readable information, usually modeled in RDF and queried with SPARQL. KGs have opened the door to a plethora of applications such as Web search or smart assistants that query and process the knowledge contained in those KGs. An important, but often disregarded, aspect of querying KGs is query provenance: explanations of the data sources and transformations that made a query result possible. In this article we demonstrate, through a Web application, the capabilities of SPARQLprov, an engine-agnostic method that annotates query results with how-provenance annotations. To this end, SPARQLprov resorts to query rewriting techniques, which make it applicable to already deployed SPARQL endpoints. We describe the principles behind SPARQLprov and discuss perspectives on visualizing how-provenance explanations for SPARQL queries.
更多
查看译文
关键词
SPARQL,RDF,how-provenance,query provenance
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要