QED: Out-of-the-Box Datasets for SPARQL Query Evaluation

被引：3
|
作者：
Thost, Veronika [1 ]
Dolby, Julian [2 ]
机构：
[1] IBM Res, MIT IBM Watson AI Lab, Cambridge, MA 02142 USA
[2] IBM Res, Yorktown Hts, NY USA
来源：
SEMANTIC WEB, ESWC 2019 | 2019年 / 11503卷
关键词：
SPARQL datasets; Compliance tests; Benchmark;
D O I：
10.1007/978-3-030-21348-0_32
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present SPARQL QED, a system generating out-of-the-box datasets for SPARQL queries over linked data. QED distinguishes the queries according to the different SPARQL features and creates, for each query, a small but exhaustive dataset comprising linked data and the query answers over this data. These datasets can support the development of applications based on SPARQL query answering in various ways. For instance, they may serve as SPARQL compliance tests or can be used for learning in query-by-example systems. We ensure that the created datasets are diverse and cover various practical use cases and, of course, that the sets of answers included are the correct ones. Example tests generated based on queries and data from DBpedia have shown bugs in Jena and Virtuoso.
引用
收藏
页码：491 / 506
页数：16
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