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PG-explorer: Resource Description Framework data exploration with property graphs
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PRE
AI
DOI：10.1016/j.eswa.2022.116789.png)
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Abstract
En 中文
The Resource Description Framework (RDF) has been widely applied to represent and exchange domain infor-mation because of its machine-readable characteristic. With a huge amount of RDF data available, retrieving RDF data is essential, so that many RDF query approaches have been developed. But many traditional approaches generally require users to know RDF model and query language, and this seriously prevents a large number of common non-expert users from obtaining information in RDF datasets. In this paper, we propose an approach that users can explore massive RDF datasets by interactively manipulating property graphs. Our approach provides users with a series of operations in interactively constructing property graphs to describe their query intents. To efficiently explore massive RDF datasets, we convert RDF data into property graphs for storage. This can greatly reduce the size of massive RDF datasets and more importantly the converted property graphs can instruct users to understand the underlying structure of RDF datasets, which is very useful in users' construction of their query property graphs. The constructed query property graphs are finally transformed into expressions with the query language of graph databases. With high-performance graph databases as query engines, we developed an RDF data exploration system - PG-Explorer. Through experiments over real-world datasets, we evaluated the effectiveness and superiority of our approach. The user study demonstrates that the proposed approach simplifies users' exploration of RDF data and can satisfy their exploration needs.
Keywords:
RDF
Property graphs
Graph database
Semantic data
Data exploration
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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