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SHARQL: Shape Analysis of Recursive SPARQL Queries
Author(s) -
Angela Bonifati,
Wim Martens,
Thomas Timm
Publication year - 2020
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-6735-6
DOI - 10.1145/3318464.3384684
Subject(s) - sparql , computer science , rendering (computer graphics) , information retrieval , property (philosophy) , rdf , named graph , database , data mining , artificial intelligence , semantic web , epistemology , philosophy
We showcase SHARQL, a system that allows to navigate SPARQL query logs, can inspect complex queries by visualizing their shape, and can serve as a back-end to flexibly produce statistics about the logs. Even though SPARQL query logs are increasingly available and have become public recently, their navigation and analysis is hampered by the lack of appropriate tools. SPARQL queries are sometimes hard to understand and their inherent properties, such as their shape, their hypertree properties, and their property paths are even more difficult to be identified and properly rendered. In SHARQL, we show how the analysis and exploration of several hundred million queries is possible. We offer edge rendering which works with complex hyperedges, regular edges, and property paths of SPARQL queries. The underlying database stores more than one hundred attributes per query and is therefore extremely flexible for exploring the query logs and as a back-end to compute and display analytical properties of the entire logs or parts thereof.

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