A knowledge and reasoning toolkit for cognitive applications
Mustafa Canim, Cristina Cornelio, et al.
HotWeb 2017
Existing SPARQL-to-SQL translation techniques have limitations that reduce their robustness, efficiency and dependability. These limitations include the generation of inefficient or even incorrect SQL queries, lack of formal background, and poor implementations. Moreover, some of these techniques cannot be used over arbitrary DB schemas due to the lack of support for RDB to RDF mapping languages, such as R2RML. In this paper we present a technique (implemented in the -ontop- system) that tackles all these issues. We propose a formal approach for SPARQL-to-SQL translation that (i) generates efficient SQL by combining optimization techniques from the logic programming and SQL optimization fields; (ii) provides a well-defined specification of the SPARQL semantics used in the translation; and (iii) supports R2RML mappings over general relational schemas. We provide extensive benchmarks using the -ontop- system for Ontology Based Data Access (OBDA) and show that by using these techniques -ontop- is able to outperform well known SPARQL-to-SQL systems, as well as commercial triple stores, by several orders of magnitude.
Mustafa Canim, Cristina Cornelio, et al.
HotWeb 2017
Oktie Hassanzadeh, Michael J. Ward, et al.
OM 2015
Diego Calvanese, Benjamin Cogrel, et al.
Semantic Web
Thien Huu Nguyen, Nicolas Rodolfo Fauceglia, et al.
COLING 2016