Some Thoughts on OWL-Empowered SPARQL Query Optimization

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9989)


The discovery of optimal or close to optimal query plans for SPARQL queries is a difficult and challenging problem for query optimisers of RDF engines. Despite the growing volume of work on optimising SPARQL query answering, using heuristics or data statistics (such as cardinality estimations) there is little effort on the use of OWL constructs for query optimisation. OWL axioms can be the basis for the development of schema-aware optimisation techniques that will allow significant improvements in the performance of RDF query engines when used in tandem with data statistics or other heuristics. The aim of this paper is to show the potential of this idea, by discussing a diverse set of cases that depict how schema information can assist SPARQL query optimisers.


SPARQL Query Optimal Query Plan Query Planning Schema Information Triple Patterns 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partially funded by the EU projects LDBC (FP7 GA No. 317548) and HOBBIT (H2020 GA No. 688227).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Institute of Computer Science-FORTHHeraklionGreece
  2. 2.TU MunichMunichGermany

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