Towards Large-Scale Probabilistic OBDA

  • Joerg SchoenfischEmail author
  • Heiner Stuckenschmidt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9310)


Ontology-based Data Access has intensively been studied as a very relevant problem in connection with semantic web data. Often it is assumed, that the accessed data behaves like a classical database, i.e. it is known which facts hold for certain. Many Web applications, especially those involving information extraction from text, have to deal with uncertainty about the truth of information. In this paper, we introduce an implementation and a benchmark of such a system on top of relational databases. Furthermore, we propose a novel benchmark for systems handling large probabilistic ontologies. We describe the benchmark design and show its characteristics based on the evaluation of our implementation.


Query Processing Description Logic Query Time Conjunctive Query Query Plan 
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.



The authors want to thank Christian Meilicke for his ongoing support and fruitful discussions about the topic of this paper.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Data- and Web Science GroupUniversity of MannheimMannheimGermany

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