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Towards Large-Scale Probabilistic OBDA

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Book cover Scalable Uncertainty Management (SUM 2015)

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Abstract

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.

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Notes

  1. 1.

    In particular, axioms of the form \(A \sqsubseteq \exists R\) cannot be represented in ProbLog.

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Acknowledgement

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

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Authors and Affiliations

  1. Data- and Web Science Group, University of Mannheim, B6 26, 68159, Mannheim, Germany

    Joerg Schoenfisch & Heiner Stuckenschmidt

Authors
  1. Joerg Schoenfisch
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  2. Heiner Stuckenschmidt
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Corresponding author

Correspondence to Joerg Schoenfisch .

Editor information

Editors and Affiliations

  1. Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Hagen, Germany

    Christoph Beierle

  2. California Polytechnic State University, SAN LUIS OBISPO, USA

    Alex Dekhtyar

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Schoenfisch, J., Stuckenschmidt, H. (2015). Towards Large-Scale Probabilistic OBDA. In: Beierle, C., Dekhtyar, A. (eds) Scalable Uncertainty Management. SUM 2015. Lecture Notes in Computer Science(), vol 9310. Springer, Cham. https://doi.org/10.1007/978-3-319-23540-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-23540-0_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23539-4

  • Online ISBN: 978-3-319-23540-0

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