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Parallel OWL Reasoning: Merge Classification

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Semantic Technology (JIST 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8388))

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Abstract

Our research is motivated by the ubiquitous availability of multiprocessor computers and the observation that available Web Ontology Language (OWL) reasoners only make use of a single processor. This becomes rather frustrating for users working in ontology development, especially if their ontologies are complex and require long processing times using these OWL reasoners. We present a novel algorithm that uses a divide and conquer strategy for parallelizing OWL TBox classification, a key task in description logic reasoning. We discuss some interesting properties of our algorithm, e.g., its suitability for distributed reasoning, and present an empirical study using a set of benchmark ontologies, where a speedup of up to a factor of 4 has been observed when using 8 workers in parallel.

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Notes

  1. 1.

    This process does not show a full calling order of computing \( A_4 \le A_5 \) for sake of brevity. For instance, \( \top \_merge ( A_7 , A_6 , \le _\alpha , \le _\beta ) \) is not shown.

  2. 2.

    http://github.com/kejia/mc

  3. 3.

    http://jfact.sourceforge.net

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Acknowledgements

We are grateful for Ralf Möller at Hamburg University of Technology in giving us access to their equipment that was used to conduct the presented evaluation.

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Authors and Affiliations

  1. Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada

    Kejia Wu & Volker Haarslev

Authors
  1. Kejia Wu
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  2. Volker Haarslev
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Corresponding author

Correspondence to Kejia Wu .

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Editors and Affiliations

  1. Yonsei University, Seoul, Korea, Republic of (South Korea)

    Wooju Kim

  2. Indiana University, Bloomington, Indiana, USA

    Ying Ding

  3. Seoul National University, Seoul, Korea, Republic of (South Korea)

    Hong-Gee Kim

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Wu, K., Haarslev, V. (2014). Parallel OWL Reasoning: Merge Classification. In: Kim, W., Ding, Y., Kim, HG. (eds) Semantic Technology. JIST 2013. Lecture Notes in Computer Science(), vol 8388. Springer, Cham. https://doi.org/10.1007/978-3-319-06826-8_17

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  • DOI: https://doi.org/10.1007/978-3-319-06826-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06825-1

  • Online ISBN: 978-3-319-06826-8

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