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Parallelization of Conjunctive Query Answering over Ontologies

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Information Management and Big Data (SIMBig 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 795))

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Abstract

Efficient query answering over Description Logic (DL) ontologies with very large datasets is becoming increasingly vital. Recent years have seen the development of various approaches to ABox partitioning to enable parallel processing. Instance checking using the enhanced most specific concept (MSC) method is a particularly promising approach. The applicability of these distributed reasoning methods to typical ontologies has been shown mainly through anecdotal observation. In this paper, we present a parallelizable, enhanced MSC method for the answering of ABox conjunctive queries, using a set of syntactic conditions that permit querying of large practical ontologies in reasonable time, and combining it with pattern matching to answer queries over role assertions. We also present execution time and efficiency of an implementation deployed over computing clusters of various sizes, showing the ability of the method to process instance checking for large scale datasets.

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Notes

  1. 1.

    aws.amazon.com.

  2. 2.

    https://spark.apache.org/.

  3. 3.

    http://www.hermit-reasoner.com.

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    http://thinkaurelius.github.io/titan/.

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Acknowledgements

This work is supported by grant # R44GM097851 from the National Institute of General Medical Sciences (NIGMS), part of the U.S. National Institutes of Health (NIH).

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Authors and Affiliations

  1. INFOTECH Soft, Inc., 1201 Brickell Avenue, Suite 220, Miami, FL, 33131, USA

    E. Patrick Shironoshita & Mansur R. Kabuka

  2. University of Miami, Coral Gables, FL, 33124, USA

    Da Zhang, Mansur R. Kabuka & Jia Xu

Authors
  1. E. Patrick Shironoshita
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  2. Da Zhang
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  3. Mansur R. Kabuka
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  4. Jia Xu
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Corresponding author

Correspondence to E. Patrick Shironoshita .

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Editors and Affiliations

  1. University of Florida, Gainesville, Florida, USA

    Juan Antonio Lossio-Ventura

  2. Universidad del Pacífico, Lima, Peru

    Hugo Alatrista-Salas

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Shironoshita, E.P., Zhang, D., Kabuka, M.R., Xu, J. (2018). Parallelization of Conjunctive Query Answering over Ontologies. In: Lossio-Ventura, J., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2017. Communications in Computer and Information Science, vol 795. Springer, Cham. https://doi.org/10.1007/978-3-319-90596-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-90596-9_1

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