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Alignment-Based Querying of Linked Open Data

  • Conference paper
Book cover On the Move to Meaningful Internet Systems: OTM 2012 (OTM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7566))

Abstract

The Linked Open Data (LOD) cloud is rapidly becoming the largest interconnected source of structured data on diverse domains.The potential of the LOD cloud is enormous, ranging from solving challenging AI issues such as open domain question answering to automated knowledge discovery. However, due to an inherent distributed nature of LOD and a growing number of ontologies and vocabularies used in LOD datasets, querying over multiple datasets and retrieving LOD data remains a challenging task. In this paper, we propose a novel approach to querying linked data by using alignments for processing queries whose constituent data come from heterogeneous sources. We also report on our Alignment based Linked Open Data Querying System (ALOQUS) and present the architecture and associated methods. Using the state of the art alignment system BLOOMS, ALOQUS automatically maps concepts in users’ SPARQL queries, written in terms of a conceptual upper ontology or domain specific ontology, to different LOD concepts and datasets. It then creates a query plan, sends sub-queries to the different endpoints, crawls for co-referent URIs, merges the results and presents them to the user. We also compare the existing querying systems and demonstrate the added capabilities that the alignment based approach can provide for querying the Linked data.

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Author information

Authors and Affiliations

  1. Kno.e.sis Center, Wright State University, Dayton, OH, U.S.A.

    Amit Krishna Joshi, Prateek Jain, Pascal Hitzler & Amit P. Sheth

  2. Accenture Technology Labs San Jose, CA, U.S.A.

    Peter Z. Yeh & Kunal Verma

  3. OntoText, Bulgaria

    Mariana Damova

Authors
  1. Amit Krishna Joshi
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  2. Prateek Jain
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  3. Pascal Hitzler
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  4. Peter Z. Yeh
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  5. Kunal Verma
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  6. Amit P. Sheth
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  7. Mariana Damova
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Semantic Technology and Application Research Laboratory (STARLab), Vrije Universiteit Brussel, Building G-10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. Research Centre for Automatic Control, School of Engineering in Information Technology, Campus scientifique, University of Lorraine, CNRS, BP 70239, 54506, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. La Trobe University, Melbourne, VIC, Australia

    Tharam Dillon

  4. Faculty of Computer Science, University of Vienna, 1010, Vienna, Austria

    Stefanie Rinderle-Ma

  5. Institute of Databases and Information Systems, Ulm University, Germany

    Peter Dadam

  6. School of Information Technology and Electrical Engineering, University of Queensland, QLD 4072, Brisbane, Australia

    Xiaofang Zhou

  7. HP Labs, Bristol, UK

    Siani Pearson

  8. Johannes Kepler University, Linz, Austria

    Alois Ferscha

  9. Università di Modena e Reggio Emilia, Modena, Italy

    Sonia Bergamaschi

  10. ADVIS Lab, Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA

    Isabel F. Cruz

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© 2012 Springer-Verlag Berlin Heidelberg

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Joshi, A.K. et al. (2012). Alignment-Based Querying of Linked Open Data. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2012. OTM 2012. Lecture Notes in Computer Science, vol 7566. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33615-7_25

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  • DOI: https://doi.org/10.1007/978-3-642-33615-7_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33614-0

  • Online ISBN: 978-3-642-33615-7

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