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Benchmarking Faceted Browsing Capabilities of Triplestores

Published: 11 September 2017 Publication History

Abstract

The increasing availability of large amounts of linked data creates a need for software that allows for its efficient exploration. Systems enabling faceted browsing constitute a user-friendly solution that need to combine suitable choices for front and back end. Since a generic solution must be adjustable with respect to the dataset, the underlying ontology and the knowledge graph characteristics raise several challenges and heavily influence the browsing experience. As a consequence, an understanding of these challenges becomes an important matter of study. We present a benchmark on faceted browsing of triple stores, which allows systems to test their performance on specific choke points on the back end. Further, we address additional issues in faceted browsing that may be caused by problematic modelling choices within the underlying ontology.

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Cited By

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  • (2019)Generating public transport data based on population distributions for RDF benchmarkingSemantic Web10.3233/SW-18031910:2(305-328)Online publication date: 1-Jan-2019
  • (2018)GraFa: Scalable Faceted Browsing for RDF GraphsThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_18(301-317)Online publication date: 18-Sep-2018
  • (2018)MOCHA2018: The Mighty Storage Challenge at ESWC 2018Semantic Web Challenges10.1007/978-3-030-00072-1_1(3-16)Online publication date: 17-Oct-2018

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  1. Benchmarking Faceted Browsing Capabilities of Triplestores

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    cover image ACM Other conferences
    Semantics2017: Proceedings of the 13th International Conference on Semantic Systems
    September 2017
    202 pages
    ISBN:9781450352963
    DOI:10.1145/3132218
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • St. Pölten University: St. Pölten University of Applied Sciences, Austria
    • Wolters Kluwer: Wolters Kluwer, Germany
    • Vrije Universeit Amsterdam: Vrije Universeit Amsterdam
    • Semantic Web Company: Semantic Web Company
    • Uinv. Leipzig: Universität Leipzig

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 11 September 2017

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    Author Tags

    1. Benchmarking
    2. Choke Points
    3. Faceted Browsing
    4. Linked Data

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    Overall Acceptance Rate 40 of 182 submissions, 22%

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    Cited By

    View all
    • (2019)Generating public transport data based on population distributions for RDF benchmarkingSemantic Web10.3233/SW-18031910:2(305-328)Online publication date: 1-Jan-2019
    • (2018)GraFa: Scalable Faceted Browsing for RDF GraphsThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_18(301-317)Online publication date: 18-Sep-2018
    • (2018)MOCHA2018: The Mighty Storage Challenge at ESWC 2018Semantic Web Challenges10.1007/978-3-030-00072-1_1(3-16)Online publication date: 17-Oct-2018

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