A Discovery and Analysis Engine for Semantic Web

Semih Yumusak, Andreas Kamilaris, Erdogan Dogdu, Halife Kodaz, Elif Uysal, Riza Emre Aras

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)
    63 Downloads (Pure)

    Abstract

    The Semantic Web promotes common data formats and exchange protocols on the web towards better interoperability among systems and machines. Although Semantic Web technologies are being used to semantically annotate data and resources for easier reuse, the ad hoc discovery of these data sources remains an open issue. Popular Semantic Web endpoint repositories such as SPARQLES, Linking Open Data Project (LOD Cloud), and LODStats do not include recently published datasets and are not updated frequently by the publishers. Hence, there is a need for a web-based dynamic search engine that discovers these endpoints and datasets at frequent intervals. To address this need, a novel web meta-crawling method is proposed for discovering Linked Data sources on the Web. We implemented the method in a prototype system named SPARQL Endpoints Discovery (SpEnD). In this paper, we describe the design and implementation of SpEnD, together with an analysis and evaluation of its operation, in comparison to the aforementioned static endpoint repositories in terms of time performance, availability, and size. Findings indicate that SpEnD outperforms existing Linked Data resource discovery methods.
    Original languageEnglish
    Title of host publicationWWW '18 Companion Proceedings of the The Web Conference 2018
    Place of PublicationNew York, New York, USA
    Pages1497-1505
    Number of pages9
    ISBN (Electronic)978-1-4503-5640-4
    DOIs
    Publication statusPublished - 24 Apr 2018
    EventInternational Workshop on Profiling and Searching Data on the Web Workshop 2018 - Lyon, France
    Duration: 24 Apr 201824 Apr 2018
    https://profiles-datasearch.github.io/2018/

    Conference

    ConferenceInternational Workshop on Profiling and Searching Data on the Web Workshop 2018
    CountryFrance
    CityLyon
    Period24/04/1824/04/18
    OtherCo-located with The Web Conference '2018
    Internet address

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  • Cite this

    Yumusak, S., Kamilaris, A., Dogdu, E., Kodaz, H., Uysal, E., & Aras, R. E. (2018). A Discovery and Analysis Engine for Semantic Web. In WWW '18 Companion Proceedings of the The Web Conference 2018 (pp. 1497-1505). New York, New York, USA. https://doi.org/10.1145/3184558.3191599