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SpEnD portal: linked data discovery using SPARQL endpoints

dc.contributor.author Yumuşak, Semih
dc.contributor.author Aras, Rıza Emre
dc.contributor.author Uysal, Elif
dc.contributor.author Doğdu, Erdoğan
dc.contributor.author Kodaz, Halife
dc.contributor.author Öztoprak, Kasım
dc.contributor.other 06.01. Bilgisayar Mühendisliği
dc.contributor.other 06. Mühendislik Fakültesi
dc.contributor.other 01. Çankaya Üniversitesi
dc.date.accessioned 2020-03-20T06:30:14Z
dc.date.available 2020-03-20T06:30:14Z
dc.date.issued 2017
dc.description.abstract We present the project SpEnD, a complete SPARQL endpoint discovery and analysis portal. In a previous study, the SPARQL endpoint discovery and analysis steps of the SpEnD system were explained in detail. In the SpEnD portal, the SPARQL endpoints are extracted from the web by using web crawling techniques, monitored and analyzed by live querying the endpoints systematically. After many sustainability improvements in the SpEnD project, the SpEnD system is now online as a portal. SpEnD portal currently serves 1487 SPARQL endpoints, out of which 911 endpoints are uniquely found by SpEnD only when compared to the other existing SPARQL endpoint repositories. In this portal, the analytic results and the content information are shared for every SPARQL endpoint. The endpoints stored in the repository are monitored and updated continuously. en_US
dc.identifier.citation Yumusak, Semih; Aras, Rıza Emre; Uysal, Elif, "SpEnD portal: linked data discovery using SPARQL endpoints", 2017 IEEE International Conference On Big Data (Big Data), pp.200-2202, (2017). en_US
dc.identifier.isbn 9781538627150
dc.identifier.issn 2639-1589
dc.identifier.uri https://hdl.handle.net/20.500.12416/2701
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartof 2017 IEEE International Conference On Big Data (Big Data) en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Sparql Endpoints en_US
dc.subject Linked Data en_US
dc.subject Search Engines en_US
dc.title SpEnD portal: linked data discovery using SPARQL endpoints tr_TR
dc.title SpEnD portal: linked data discovery using SPARQL endpoints en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Doğdu, Erdoğan
gdc.description.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği en_US
gdc.description.endpage 2202 en_US
gdc.description.startpage 2200 en_US
relation.isAuthorOfPublication 0d453674-7998-4d57-a06c-03e13bb1e314
relation.isAuthorOfPublication.latestForDiscovery 0d453674-7998-4d57-a06c-03e13bb1e314
relation.isOrgUnitOfPublication 12489df3-847d-4936-8339-f3d38607992f
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relation.isOrgUnitOfPublication.latestForDiscovery 12489df3-847d-4936-8339-f3d38607992f

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