Spend Portal: Linked Data Discovery Using Sparql Endpoints
| dc.contributor.author | Yumusak, Semih | |
| dc.contributor.author | Aras, Riza Emre | |
| dc.contributor.author | Uysal, Elif | |
| dc.contributor.author | Dogdu, Erdogan | |
| dc.contributor.author | Kodaz, Halife | |
| dc.contributor.author | Oztoprak, Kasim | |
| dc.date.accessioned | 2025-05-13T13:44:39Z | |
| dc.date.available | 2025-05-13T13:44:39Z | |
| dc.date.issued | 2017 | |
| dc.description | Cisco; Elsevier; IEEE; IEEE Computer Society; The Mit Press | en_US |
| dc.description | Uysal, Elif/0000-0002-7258-4872; Yumusak, Semih/0000-0002-8878-4991; Kodaz, Halife/0000-0001-8602-4262 | en_US |
| 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.doi | 10.1109/BigData.2017.8258169 | |
| dc.identifier.isbn | 9781538627150 | |
| dc.identifier.issn | 2639-1589 | |
| dc.identifier.scopus | 2-s2.0-85047830586 | |
| dc.identifier.uri | https://doi.org/10.1109/BigData.2017.8258169 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12416/9971 | |
| dc.language.iso | en | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | IEEE International Conference on Big Data (IEEE Big Data) -- DEC 11-14, 2017 -- Boston, MA | en_US |
| dc.relation.ispartofseries | IEEE International Conference on Big Data | |
| 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 | en_US |
| dc.type | Conference Object | en_US |
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| gdc.author.id | Uysal, Elif/0000-0002-7258-4872 | |
| gdc.author.id | Yumusak, Semih/0000-0002-8878-4991 | |
| gdc.author.id | Kodaz, Halife/0000-0001-8602-4262 | |
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| gdc.author.wosid | Uysal, Elif/Aaf-7958-2019 | |
| gdc.author.wosid | Yumusak, Semih/Y-1134-2019 | |
| gdc.author.wosid | Kodaz, Halife/Abg-2951-2020 | |
| gdc.author.wosid | Kodaz, Halife/Q-2141-2015 | |
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| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Yumusak, Semih; Aras, Riza Emre; Uysal, Elif; Oztoprak, Kasim] KTO Karatay Univ, Karatay, Konya, Turkey; [Dogdu, Erdogan] Cankaya Univ, Ankara, Turkey; [Kodaz, Halife] Selcuk Univ, Selcuklu, Konya, Turkey | en_US |
| gdc.description.endpage | 2202 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | N/A | |
| gdc.description.startpage | 2200 | en_US |
| gdc.description.volume | 2018-January | en_US |
| gdc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
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| gdc.oaire.keywords | Sparql Endpoints | |
| gdc.oaire.keywords | Linked Data | |
| gdc.oaire.keywords | Search Engines | |
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| gdc.virtual.author | Doğdu, Erdoğan | |
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