Spend Portal: Linked Data Discovery Using Sparql Endpoints
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Ieee
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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.
Description
Cisco; Elsevier; IEEE; IEEE Computer Society; The Mit Press
Uysal, Elif/0000-0002-7258-4872; Yumusak, Semih/0000-0002-8878-4991; Kodaz, Halife/0000-0001-8602-4262
Uysal, Elif/0000-0002-7258-4872; Yumusak, Semih/0000-0002-8878-4991; Kodaz, Halife/0000-0001-8602-4262
Keywords
Sparql Endpoints, Linked Data, Search Engines, Sparql Endpoints, Linked Data, Search Engines
Fields of Science
05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0509 other social sciences
Citation
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
N/A
Source
IEEE International Conference on Big Data (IEEE Big Data) -- DEC 11-14, 2017 -- Boston, MA
Volume
2018-January
Issue
Start Page
2200
End Page
2202
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Scopus : 0
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