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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

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Publicly Funded

No
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Average
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Average
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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

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

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N/A
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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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