A Discovery and Analysis Engine for Semantic Web
| Autor: | Erdogan Dogdu, Semih Yumusak, Elif Uysal, Riza Emre Aras, Andreas Kamilaris, Halife Kodaz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science Interoperability Cloud computing 02 engineering and technology Linked data computer.file_format Reuse World Wide Web Open data Resource (project management) 020204 information systems 0202 electrical engineering electronic engineering information engineering SPARQL 020201 artificial intelligence & image processing business Semantic Web computer |
| Zdroj: | WWW '18 Companion Proceedings of the The Web Conference 2018, 1497-1505 STARTPAGE=1497;ENDPAGE=1505;TITLE=WWW '18 Companion Proceedings of the The Web Conference 2018 WWW (Companion Volume) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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