paper

SpEnD: Linked Data SPARQL Endpoints Discovery Using Search Engines

arXiv:1608.02761 · doi:10.1587/transinf.2016DAP0025

Abstract

In this study, a novel metacrawling method is proposed for discovering and monitoring linked data sources on the Web. We implemented the method in a prototype system, named SPARQL Endpoints Discovery (SpEnD). SpEnD starts with a "search keyword" discovery process for finding relevant keywords for the linked data domain and specifically SPARQL endpoints. Then, these search keywords are utilized to find linked data sources via popular search engines (Google, Bing, Yahoo, Yandex). By using this method, most of the currently listed SPARQL endpoints in existing endpoint repositories, as well as a significant number of new SPARQL endpoints, have been discovered. Finally, we have developed a new SPARQL endpoint crawler (SpEC) for crawling and link analysis.

This paper has been withdrawn by the author due to a crucial illustration error in Figure 2, critical numerical errors in Table 5 and Table 8