Derzis: A Path Aware Linked Data Crawler

Authors André Fernandes dos Santos , José Paulo Leal

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André Fernandes dos Santos
  • CRACS & INESC Tec LA, Faculty of Sciences, University of Porto, Portugal
José Paulo Leal
  • CRACS & INESC Tec LA, Faculty of Sciences, University of Porto, Portugal

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André Fernandes dos Santos and José Paulo Leal. Derzis: A Path Aware Linked Data Crawler. In 10th Symposium on Languages, Applications and Technologies (SLATE 2021). Open Access Series in Informatics (OASIcs), Volume 94, pp. 2:1-2:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Consuming Semantic Web data presents several challenges, from the number of datasets it is composed of, to the (very) large size of some of those datasets and the uncertain availability of querying endpoints. According to its core principles, accessing linked data can be done simply by dereferencing the IRIs of RDF resources. This is a light alternative both for clients and servers when compared to dataset dumps or SPARQL endpoints. The linked data interface does not support complex querying, but using it recursively may suffice to gather information about RDF resources, or to extract the relevant sub-graph which can then be processed and queried using other methods. We present Derzis, an open source semantic web crawler capable of traversing the linked data cloud starting from a set of seed resources. Derzis maintains information about the paths followed while crawling, which allows to define property path-based restrictions to the crawling frontier.

Subject Classification

ACM Subject Classification
  • Information systems → Web crawling
  • Information systems → Structure and multilingual text search
  • Semantic web
  • linked open data
  • RDF
  • crawler


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