Derzis: A Path Aware Linked Data Crawler

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2021

Autores

dos Santos, AF (Autor) Outra; José Paulo Leal (Autor) FCUP

Ata de Conferência Internacional

Título: 10th Symposium on Languages, Applications and Technologies, SLATE 2021, July 1-2, 2021, Vila do Conde/Póvoa de Varzim, Portugal.

Páginas: 2:1-2:12

Indexação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00V-AKZ

DOI: 10.4230/oasics.slate.2021.2

Abstract (EN): 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 Derzis1, 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica