Matches in Ruben’s data for { <https://ruben.verborgh.org/publications/beek_semantics_2017/#publication> ?p ?o }
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- publication author javier_d_fernandez.
- publication author wouter_beek.
- publication author me.
- publication creator javier_d_fernandez.
- publication creator wouter_beek.
- publication creator me.
- publication about data_science.
- publication about data_access.
- publication about HDT.
- publication about DBpedia.
- publication about Linked_Data.
- publication about RDF.
- publication author javier_d_fernandez.
- publication author wouter_beek.
- publication author me.
- publication coparticipatesWith javier_d_fernandez.
- publication coparticipatesWith wouter_beek.
- publication coparticipatesWith me.
- publication type ScholarlyArticle.
- publication type Article.
- publication type Document.
- publication type Document.
- publication type Document.
- publication type Q386724.
- publication type CreativeWork.
- publication type Work.
- publication P50 javier_d_fernandez.
- publication P50 wouter_beek.
- publication P50 me.
- publication maker javier_d_fernandez.
- publication maker wouter_beek.
- publication maker me.
- publication title "LOD-a-lot: A Single-File Enabler for Data Science".
- publication isPartOf proceedings_of_the_13th_international_conference_on_semantic_systems.
- publication name "LOD-a-lot: A Single-File Enabler for Data Science".
- publication label "LOD-a-lot: A Single-File Enabler for Data Science".
- publication name "LOD-a-lot: A Single-File Enabler for Data Science".
- publication topic data_science.
- publication topic data_access.
- publication topic HDT.
- publication topic DBpedia.
- publication topic Linked_Data.
- publication topic RDF.
- publication subject data_science.
- publication subject data_access.
- publication subject HDT.
- publication subject DBpedia.
- publication subject Linked_Data.
- publication subject RDF.
- publication authorList b0_b2371.
- publication topic data_science.
- publication topic data_access.
- publication topic HDT.
- publication topic DBpedia.
- publication topic Linked_Data.
- publication topic RDF.
- publication abstract "Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base represented in RDF. However, the distributed nature of the information and the lack of a scalable approach to manage and consume such Big Semantic Data makes it difficult and expensive to conduct large-scale studies. As a consequence, most scientists restrict their analyses to one or two datasets (often DBpedia) that contain – at most – hundreds of millions of RDF triples. LOD-a-lot is a dataset that integrates a large portion (over 28 billion triples) of the LOD Cloud into a single ready-to-consume file that can be easily downloaded, shared and queried, locally or online, with a small memory footprint. This paper shows there exists a wide collection of Data Science use cases that can be performed over such a LOD-a-lot file. For these use cases LOD-a-lot significantly reduces the cost and complexity of conducting Data Science.".
- publication datePublished "2017".
- publication mainEntityOfPage beek_semantics_2017.
- publication sameAs publication.
- publication isPrimaryTopicOf beek_semantics_2017.
- publication page beek_semantics_2017.