Meta-data for a lot of LOD

Laurens Rietveld*, Wouter Beek, Rinke Hoekstra, Stefan Schlobach

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This paper introduces the LOD Laundromat meta-dataset, a continuously updated RDF meta-dataset that describes the documents crawled, cleaned and (re)published by the LOD Laundromat. This meta-dataset of over 110 million triples contains structural information for more than 650,000 documents (and growing). Dataset meta-data is often not provided alongside published data, it is incomplete or it is incomparable given the way they were generated. The LOD Laundromat meta-dataset provides a wide range of structural dataset properties, such as the number of triples in LOD Laundromat documents, the average degree in documents, and the distinct number of Blank Nodes, Literals and IRIs. This makes it a particularly useful dataset for data comparison and analytics, as well as for the global study of the Web of Data. This paper presents the dataset, its requirements, and its impact.
Original languageEnglish
Pages (from-to)1067-1080
Number of pages14
JournalSemantic Web
Volume8
Issue number6
DOIs
Publication statusPublished - 1 Jan 2017

Fingerprint Dive into the research topics of 'Meta-data for a lot of LOD'. Together they form a unique fingerprint.

Cite this