Meta-data for a lot of LOD

Article type: Research Article

Authors: Rietveld, Laurens^{a; *} | Beek, Wouter^a | Hoekstra, Rinke^{a; b} | Schlobach, Stefan^a

Affiliations: [a] Department of Computer Science, VU University Amsterdam, The Netherlands. E-mails: laurens.rietveld@vu.nl, w.g.j.beek@vu.nl, rinke.hoekstra@vu.nl, stefan.schlobach@vu.nl | [b] Leibniz Center for Law, Faculty of Law, University of Amsterdam, The Netherlands. E-mail: hoekstra@uva.nl

Correspondence: [*] Corresponding author. E-mail: laurens.rietveld@vu.nl.

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.

Keywords: Dataset meta-data, linked data, dataset descriptions

DOI: 10.3233/SW-170256

Journal: Semantic Web, vol. 8, no. 6, pp. 1067-1080, 2017