Meta-data for a lot of LOD. Rietveld, L., Beek, W., Hoekstra, R., & Schlobach, S. Semantic Web, 8(6):1067–1080, IOS Press, 1, 2017.
doi  abstract   bibtex   
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.
@article{f79133cc037d4f42a6bd4bd84d446488,
  title     = "Meta-data for a lot of LOD",
  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.",
  author    = "Laurens Rietveld and Wouter Beek and Rinke Hoekstra and Stefan Schlobach",
  year      = "2017",
  month     = "1",
  doi       = "10.3233/SW-170256",
  volume    = "8",
  pages     = "1067--1080",
  journal   = "Semantic Web",
  issn      = "1570-0844",
  publisher = "IOS Press",
  number    = "6",
}

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