Advertisement

Linked Open Data Statistics: Collection and Exploitation

  • Ivan Ermilov
  • Michael Martin
  • Jens Lehmann
  • Sören Auer
Part of the Communications in Computer and Information Science book series (CCIS, volume 394)

Abstract

This demo presents LODStats, a web application for collection and exploration of the Linked Open Data statistics. LODStats consists of two parts: the core collects statistics about the LOD cloud and publishes it on the LODStats web portal, a front-end for exploration of dataset statistics. Statistics are published both in human-readable and machine-readable formats, thus allowing consumption of the data through web front-end by the users as well as through an API by services and applications. As an example for the latter we showcase how to visualize the statistical data with the CubeViz application.

Keywords

Resource Description Framework Link Open Data Data Catalog Resource Description Framework Data SPARQL Endpoint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alexander, K., Cyganiak, R., Hausenblas, M., Zhao, J.: Describing linked datasets. In: 2nd WS on Linked Data on the Web, Madrid, Spain (April 2009)Google Scholar
  2. 2.
    Beckett, D.: Redland librdf language bindings, http://librdf.org/bindings/
  3. 3.
    Beckett, D.: The design and implementation of the redland rdf application framework. In: Proc. of 10th Int. World Wide Web Conf, pp. 449–456. ACM (2001)Google Scholar
  4. 4.
    Ermilov, I., Demter, J., Martin, M., Lehmann, J., Auer, S.: LODStats – Large Scale Dataset Analytics for Linked Open Data. Under Review in ISWC (2013)Google Scholar
  5. 5.
    Herman, I., Fernández, S., Tejo, C.: SPARQL endpoint interface to python, http://sparql-wrapper.sourceforge.net/
  6. 6.
    Stadler, C., Unbehauen, J., Lehmann, J., Auer, S.: Connecting crowd-sourced spatial information to the data web with sparqlify (2013), http://sparqlify.org/downloads/documents/2013-Sparqlify-Technical-Report.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ivan Ermilov
    • 1
  • Michael Martin
    • 1
  • Jens Lehmann
    • 1
  • Sören Auer
    • 2
  1. 1.AKSW/BISUniversität LeipzigGermany
  2. 2.CS/EISUniversität BonnGermany

Personalised recommendations