ANN: - Offering 3.2 billion quads current RDFa, Microdata and Miroformat data extracted from 65.4 million websites

Hi all,


we are happy to announce, a joined project of Freie
Universität Berlin and the Karlsruhe Institute of Technology to extract all
Microformat, Microdata and RDFa data from the Common Crawl web corpus, the
largest and most up-to-data web corpus that is currently available to the
public. provides the extracted data for download in the form of
RDF-quads. In addition, we produce basic statistics about the extracted


Up till now, we have extracted data from two Common Crawl web corpora: One
corpus consisting of 2.5 billion HTML pages dating from 2009/2010 and a
second corpus consisting of 1.4 billion HTML pages dating from February


The 2009/2010 extraction resulted in 5.1 billion RDF quads which describe
1.5 billion entities and originate from 19.1 million websites.

The February 2012 extraction resulted in 3.2 billion RDF quads which
describe 1.2 billion entities and originate from 65.4 million websites.


More detailed statistics about the distribution of formats, entities and
websites serving structured data, as well as growth between 2009/2010 and
2012 is provided on the project website:


It is interesting to see form the statistics that the RDFa and Microdata
deployment has grown a lot over the last years, but that Microformat data
still makes up the majority of the structured data that is embedded into
HTML pages (when looking at the amount of quads as well as the amount of


We hope that Web Data Commons will be useful to the community by:

+ easing the access to Mircodata, Mircoformat and RDFa data, as you do not
need to crawl the Web yourself anymore in order to get access to a fair
portion of the structured data that is currently available on the Web.

+ laying the foundation for the more detailed analysis of the deployment of
the different technologies.

+ providing seed URLs for focused Web crawls that dig deeper into the
websites that offer a specific type of data.


Web Data Commons is a joint effort of Christian Bizer and Hannes Mühleisen
(Web-based Systems Group at Freie Universität Berlin) and Andreas Harth and
Steffen Stadtmüller (Institute AIFB at the Karlsruhe Institute of


Lots of thanks to:

+ the Common Crawl project for providing their great web crawl and thus
enabling the Web Data Commons project.

+ the Any23 project for providing their great library of structured data

+ the PlanetData and the LOD2 EU research projects which supported the


For the future, we plan to update the extracted datasets on a regular basis
as new Common Crawl corpora are becoming available. We also plan to provide
the extracted data in the in the form of CSV-tables for common entity types
(e.g. product, organization, location, ...) in order to make it easier to
mine the data.




Christian Bizer, Hannes Mühleisen, Andreas Harth and Steffen Stadtmüller




Prof. Dr. Christian Bizer

Web-based Systems Group

Freie Universität Berlin

+49 30 838 55509


Received on Thursday, 22 March 2012 20:13:27 UTC