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[ANN] WebDataCommons releases 44.2 billion quads Microdata, Embedded JSON-LD, RDFa, and Microformat data originating from 11.9 million websites

From: Anna Primpeli <anna@informatik.uni-mannheim.de>
Date: Mon, 13 Jan 2020 09:51:45 +0100
To: <semantic-web@w3.org>, <public-schemaorg@w3.org>, <public-vocabs@w3.org>
Message-ID: <023b01d5c9ee$af10a240$0d31e6c0$@informatik.uni-mannheim.de>
Hi all,

we are happy to announce the new release of the WebDataCommons Microdata,
JSON-LD, RDFa and Microformat data corpus.

The data has been extracted from the November 2019 version of the Common
Crawl covering 2.4 billion HTML pages which originate from 32 million
websites (pay-level domains).

In summary, we found structured data within 934 million HTML pages out of
the 2.4 billion pages contained in the crawl (37.9%). These pages originate
from 11.9 million different pay-level domains out of the 32 million
pay-level-domains covered by the crawl (37.2%). 

Approximately 6.3 million of these websites use Microdata, 5.1 million
websites use JSON-LD, and 1 million websites make use of RDFa. Microformats
are used by more than 4 million websites within the crawl.

 

Background: 

More and more websites annotate data describing for instance products,
people, organizations, places, events, reviews, and cooking  recipes within
their HTML pages using markup formats such as Microdata, embedded JSON-LD,
RDFa and Microformat. 

The WebDataCommons project extracts all Microdata, JSON-LD, RDFa, and
Microformat data from the Common Crawl web corpus, the largest web corpus
that is available to the public, and provides the extracted data for
download. In addition, we publish statistics about the adoption of the
different markup formats as well as the vocabularies that are used together
with each format. We run yearly extractions since 2012 and we provide the
dataset series as well as the related statistics at:

http://webdatacommons.org/structureddata/

 

Statistics about the November 2019 Release:

Basic statistics about the November 2019 Microdata, JSON-LD, RDFa, and
Microformat data sets as well as the vocabularies that are used together
with each markup format are found at: 

http://webdatacommons.org/structureddata/2019-12/stats/stats.html

 

Markup Format Adoption

The page below provides an overview of the increase in the adoption of the
different markup formats as well as widely used schema.org classes from 2012
to 2019:

http://webdatacommons.org/structureddata/#toc3 

Comparing the statistics from the new 2019 release to the statistics about
the November 2018 release of the data sets

http://webdatacommons.org/structureddata/2018-12/stats/stats.html

we can observe that although the size of the November 2018 crawl is similar
to the one of November 2019, the relative number of PLDs using structured
data increased significantly from 29.3% to 37.2%. However, differences in
the crawling strategies that were used for the two crawls make it difficult
to directly compare absolute numbers. Even though there is clear dominance
of the Microdata and embedded JSON-LD formats in terms of number of PLDs, we
see a different distribution over the amount of extracted entities with the
Microformat hCard dominating. This comes as a result of deeper crawling of
blogging domains, such as blogspot and wordpress, which extensively use the
Microformat hCard to annotate post-related data.

 

Vocabulary Adoption

Concerning the vocabulary adoption, schema.org, the vocabulary recommended
by Google, Microsoft, Yahoo!, and Yandex continues to be the most dominant
in the context of Microdata with 73% of the webmasters using it in
comparison to its predecessor, the data-vocabulary, which is only used by
11% of the websites containing Microdata. In the context of RDFa, the Open
Graph Protocol recommended by Facebook remains the most widely used
vocabulary. 

 

Download 

The overall size of the November 2019 RDFa, Microdata, Embedded JSON-LD and
Microformat data sets is 44.2 billion RDF quads. For download, we split the
data into 9,925 files with a total size of 1.01 TB.

http://webdatacommons.org/structureddata/2019-12/stats/how_to_get_the_data.h
tml

In addition, we have created for over 43 different  <http://schema.org/>
schema.org classes separate files, including all quads extracted from pages,
using a specific schema.org class. 

http://webdatacommons.org/structureddata/2019-12/stats/schema_org_subsets.ht
ml

 

Lots of thanks to: 

+ the Common Crawl project for providing their great web crawl and thus
enabling the WebDataCommons project. 
+ the Any23 project for providing their great library of structured data
parsers. 
+ Amazon Web Services in Education Grant for supporting WebDataCommons. 




General Information about the WebDataCommons Project

The WebDataCommons project extracts structured data from the Common Crawl,
the largest web corpus available to the public, and provides the extracted
data for public download in order to support researchers and companies in
exploiting the wealth of information that is available on the Web. Beside of
the yearly extractions of semantic annotations from webpages, the
WebDataCommons project also provides large hyperlink graphs, the largest
public corpus of web tables, two corpora of product data, as well as a
collection of hypernyms extracted from billions of web pages for public
download. General information about the WebDataCommons project is found at 

http://webdatacommons.org/


Have fun with the new data set. 

Cheers, 


Anna Primpeli and Chris Bizer

 
Received on Monday, 13 January 2020 08:51:58 UTC

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