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Produce and Consume Linked Data
with Drupal!
Stéphane Corlosquet, Renaud Delbru, Tim Clark,
Axel Polleres and Stefan Decker
ISWC 2009
scorlosquet@gmail.com
DERI NUI Galway, MGH
October 27th, 2009
Chapter 1
Copyright 2009 Digital Enterprise Research Institute. All rights reserved.

Loads of Data on the Web in CMS...
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Some Motivations...
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 Status of the current web
 Data contained in millions of documents
 Disparate platforms and systems
 Wide range of topics (personal blogs, news, etc.)
 Various types of resources (text, pictures, video, etc.)
 Note: Lots of Structured data in Content Management Systems
 Problem
 Not possible to reuse this data outside the CMS (except RSS)
 Not available as unified machine readable format
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So, here’s our idea of CMS:
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PROJECT BLOGS
DBLP
SPARQL
endpoint
SPARQL REMOTE DRUPAL SITE
endpoint
SELECT ?name ?title Tim
WHERE { .........
?person foaf:made ?pub.
?person rdfs:label ?name.
?pub dc:title ?title. SPARQL
FILTER regex(?title, "knowledge", "i") endpoint
}
Figure 3.5: Extended example in a typical Linked Data eco-system.
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Approach
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 Our Goal
 Integrate "any" CMS site to the Web of Data
A challenging task
 Little incentive for users to annotate their data manually
 Site owners do not have the resources to convert their data to RDF
 Per-siteschema: each site is different and its structure cannot be
predefined
 Solutions
 Expose the CMS site structure in a unified format AUTOMATICALLY!
 Use Semantic Web standards (RDFa, SPARQL)
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Approach
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 Implementation in Drupal
 Why? One of the most popular CMS out there
 Modules to take the burden off the site users
 What our modules allow:
 1. Automatic site vocabulary generation
 2. Mapping Content Models to existing ontologies
 3. Data endpoint for SPARQL querying
 4. Lazy loading of external data (data import)
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Pre-Existing work
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 “Semantic Content Management Systems”
 Ontology-based CMS:
– Semantic community Web portals (2000)
– OntoWebber: Model-Driven Ontology-Based Web Site Management
(2001)
 Our approach is reverse: from existing CMS structure to
ontologies
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The Drupal CMS
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 Drupal*
 Easy to use
 Large community
 Popularon the Web
 Hundreds of thousands of sites
 Modular design
 Drupal site workflow
 Site administrator: set up the site and install modules they
like/need
 Site editors: create the content of the site following the
schema defined by the site administrator
* http://drupal.org/
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Drupal: Content Construction Kit
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 Content Construction Kit (CCK) module
 GUI for extending the internal schema of a Drupal site
 Used on many Drupal sites
 Can build new types of pages, known as content types
 Can create fields for each content types. Fields can be of
various types: plain text fields, dates, email addresses, file
uploads, reference to other pages
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Drupal: Content Construction Kit
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 Demo use case: project blogs site*
 Community site
PROJECT BLOGS
 Various content:
– People DBLP
– Organizations
– Projects SPARQL
endpoint
– Blogs SPARQL REMOTE DRUPAL SITE
endpoint
SELECT ?name ?title Tim
WHERE { .........
?person foaf:made ?pub.
?person rdfs:label ?name.
?pub dc:title ?title. SPARQL
FILTER regex(?title, "knowledge", "i") endpoint
}
Figure 3.5: Extended example in a typical Linked Data eco-system.
one for bridging the DBLP SPARQL endpoint to the project blogs website, and a sec-
ond for bridging the Science Collaboration Framework website. When visiting Tim’s
profile page, the relevant publication information will be fetched from both DBLP and
* http://drupal.deri.ie/projectblogs/ SCF websites, and either new nodes will be created on the site or older ones will be
updated if necessary.
10 3.4 Neologism: Easy RDFS vocabulary publishing
Neologism11 is a web-based vocabulary editor and publishing platform designed to

Drupal: Content Construction Kit
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 CCK User Interface
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Drupal: the Person contentConstruction KitThis form
The fields form for
Content type is displayed on Figure 2.11.
llows to easily reorder the fields by a “drag and drop” technique, add new fields,
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emove existing fields or access the configuration form for a field.
 CCK User Interface
Figure 2.12: Defining constraints on the gender field in Drupal’s CCK.
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Figures 2.9, 2.10, 2.11 and 2.12 show the typical look and feelKit
Drupal: Content Construction of a Drupal page and
administrative interface for the Person content type, without our extensions installed.
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This content type offers fields such as name, homepage, email, colleagues, blog url,
current project,User Interface
 CCK past projects, publications, contributions.
Figure 2.9: User profile page built with Drupal’s CCK.
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An example of node (page) of the type Person is depicted on Figure 2.9 where all

What do we add?
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1, 2
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1. Site Vocabulary
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 Automatic site vocabulary in RDFS/OWL from CCK
 Describes the content types and fields
 Content type <=> RDF class
 Field
<=> RDF property
 RDFa output on site
 http://siteurl/ns#
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1. Site Vocabulary
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 Automatic site vocabulary in RDFS/OWL
 Field constraints
 Example with cardinalities:
– the name of a Person is required
– max. 5 projects per person
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Search examples are shown in Figure 3.2. Details on improving the ran
2.search algorithm can be found in [45].
Mapping Content Models to existing ontologies
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3.2.3 Mapping process
 Mapping Content Models to Existing Ontologies
The terms suggested by both of the import service and the ontology search
 Import of any vocabulary published online
be mapped to each content type and their fields. For mapping content ty
choose among the classes of service
 External ontology search
the imported ontologies and for fields, one
 Local terms are subclasses/subproperties of public terms
among the properties. The local terms will be linked with rdfs:subCl
rdfs:subPropertyOf statements, e.g.
site:Person rdfs:subClassOf foaf:Person to the mapped
site vocabulary; wherever a mapping is definined, extra triples using the m
are exposed in the RDFa of the page.
 Ensure “safe” vocabulary re-use:
– only subclassing/subproperty avoids “redefinition” properties. E.g., ass
Additionally, we allow inverse reuse of existing
administrator imports amight introduce inconsistencies a relation between C
– adding cardinalities vocabulary ex: that defines still, possible to
gions and goods user interface
avoid in the that this region/coutry produces via the property ex:prod
user interface also allows to relate fields to the inverse of imported proper
stance, the origin field could be related to ex:produces in such an inve
resulting in
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site:origin rdfs:subPropertyOf

2. Mapping Content Models to existing ontologies
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 RDF mappings page
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Figure 3.2: RDF mappings management through the Dru

2. Mapping Content Models to existing ontologies
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 RDF mappings page
agement through the Drupal interface: RDF class map-
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What do we add?
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1, 2
3
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3. Data endpoint for complex querying
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 Local RDF data exposed in a SPARQL endpoint
 Enables interoperability across sites
 Built on the PHP ARC2 library
 AllRDF data indexed in the endpoint
 Each page stored as graph and kept up to date
Figure 3.6: A list of SPARQL results (left) and an RDF SPARQL Proxy
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3. Data endpoint for complex querying
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 Local RDF data exposed in a SPARQL endpoint
 enable interoperability across sites
 built on the PHP ARC2 library
 allRDF data indexed in the endpoint
 Each page stored as graph and kept up to date
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What do we add?
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4
1, 2
3
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4. Lazy loading of external data
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 Lazy loading (caching) of distant RDF resources
 Enables interoperability across sites
 Built on the PHP ARC2 library
 CONSTRUCT query to map distant schema to local schema
A list of SPARQL results (left) and an RDF SPARQL Proxy profile form
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4. Lazy loading of external data
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 Lazy loading of distant RDF resources
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Where is it used?
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Science Collaboration Framework
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 Web application toolkit based on Drupal
 Enables online scientific collaboration
– publishing, annotating, sharing and discussing any content
– articles, papers, reviews, perspectives, interviews, news, biographies
– profile information on community members
 Targets biomedecine communities, but generic in essence
 Networked sites producing Linked Data
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SCF collaborating sites
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 Stembook (Stem Cell articles and reviews)
– http://www.stembook.org/
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SCF collaborating sites
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 Michael J Fox Foundation (Parkinson disease)
– http://www.pdonlineresearch.org/
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Conclusion
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Conclusion
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 Structureof CMS sites contain valuable schema
information
 Our suggested “workflow”:
 site vocabulary from the local structure (RDF CCK)
 enables out-of-the-box RDF export: expose your Drupal site
to the Web of Data without any additional effort from site
admin or content editors (RDF CCK)
 mapping to existing RDF vocabularies improves integration in
the LOD cloud (evoc)
 SPARQL endpoint
 Lazy loading of RDF resources (RDF Proxy)
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Conclusion
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 Drupal 6 modules available for download
– http://drupal.org/project/rdfcck
– http://drupal.org/project/evoc
– http://drupal.org/project/sparql_ep
– http://drupal.org/project/rdfproxy
 Online prototype
– http://drupal.deri.ie/projectblogs/
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Good news from Drupal 7:
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 RDF mapping feature committed to Drupal 7 core
 RDFa output by default (blogs, forums, comments, etc.)
using FOAF, SIOC, DC, SKOS.
 Download development snapshot
– http://ftp.drupal.org/files/projects/drupal-7.x-dev.tar.gz
 Currently more than 200.000* sites on Drupal 6
 waiting to make the switch to Drupal 7
 waiting to massively increase the amount of RDF data
on the Web
 Discussion
 http://groups.drupal.org/semantic-web
* http://drupal.org/project/usage/drupal
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