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Chapter 3 E-business infrastructure 149

Mini Case Study 3.3 Enhancement and integration of corporate social software using the
semantic web at Electricité de France

Electricité de France, the largest electricity company in France, recently introduced the use of social soft-
ware within its R&D department, embracing the Enterprise 2.0 movement. The use of blogs, wikis, free-
tagging, and the integration of external RSS feeds offers new possibilities for knowledge management and
collaboration between engineers and researchers. Yet, these tools raise various issues, such as:
Querying data across applications is not straightforward as different applications use different formats
(database structure or output format) to model their data
Knowledge created using wikis cannot be easily understood by computers. For instance, a user cannot
run a query such as ‘List all companies working on solar energy and based in the US’. The user would
need instead to browse various pages to find the answer
Free-tagging leads to heterogeneity and ambiguity which complicates the search for relevant content. For
instance, a query about ‘solar’ will not retrieve documents tagged with ‘solar energy’ or ‘solar_energy’
RSS feeds tend to produce a lot of incoming data, which, for example, makes it difficult to follow all infor-
mation about a given company

The solution
To solve these problems and offer new and value-added services to end-users, we developed a solution that
uses Semantic Web technologies and relies on various components that act together and provide a mediation
system between those services and the users. This mediation system provides a common model for meta-data
and for document content. It achieves this using ontologies, plugins for existing tools to create data according
to these ontologies, a central storage system for this data, and services to enrich information retrieval and data
exchange between components.
Since our first requirement was to provide a common and machine-readable model of meta-data for
content from any service, we decided that the model should be implemented in RDF. We then took part in
the development of the SIOC (Semantically-Interlinked Online Communities) ontology which provides a
model for describing activities of online communities in RDF. For example, SIOC can be used to describe
what is a blog post, what properties a blog has, and how a blog post relates to a user and user comments.
SIOC takes advantage of commonly used vocabularies such as FOAF (Friend Of A Friend) and Dublin Core.
SIOC exporters and translators were added to our services so that wherever the data comes from (blogs,
wikis, RSS feeds), it is automatically modeled in a common way, offering a first layer of unified semantics
over existing tools in our mediation architecture.
As much valuable knowledge is contained within our wikis, we extended the wiki server with semantic

functionalities in order to model some of its content in a machine-readable way. To do this we created
ontologies which model the concepts within the knowledge fields of our wikis. For example, we designed
an ontology to model information about companies, their industry, and location. In order to benefit from
existing models and data, our ontologies extend or reuse existing ones such as Geonames and SKOS
(Simple Knowledge Organization System). Moreover, to allow users to easily publish and maintain ontology
instances from wiki pages, our add-on provides the ability for wiki administrators to define form templates
for wiki pages and to map them to the classes and properties of the ontologies. Thus, users create and
maintain instances by editing wiki pages, which is as simple as what they were doing prior to implementing
Semantic Web technologies. For instance, instead of writing that ‘EDF is an organization located in France’,
a user fills in the template so that the following RDF triples will be immediately created when saving the
page, thus providing a second layer of semantics for the mediator:
athena:EDF rdf:type foaf:Organization;
geonames:locatedIn <http://sws.geonames.org/3017382/>.
In order to provide a bridge between the advantages and openness of tagging, and the powerful but
complex use of ontologies and semantic annotation, we developed a framework called MOAT (Meaning Of
A Tag). MOAT allows users to collaboratively provide links between tags and their meanings. The resources