Digital Enterprise Research Institute www.deri.ie
Semantic Search for Enterprise 2.0
Alexandre Passant1, Philippe Laublet2, John Breslin1, Stefan Decker1
Digital Enterprise Research Institute, NUI Galway
1
2 LaLIC, Université Paris-Sorbonne, France
SemSearch09, WWW09, Madrid
21th April 2009
Chapter
♥ Copyright 2008 Digital Enterprise Research Institute. All rights reserved.

Enterprise 2.0
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Social media in a corporate context

“The use of emergent social software platforms within

companies, or between companies and their partners or
customers”
The SLATES paradigm

Search

Links

Authoring

Tagging

Extension

Signals


Main issues
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Enterprise 2.0 can be used to foster collaboration

and social intelligence, but raises various issues
Information fragmentation

Description of a project on a wiki, minutes of meetings on

blog posts, information about partners on RSS feeds, etc .
The gap between documents and data

Valuable information in wikis, but hard to efficiently get it,

e.g “list all companies involved in project X since 2008”
Tagging issues

Ambiguity, heterogeneity, lack of organization and gap of

tagging behaviors depending on expertise

Proposed solution
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Considering Enterprise 2.0 at the level of semantics

The SemSLATES approach: middleware for Enterprise 2.0

Following the RDF bus approach

Add-ons for existing applications

RDF(S)/OWL and SPARQL

User-interfaces and applications

on the top of it

Use-case
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EDF R&D: Blogs, wikis, RSS feeds

Extensions for data integration, enabling semantic mash-

ups and semantic search
Common semantics for various applications

SIOC and related vocabularies to model the social

interactions within the user communities
From documents to structured and interlinked data

Lightweight ontologies (SKOS, FOAF extensions …)

Extending the Wiki platform to a Semantic Wiki system

Tagging issues

Semantic tagging with MOAT, i.e. “Tag with URIs”


Exposing SIOC data
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Enable common semantics for user-generated content

From various applications, completely automated


From documents to RDF data
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UfoWiki

Wiki interface including forms mapped to ontologies for

collaborative instances management
Live SPARQL-autocompletion to reuse URIs between wikis

Inline macro
Simple
autocomplete
field

Semantic tagging
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MOAT - Meaning Of A Tag

A lightweight model and framework to bridge the gap

between tagging and semantic indexing
Tags mapped to ontology instances created from the

Wikis (via their label)
User-interface for validation / disambiguation (if needed)

Ability to link new tags to existing instances


A complete interlinked graph
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a:Energy f:Company g:Feature
rdf:type rdf:type
a:produces
Ontology population
Semantic Web layer
with semantic wikis
a:EDF g:locatedIn g:3017382/
moat:topic
Semantic tagging
with MOAT
:wikipage_2
sioc:links_to
:bpost_1
Social interactions
sioc:container_of
sioc:has_creator
wth SIOC
:alex :wiki_A
Enterprise 2.0 services
hyperlink
contains
creates
Blog Post 1 Wiki page 2
Wiki A

Enabling search
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How to integrate and query all this data ?

17000 instances of sioc:Post linked to 300 domain

ontology instances, on various applications
A ping-based architecture with a central RDF store

Each component pings the store when creating /

updating / deleting RDF data
REST-ful interactions using SPARQL / SPARUL

interface
interface
SPARQL
SPARUL
Ping system to store External services using
new or updated data stored data
RDF Store
Semantic Middleware

Search interface
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End-user interface

Identifying relevant instance and retrieving information

from various sources, as well as related entities
Hiding RDF(S)/OWL and SPARQL to the users


Enabling Semantic mash-ups
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Re-using RDF data from the LOD cloud internally

Low-cost Semantic mash-ups

E.g. Geolocation of wiki instances thanks to Geonames


Conclusion
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Enterprise 2.0 enables social interactions and ease

content-generation
But introduces new issues / emphasizes existing ones

Semantic integration can help

Without having to rebuild the information system

Lightweight add-ons, transparency for end-users

Compared to existing information integration

approaches
Use lightweight semantics (FOAF, SIOC, SKOS …)

Consider the social aspect of Enterprise 2.0 both when

creating and using RDF data

Thank you !
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Any questions ?

Contact

http://apassant.net

alexandre.passant@deri.org
