SemSearch09 workshop at WWW2009, April 21th 2009- http://km.aifb.uni-karlsruhe.de/ws/semsearch09/ - Paper available at: http://km.aifb.uni-karlsruhe.de/ws/semsearch09/semse2009_25.pdf
1. 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.
2. 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
3. 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
4. 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
5. 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”
6. Exposing SIOC data
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Enable common semantics for user-generated content
From various applications, completely automated
7. 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
8. 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
9. 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
10. 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
11. 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
12. 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
13. 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
14. Thank you !
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Any questions ?
Contact
http://apassant.net
alexandre.passant@deri.org