semantic search for enterprise 2.0

Chapter ♥ Copyright 2008 Digital Enterprise Research Institute. All rights reserved.

Digital Enterprise Research Institute www.deri.ie

Semantic Search for Enterprise 2.0

Alexandre Passant1, Philippe Laublet2, John Breslin1, Stefan Decker1

1 Digital Enterprise Research Institute, NUI Galway 2 LaLIC, Université Paris-Sorbonne, France

SemSearch09, WWW09, Madrid

21th April 2009


Enterprise 2.0

  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

  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

  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

  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

  Enable common semantics for user-generated content   From various applications, completely automated

Inline macro

Simple autocomplete

field

Complex instance field


From documents to RDF data

  UfoWiki   Wiki interface including forms mapped to ontologies for

collaborative instances management

  Live SPARQL-autocompletion to reuse URIs between wikis


Semantic tagging

  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

Wiki page 2Blog Post 1

hyperlink

a:EDF

f:Company

g:3017382/

g:Featurea:Energy

rdf:type rdf:typea:produces

g:locatedIn

:bpost_1

moat:topic

:wikipage_2sioc:links_to

:wiki_A

sioc:container_of

:alex

sioc:has_creator

creates contains

Wiki A

Sem

antic W

eb layer

Ente

rprise 2

.0 s

erv

ices

Social interactionswth SIOC

Semantic tagging with MOAT

Ontology populationwith semantic wikis


Enabling search

  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

Semantic Middleware

RDF Store

SPARU

L

inte

rface

SPARQ

Lin

terf

ace

Ping system to store

new or updated data

External services using

stored data


Search interface

  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

  Re-using RDF data from the LOD cloud internally   Low-cost Semantic mash-ups

  E.g. Geolocation of wiki instances thanks to Geonames


Conclusion

  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 !

  Any questions ?

  Contact   http://apassant.net

  [email protected]

semantic search for enterprise 2.0

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