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Semantic Search for Enterprise 2.0


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SemSearch09 workshop at WWW2009, April 21th 2009- - Paper available at:

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Semantic Search for Enterprise 2.0

  1. 1. Digital Enterprise Research Institute 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. 2. Enterprise 2.0 Digital Enterprise Research Institute 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. 3. Main issues Digital Enterprise Research Institute 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. 4. Proposed solution Digital Enterprise Research Institute 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. 5. Use-case Digital Enterprise Research Institute 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. 6. Exposing SIOC data Digital Enterprise Research Institute Enable common semantics for user-generated content   From various applications, completely automated  
  7. 7. From documents to RDF data Digital Enterprise Research Institute 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. 8. Semantic tagging Digital Enterprise Research Institute 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. 9. A complete interlinked graph Digital Enterprise Research Institute 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. 10. Enabling search Digital Enterprise Research Institute 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. 11. Search interface Digital Enterprise Research Institute 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. 12. Enabling Semantic mash-ups Digital Enterprise Research Institute Re-using RDF data from the LOD cloud internally   Low-cost Semantic mash-ups   E.g. Geolocation of wiki instances thanks to Geonames  
  13. 13. Conclusion Digital Enterprise Research Institute 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. 14. Thank you ! Digital Enterprise Research Institute Any questions ?   Contact   