Semantic Wiki For The Enterprise

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Keynote presentation from the Semantic Wiki Workshop at the European Semantic Web Conference 2009.

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Semantic Wiki For The Enterprise

  1. 1. Semantic Wiki In The Enterprise Josef Holy Social Network Designer Sun Microsystems
  2. 2. Web Semantic Wiki In The Enterprise Josef Holy Social Network Designer Sun Microsystems
  3. 3. Introducing Sun Context Everyone and Everything Participating on the Network
  4. 4. Sun – Introduction • 30 000+ employees • Network is the computer • Everybody and everything participating on the Network • HW, SW + Services – we have the whole stack • Main asset: IP
  5. 5. We Are Open • The biggest Open Source contributor • Not just SW, but also HW (OpenSparc.net) • Utilization of community model is a must • Communities spanning over the actual corporate boundaries • Strong notion of bottom-up innovation
  6. 6. We Use 'The 2.0ols' • Basic infrastructure for our communities: > Blogs - http://blogs.sun.com – CEO blog: http://blogs.sun.com/jonathan > Wikis – Internal: literally hundreds of internal wikis – External: http://wiki.sun.com > Forums – http://java.sun.com > “Code-forge” – http://www.kenai.com > Social networks – Twitter, Facebook, LinkedIn...etc.
  7. 7. KIWI Scope: Customer Engineering Community (CEC) • 9000+ people geographically and organizationally dispersed • Design, Deployment and Post-sale support • Sub-groups relate to products, services and practices • Running on Wiki since years > Project SunSpace > Low barrier for participation
  8. 8. What is SunSpace ? • Wiki-centric collaboration platform • Low barrier for participation • Built on top of Confluence Wiki > http://www.atlassian.com/confluence • CEC's main community infrastructure > Wiki > File Store > Tags > Ratings, Comments > Social Graph > Value System
  9. 9. What is SunSpace ? Wiki-centric collaboration platform •25'000 users •400+ on top of Confluence Wiki Built communities > http://www.atlassian.com/confluence 10X growth in 6 month •Securemain community infrastructure CEC's Enterprise Wiki > Wiki Architecture, Methodology, Value System > File Store > Tags > Ratings, Comments > Social Graph > Value System
  10. 10. Who am I : MyProfile
  11. 11. What I need: Communities
  12. 12. Mashup: Personalized Search
  13. 13. KM Challenges • Low barrier for participation brings: > Missing notion of relevance and quality > Relevant knowledge retrieval and discovery > Expert discovery > Shared concept model maintenance
  14. 14. KM Challenges • Missing notion of relevance and quality • Relevant knowledge retrieval and discovery • Expert discovery • Shared concept model maintenance
  15. 15. Missing Notion Of Relevance and Quality • What is the best white paper about topic X? • Who is the main contributor in the Community Y? • What is a current hot topic? • Who is an expert on topic Z?
  16. 16. Community Equity Introduction Measuring Quality In Open Communities
  17. 17. Deriving value from user's activities Activities Value Social Cloud System
  18. 18. Deriving value from user's activities - eBay eBay Sell/Buy Ranking Send/Pay/Rate Top buyers/Top sellers
  19. 19. Deriving value from user's activities Post/Read Digg Digg System Digg it! Top stories/Top Diggers
  20. 20. Deriving value from user's activities – Community Equity Content-Centric Create/Modify Community CEQ Rate/Comment /... Top Content/Top Authors/...
  21. 21. Information Equity Content Activities People create modify download view rate comment tag
  22. 22. Personal Equity my Community Equity Activities Me Contribution create modify tag Participation People view rate comment reuse
  23. 23. Community Equity CONTRIBUTION PARTICIPATION EQUITY EQUITY Attachments Rate Wiki Comment Blogs Re-use CQ+PQ+SQ+RQ IP Tags Personal SKILLS EQUITY Equity ROLE EQUITY Enterprise Business User Projects Skills Rating Formal Training Informal
  24. 24. SunSpace is a start Activities CEQ • Wiki-centric social collaboration platform • Traditional Web technologies • Very basic metadata handling (flat tags)
  25. 25. Now let's move further Activities CEQ • Wiki-centric social collaboration platform • Built on top of semantic web technologies • Much better metadata handling (triples) > Flat tags → Taxonomy → … → Ontology
  26. 26. KM Challenges • Missing notion of relevance and quality • Relevant knowledge retrieval and discovery • Expert discovery • Shared concept model maintenance
  27. 27. Relevant knowledge retrieval and discovery • Current PULL techniques are not sufficient > Full-text search • A need to PUSH relevant content to users • A need for more structure –> better metadata handling
  28. 28. Semantic Wiki – Social Semantic Platform • Source of structure – interaction with existing tools and services • Structure created both by people and machines • Linking to outside resources → new relations • Social filtering – content with no social actions is less relevant
  29. 29. Semantic Wiki - Source Of Structure Corporate boundaries
  30. 30. Semantic Wiki - Integration Layer
  31. 31. Default Entry Page – Activity Feed • Activities related to content relevant/interesting for the user > Semantic Graph → Reasoning → Personalization • PUSH in a natural, non-intrusive way > “Check out this new white paper” > “Hey, new version of Java was just released.” > “Could you maybe help this guy?” • Empowers participation > Beneficial for the Equity measures
  32. 32. Activity Feed Example: Facebook
  33. 33. KM Challenges • Missing notion of relevance and quality • Relevant knowledge retrieval and discovery • Expert discovery • Shared concept model maintenance
  34. 34. Expert Discovery • Most of the knowledge is tacit, in people's heads > → Finding the right people is more important than finding documents • Who knows what? • Who is an expert on topic X? • Who could help me with this problem? • Who should I learn from?
  35. 35. Introducing Tag Equity: Structure + Value (Tags) (CEQ)
  36. 36. Tag Equity (TEQ) – Content View Aggregated TEQ value of tag “Java” 50 Docs tagged with “Java” 20 10 15 5
  37. 37. Tag Equity (TEQ) – People View Aggregated “Java” Expertise 50 People who produced docs with tag “Java” 20 10 15 5
  38. 38. TEQ → Concept Equity (SemEQ) • How does the Equity Value spread in the semantic graph? • Example: SKOS – cumulatively: Software 70 broader broader + + 50 Java 20
  39. 39. TEQ → Concept Equity (SemEQ) • But what to do with other types of relations? Software 70 broader broader + + built on 50 ??? 20 Java
  40. 40. KM Challenges • Missing notion of relevance and quality • Relevant knowledge retrieval and discovery • Expert discovery • Shared concept model maintenance
  41. 41. Shared Concept Model Maintenance • How to manage folksonomies? > How to bring more structure into the (flat) tag-space? > How to handle new tags invented by users? > Merge, delete, synonyms...etc. > How to give tags a more formal meaning? > How to relate tags to each other? • Concept model should evolve with the domain > Open Communities need flexibility
  42. 42. Top-down Approach • “Let it be taken care of by experts who know everything” > Dictatorship > Failed vision of the SemWeb from 2000 (“World-wide ontology”) > Too static → slow → inefficient
  43. 43. Bottom-up Approach • “Let the community do it in a wiki way!” > Anarchy – chaotic > Some level of control needed > There is no free market in the end > Even wikipedia has its “gardeners”
  44. 44. Solution: Open Concept Model Management (OCM) • Top-down + Bottom-up > Democracy – Elites (“elected” via CEQ) managing the “folksonomy chaos” • Managing Concept Model in a Wiki way • Expertise-based access rights to the CM > Domains maintained by competent experts • Sustainable concept model evolution > Opened to expertise emerging from bottom
  45. 45. Summary – Semantic Wiki In The Enterprise • Semantic Wiki as a core of dynamic intranet > And of Semantic Web • Source of Structure in Unstructured Environment • Need for a Value System > Merged with the semantic graph
  46. 46. Thanks for your attention! Josef Holy Josef.Holy@Sun.COM twitter.com/holyj
  47. 47. Semantic Wiki Function(s) • Wiki - Document authoring tool > Users create structured content (documents) > They are shaping the knowledge base on the instance level • Ontology manager > Creating new classes, defining properties... > Knowledge models need to dynamically evolve • Source of structure, Integration layer > Sustainable approach to data integration

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