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

1. Semantic Wiki In The
Enterprise
Josef Holy
Social Network Designer
Sun Microsystems

2. Web
Semantic Wiki In The
Enterprise
Josef Holy
Social Network Designer
Sun Microsystems

3. Introducing Sun Context
Everyone and Everything Participating on the
Network

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. 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. 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. 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. 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. 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. Who am I : MyProfile

11. What I need: Communities

12. Mashup: Personalized Search

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. KM Challenges
• Missing notion of relevance and quality
• Relevant knowledge retrieval and
discovery
• Expert discovery
• Shared concept model maintenance

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. Community Equity Introduction
Measuring Quality In Open Communities

17. Deriving value from user's activities
Activities Value
Social Cloud
System

18. Deriving value from user's activities -
eBay
eBay Sell/Buy
Ranking
Send/Pay/Rate
Top buyers/Top sellers

19. Deriving value from user's activities
Post/Read Digg
Digg
System
Digg it!
Top stories/Top Diggers

20. Deriving value from user's activities –
Community Equity
Content-Centric Create/Modify
Community CEQ
Rate/Comment
/...
Top Content/Top Authors/...

21. Information Equity
Content Activities People
create
modify
download
view
rate
comment
tag

22. Personal Equity
my Community Equity Activities Me
Contribution
create
modify
tag
Participation People
view
rate
comment
reuse

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. SunSpace is a start
Activities
CEQ
• Wiki-centric social collaboration platform
• Traditional Web technologies
• Very basic metadata handling (flat tags)

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. KM Challenges
• Missing notion of relevance and quality
• Relevant knowledge retrieval and
discovery
• Expert discovery
• Shared concept model maintenance

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. 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. Semantic Wiki - Source Of Structure
Corporate
boundaries

30. Semantic Wiki - Integration Layer

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. Activity Feed Example: Facebook

33. KM Challenges
• Missing notion of relevance and quality
• Relevant knowledge retrieval and
discovery
• Expert discovery
• Shared concept model maintenance

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. Introducing Tag
Equity:
Structure + Value
(Tags) (CEQ)

36. Tag Equity (TEQ) – Content View
Aggregated TEQ value
of tag “Java”
50
Docs tagged
with
“Java”
20 10 15 5

37. Tag Equity (TEQ) – People View
Aggregated “Java”
Expertise
50
People who
produced
docs with
tag
“Java” 20 10 15 5

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. TEQ → Concept Equity (SemEQ)
• But what to do with other types of
relations?
Software
70
broader broader
+ +
built on
50
??? 20
Java

40. KM Challenges
• Missing notion of relevance and quality
• Relevant knowledge retrieval and
discovery
• Expert discovery
• Shared concept model maintenance

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. 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. 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. 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. 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. Thanks for your
attention!
Josef Holy
Josef.Holy@Sun.COM
twitter.com/holyj

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