My talk for Tsinghua University Alumni in Seattle area for centennial celebration tech talk

1. Semantic Wikis
Social Semantic Web In Action
2011-03-25
Specially Prepared for Tsinghua University Alumni
in greater Seattle area for centennial celebration

2. About Me: Jesse Wang 王(嘉)欣
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3. Who is Vulcan
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4. What does Vulcan do
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5. It all began with a vision…
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6. Now the Vision Continues as Project Halo
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7. Project Halo’s Focus Areas
• Automated User-Centered
AURA Reasoning and Acquisition System
• Text book you can talk to
• Semantic Inference with Large
SILK Knowledge-base
• Non-monotonic rule system / RIF
• Semantic MediaWiki +
SMW+ • Knowledge authoring with SMEs
Plus other related semantic technologies and commercial efforts
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8. Project Halo’s Goals
 Address the core problems
in Knowledge Bases
– scale
– brittleness
 Have high impact
KB Effort (cost, people,…)
Now
Vulcan
Future
KB size (number of assertions, complexity…)
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9. Crowdsourcing for Better Knowledge Acquisition
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10. Wiki as a Crowdsourcing Tool
This distinguishes wikis from other publication tools
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11. Consensus in Wikis Comes from
 Collaboration
– ~17 edits/page on average in
Wikipedia (with high variance)
– Wikipedia‟s Neutral Point of View
 Convention
– Users follow customs and
conventions to engage with
articles effectively
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12. Software Support Makes Wikis Successful
 Trivial to edit by anyone
 Tracking of all changes, one-
step rollback
 Every article has a “Talk” page
for discussion
 Notification facility allows
anyone to “watch” an article
 Sufficient security on pages,
logins can be required
 A hierarchy of administrators,
gardeners, and editors
 Software Bots recognize certain
kinds of vandalism and auto-
revert, or recognize articles that
need work, and flag them for
editors
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13. Success of Wikis
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14. Wikis are Great, But…
Wiki Clock?
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15. How About Hidden Goodies in the Wiki?
Wikipedia has articles
about…
•… all cities
•… their populations
•… their mayors
•… the skyscrapers
So can I ask for a list of
the world‟s 5 largest
cities with a female
mayor?
Or Skyscrapers in
Shanghai with 50+ floors
and built after 2000?
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16. Enters Semantics…
To answer questions like:
• The female majors of top 10 cities,
sorted by population, starting year,
age…
• All skyscrapers in China (Japan,
Thailand,…) of 50 (40/60/70) floors or
more, and built in year 2000
(2001/2002) and after, sorted by built
year, floors…, grouped by cities,
regions…
• Median (average) base annual salary
of CEOs of Fortune 100 companies in
America (Europe, Asian,…)
• All Porsche Vehicles Made in Germany
that accelerate from 1-100 km/h less
than 4 seconds
• Sci-Fi movies made after year 2000
that cost less than $10M and gross
more than $30M
• A map showing where all Mercedes-
Benz vehicles are manufactured
• And many more
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17. What is a Semantic Wiki
 A wiki that has an underlying model of the
knowledge described in its pages.
 To allow users to make their knowledge explicit and formal
 Semantic Web Compatible
Semantic Wiki
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18. Two Perspectives
Wikis for
Metadata
Metadata for
Wikis
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19. Characteristics of Semantic Wikis
Semantic Wikis
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20. List of Semantic Wikis
AceWiki Semantic MediaWiki - an
ArtificialMemory extension to MediaWiki that
Wagn - Ruby on Rails-based turns it into a semantic wiki
KiWi – Knowledge in a Wiki Swirrl - a spreadsheet-based
semantic wiki application
Knoodl – Semantic
Collaboration tool and TaOPis - has a semantic wiki
application platform subsystem based on Frame
logic
Metaweb - the software that
powers Freebase TikiWiki CMS/Groupware
integrates Semantic links as a
OntoWiki core feature
OpenRecord zAgile Wikidsmart - semantically
PhpWiki enables Confluence
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21. Basics of Semantic Wikis
 Still a wiki, with regular wiki features
– Category/Tags, Namespaces, Title, Versioning, ...
 Typed Content (built-ins + user created, e.g. categories)
– Page/Card, Date, Number, URL/Email, String, …
 Typed Links (e.g. properties)
– “capital_of”, “contains”, “born_in”…
 Querying Interface Support
– E.g. “[[Category:Member]] [[Age::<30]]” (in SMW)
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22. SMW Markup Syntax
Tsinghua is a university located in
[[Has location::Beijing]], with
[[Has population::27,000]] students.
In page "Property:Has location": In page "Property:Has population":
[[Has type::Page]] [[Has type::number]]
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23. Define Classes
 On Page Beijing a city in [[Has
Beijing is
country::China]], with population
 One possible solution:
[[Has population::2,200,000]].
– Beijing is a [[Is a::city]]
[[Category::Cities]]
Categories are used to define classes because they are better for class inheritance.
The Jin Mao Tower (金茂大厦) is an 88-story landmark supertall
skyscraper in …
[[Categories: 1998 architecture | Skyscrapers in
Shanghai | Hotels in Shanghai | Skyscrapers over 350
meters | Visitor attractions in Shanghai | Landmarks in
Shanghai | Skidmore, Owings and Merrill buildings]]
Category:Skyscrapers in China Category: Skyscrapers by country
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24. Database-style Query over Wiki Data
Example: Skyscrapers in China
higher than 50 stories, built before
2000
ASK/SPARQL query target
{{#ask:
[[Category:Skyscrapers]]
[[Located in::China]]
[[Floor count::>50]]
[[Year built::<2000]]
…
}}
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25. What is the Promise of Semantic Wikis?
 Semantic Wikis promise
Consensus over Data
 Combine low-expressivity
data authorship with the
best features of traditional
wikis
 User-governed, user-
maintained, user-defined
 Easy to use as an
extension of text authoring
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26. One Key Helpful Feature of Semantic Wikis
Semantic Wikis are “Schema-Last”
Databases require DBAs and schema design;
Semantic Wikis develop and maintain the schema in the wiki
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27. Semantic MediaWiki in 2010
 Open source (GPL)
 Well documented
 Active mailing list
 Commercial support available
 World-wide community
 Regular Conferences
– Next SMWCon 4/28-30, 2011 Arlington, VA
Very stable SMW core
Mature while still growing, slowly but steadily
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28. SMW Extensions
Data I/O
• Halo Extensions, Semantic Forms, Semantic Notification, …
Query and Browsing
• Semantic Toolbar, Semantic Drilldown, Enhanced Retrieval, Search…
Visualization
• Semantic Result Printers, Tree View, Exhibit, Flash charts…
Other useful extensions
• HaloACL, Deployment, Triplestore Connector, Simple Rules…
• Semantic WikiTags and Subversion Integration extensions
• Upcoming Linked Data Extension, with R2R and SILK from F.U.Berlin
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29. Wikis Can Help Information Management
Research = Locate and Find Data ?
 Business Intelligence
 Finding Expertise
 Internal Encyclopedia
 Documentation
 Enterprise Search
Crowd Sourcing is a Great Solution!
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30. Example I: KnowIT in Johnson & Johnson
 Most Frequently Asked Questions: (J&J example)
– What are the directions between two J&J sites?
– What is the meaning of KOL ? HLM ? DRU ?
– What data sources can we use to compare biological pathways?
– Can you give us a list of R&D applications, related servers and
stakeholders and send us an update every six months?
 Capture Facts About Things
– Definitions, concepts, questions
– Locations
– Data sources
– Organizations and people
– Technologies and systems
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31. System Architecture
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32. Example II: Knowledge Encapsulation Framework
 Allow modelers to exploit the „information resources‟ they
have and discover new, potentially relevant material across
new media types
 KEF aims to provide:
– an effective method for storing, retrieving, reviewing and
annotating your documents
– an environment where you can share these materials with team
members and discuss
– a mechanism to discover new, related information for social and
traditional media
– a means to link this material to model representations to aid
analysis and game-play
 Achieved by a semantic wiki enabled with an NLP pipeline
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35. Example 3: Ultrapedia – An Analytical Semantic Wikipedia
 Ultrapedia: An SMW demo built to explore general knowledge
acquisition in a wiki
 Wikipedia merged with the power of a database
– Data extracted from Wikipedia Infobox and Table data; stored in RDF
– For Authors: tools to create more compelling articles
• Great visualizations: charts, tables, timelines, photos, analytics
• Always up-to-date across the Encyclopedia
• Encourage data consistency and find data errors
• Link in other web data sources
– For Readers:
• Enhanced articles and data interaction
• Faceted navigation
• Sophisticated queries (both standing and ad-hoc)
 Maintenance via the Wikipedia update process
– Data is from the article text, with simple ways for article authors to maintain and
extend it.
– Authors and readers always in the loop for merging, updating, validating,
mapping
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36. Graph Views of the Acceleration Data

37. Dynamic Mapping and Charting

38. Information Discovery via Visualization
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39. Video: Semantic Wikis for A New Problem
Increasing technical complexity →
← Increasing User Participation
 Social tag-based  Algorithm-based
Semantic
characterization object
Entertainment
 Keyword search over Wiki characterization
tag data  Database-style
 Inconsistent  Social database-style search
semantics characterization  Consistent semantics
 Easy to engineer  Database search +  Extremely difficult to
wiki text search engineer
 Semantic consistency
via wiki mechanisms
 Easy to engineer
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40. Semantic Seahawks Football Wiki
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41. Based on Simple Templates and Forms
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42. Semantic Entertainment: Query Result  Highlight Reel
 Commercial
Look/Feel
 Play-by-play
video search
 Highlight reel
generation
 Search on
crowd-defined
patterns
(“touchdowns
with big hits”)
 Tree-based
navigation
widget
 Very favorable
economics

43. The Inspiration
 We started with a
 We built a
 We now have an
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44. We CAN Build Applications (Fairly) Easily
 With all the extensions of Semantic MediaWiki.
Data I/O
• Halo Extensions, Semantic Forms, Semantic Notification, …
Query and Browsing
• Semantic Toolbar, Semantic Drilldown, Enhanced Retrieval, Search…
Visualization
• Semantic Result Printers, Tree View, Exhibit, Flash charts…
Other useful extensions
• HaloACL, Deployment, Triplestore Connector, Simple Rules…
• Semantic WikiTags and SVN Integration extensions
• Upcoming Linked Data Extension, with R2R and SILK from FUB
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45. Collaborative Proposal Management at BT with SMW+
Active Bid Viewer
Service Desk Selector
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46. Social Semantic Web Applications
Omitting x examples, y pictures and z lines of text…
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47. Case Study 2 and Demo: Project Management with SMW+
 Automatically
populate tables
 Just the data you
want,
 At the level you want
 Calendars and
timelines
 Workflows
 Personal menus
 Form-oriented inputs
 Notifications via
email/RSS
 MS Office integration
 SVN integration
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48. Vulcan Project Management Wiki (Story)

49. Vulcan Project Management Wiki (Task)
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50. Vulcan Project Management Wiki (Visualizations)
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51. Screenshot of a Sprint page
Data automatically generated via template queries on page
http://wiking.vulcan.com/dev/index.php/Sprint_101020
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52. Requirements for Wiki “Developers”
 One need not
– Write code like a hardcore programmer
– Design, setup RDBMS or make frequent schema changes
– Possess knowledge of a senior system admin
 Instead one need
– Configure the wiki with desired extensions
– Design and evolve the data model (schema)
– Design Content
• Customize templates, forms, styles, skin, etc.
 The bar is dramatically lowered to build applications
– “Source code” is part of the open content of wiki too!
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53. Effectiveness of SMW as a Platform Choice
Packaged Software SMW + Extensions Custom Development
☺Very quick to ☺ Still quick to N Slow to develop
obtain program ☺Extremely flexible
N Hard to customize ☺ Easy to customize N High cost to develop
N Expensive ☺ Low-moderate cost and maintain
 Microsoft Project  Vulcan Project Wiki  .NET Framework
 Version One  B.L.S.  J2EE, …
 Microsoft  RPI map  Ruby on rails
SharePoint
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54. Conclusions
 Semantic MediaWiki+ (http://smwforum.ontoprise.com)
– Open-source, growing semantic wiki software system
– Wiki-style text + semantic markups
– Collaborative, user-governed subject models and data curation
– Simple and extensible data models with easy import/export
 SMW+ has many government and industry users
– People built applications with it
Knowledge Management via
KB Effort (cost, people,…)
 Now
crowds can work
– A way to leverage and exploit
web-collected data Vulcan
– A lightweight collaborative
knowledge management tool Future
 A new platform for lightweight KB size (number of assertions, complexity…)
web application development
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55. Acknowledgement
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56. (End of Slides)
Backups starts here
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57. Case Study: Battle-space Luminary System
 Discover when New Information represents a change in understanding of entities
– Discovery of explicit entity links, implicit relationships
 Large Volumes of Data in various formats
– Unstructured news articles
– Tactical Reports, Field Intelligence
– Structured Database Information
 Use Wiki Pages to represent current knowledge about an entity – “what we know”
 Domain Ontology to represent domain of information – “what we want to know”
 Issue Alerts when Significant Events occur
– New information according to category
– Changing information on topics of interest
– Need to send information to various devices – cell phones, email, etc.
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58. System Design
 Wiki Configuration
– Semantic MediaWiki: Large developer community, active development, open
source. Wikipedia uses MediaWiki, so scalability and performance are
important.
– Semantic Results Format: Provides various rich media displays of semantic
information, including graphs, timelines, maps
– Semantic Forms: Provides convenient user interface for entering semantic
data into wiki, avoiding cumbersome wikitext
– Semantic Notifications: Enables sending of notifications when results of
semantic query change.
 Domain Ontology
– Created OWL Ontology for Terrorism
 Semantic Parsing, Extraction, Reasoning
– Java Process using various Open-Source Toolkits
– Rapid plugin of new technologies
83 – Multiple Data Sources supported

59. Sample Content Page
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60. Wiki Content Design
 Use Templates to Ensure Consistent Look-and-Feel
– Templates Correspond to Ontology Classes
– Fields within Templates correspond to Properties within Ontology
– Rich Content Visualizations derived in consistent way
 Hierarchical Categories match Class Hierarchy within Ontology
– Ensures Validity for Properties
– Category included on each Template page to ensure consistency
 Forms Provide ability for users to enter data directly into wiki without
knowing Wiki Text
– Each form corresponds to a Template
– Fields within forms correspond to the fields/properties within the Template
– GUI can include auto-completion
– Created Page immediately linked semantically to rest of Wiki
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61. Sample Visualizations
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62. Wikipedia for Porsches (Acceleration Data Example)
 Information Need: All Porsche models that accelerate 0-
100kph in under 5, 6, and 7 seconds

63. More Porsche Acceleration Data in Wikipedia

64. Ultrapedia Main Page
Main Page

65. Semantics for Improved Wiki Navigation
Tree View Control Abstract/Summary quick preview

66. The Porsche 996 Acceleration Table In Ultrapedia

67. Same Table as a Query

68. Dynamically-Generated Tables forfast?
Which Porsches accelerate
Queries
 Information Need: All Porsche models that accelerate 0-
100kph in under 5, 6, and 7 seconds

69. Graph Views of the Acceleration Data

70. External Data via a Live Ebay Query

71. Linking to External Ebay Data

72. Photos in Mercedes-Benz E-class W212 Gallery Section
Wiki Articles as Data

73. Timelines from Data Production Timeline View
Volkswagen

74. Dynamic Mapping and Charting

75. Editing Wiki Data In Place
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