1. What is a Semantic Wiki
Why should you want to know or care?
Jesse Wang, Wil Smith
2012.04.11
For Semantic Web Meetup in San Diego

2. Crowdsourcing for Better Knowledge Acquisition
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3. A Key Feature of Wiki
This distinguishes wikis from other publication tools
3

4. 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
4

5. 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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6. Success of Wikis
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7. Finding information…
Wikipedia has articles about…
• … all cities with info on their
populations, locations and
skyscrapers, etc.
… all German cars with engine
size, accelerating data…
Can you find:
Skyscrapers with 50+ floors
and built after 2000 in
Shanghai (or Chinese cities
with 1,000,000+ people)?
Or German(Porsche) cars that
accelerate from 0-100km/h in
5 seconds?
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8. Can Search Solve the Problem?
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9. How Wikipedia Answers – List!
http://en.wikipedia.org/wiki/List_of_fastest_
cars_by_acceleration
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10. And Tables…
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11. Answer is Hidden Deeply In
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12. Look into List in Wikipedia
http://en.wikipedia.org/wiki/List_of_German_cars
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13. Editing Standard Wiki Article – Static List
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14. Static List, Tables, …, Not Useable Enough
http://en.wikipedia.org/wiki/List_of_lists_about_Oregon
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15. To Find More Info
• 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
• 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…
• And many more
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16. 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
16

17. Two Perspectives
Wikis for
Metadata
Metadata for
Wikis
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18. Characteristics of Semantic Wikis
Semantic Wikis
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19. 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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20. Why Semantic Wiki?
 Annotation of existing structures with machine
readable metadata
links carry meaning, typing of links, typing of pages
 Context dependent adaptation and presentation
different domains have different ways of presenting
content, personal preferences, etc.
 Improved, “intelligent”, search and navigation
queries to the structure, visualisation of structure, derived
information
 Improved interoperability between systems
exchange of content, integration of different systems,
agents, etc.
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21. What is the Promise of Semantic Wikis?
 Semantic Wikis facilitate
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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22. 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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23. 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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24. Short History of Semantic MediaWiki (SMW)
 Born at AIFB
– Typed links and types and more
– Export articles as RDF
– Maximally flexible for the wiki user
 SMW 0.1 released by AIFB in Sept 2005
– Parser/storage support for typed links – [[type::link | label]]
– FactBox for semantic relations at end of article
– Special:SearchSemantic, with basic auto-completion for link types
– Simple query language (“ask”)
 Vulcan kicks off Halo Extensions to SMW project in August 2007
 SMW 1.0 released by AIFB in Dec 2007, Ontoprise releases Halo
Extension 1.0 in parallel
– “Property” instead of “Relation” and “Attribute”
– Many new datatypes/special pages/UI features
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25. Overview of Semantic MediaWiki (SMW)
 Open source (GPL)
– Well documented, active user forum
 Active development
– Commercial support (SMW+) available
 World-wide community
– International Conferences
• Next SMWCon on 4/25-27, 2012 in Carlsbad, CA
Very stable core, various extensions
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26. Semantic MediaWiki (SMW) Markup Syntax
Tsinghua is a university located in
[[Has location::Beijing]], with
[[Has population::27000|about 27 thousands]]
students.
In page "Property:Has location": In page "Property:Has population":
[[Has type::Page]] [[Has type::number]]
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27. Define Classes
Beijing is a city in [[Has
country::China]], with population
[[Has population::2,200,000]].
[[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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28. Possible Database-style Query over Data
Ex: 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]]
…
}}
28

29. Semantic MediaWiki Stack
MediaWiki (XAMPP)
Extension: Semantic
MediaWiki
More Extensions and
Applications
29

30. Simple Example: Semantic Sci-Fi Movie Wiki
 Demo
30

31. SMW Extensions – Help Build Great Things
Data I/O
• Halo Extensions, Semantic Forms, Semantic Notification, …
Query and Browsing
• Semantic Toolbar, Semantic Drilldown, Faceted Search, Full-text Retrieval…
Visualization
• Semantic Result Printers, Tree View, Exhibit, Flash charts…
Other useful extensions
• HaloACL, Wiki Admin Tool Triplestore Connector, Simple Rules…
• Semantic WikiTags and Subversion Integration extensions
• Linked Data Integration Framework with R2R and SILK from F.U.Berlin
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32. Example: Ultrapedia – Semantic Wikipedia
 Ultrapedia: An SMW demo built to explore general
knowledge acquisition in a wiki
 Wikipedia merged with the power of a database
 Help Readers and Writers Be More Productive
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33. Standard View of the Wiki Data
http://wiking.vulcan.com/up/index.php/Porsche_996

34. Dynamic View of the Acceleration Data

35. Graph View of the Acceleration Data

36. Dynamic Mapping and Charting

37. Information Discovery via Visualization
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38. 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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39. Semantic Seahawks Football Wiki
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40. 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

41. The Inspiration
 We started with a
 We could have an
42

42. Application 1: 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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43. Vulcan Project Management Wiki (Story)

44. Vulcan Project Management Wiki (Task)
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45. Vulcan Project Management Wiki (Visualizations)
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46. 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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47. 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.
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48. 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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49. Application 2: Human Brain Map
• Open, public online access
• A detailed, interactive three-dimensional
anatomic atlas of the "normal" human
brain
• Data from multiple human brains
• Genomic analysis of every brain structure,
providing a quantitative inventory of which
genes are turned on where
• High-resolution atlases of key brain
structures, pinpointing where selected
genes are expressed down to the cellular
level
• Navigation and analysis tools for
accessing and mining the data

50. Biological Linked Data Map
• Open, public online access
• Data from multiple RDF data stores
• Complete import pipeline using LDIF
framework
• Outlines of each imported instance
embedding inline wiki properties and
providing views of imported properties from
original RDF datasets
• Charting tools that „pivot‟ SPARQL queries
providing several views of each query
• Navigation and composition tools for
accessing and mining the data

51. Where did we get the data?
 KEGG : Kyoto Encyclopedia of Genes and Genomes
– “KEGG GENES is a collection of gene catalogs for all complete genomes
generated from publicly available resources, mostly NCBI RefSeq.”
 Diseasome
– “The Diseasome website is a disease/disorder relationships explorer and a
sample of an innovative map-oriented scientific work. Built by a team of
researchers and engineers, it uses the Human Disease Network dataset.”
 DrugBank
– “The DrugBank database is a unique bioinformatics and cheminformatics
resource that combines detailed drug data with comprehensive drug target
information.”
 SIDER
– “SIDER contains information on marketed medicines and their recorded adverse
drug reactions. The information is extracted from public documents and package
inserts.”

52. Wiki Ontology Map
• Genes
• DrugBank : 4,553
• Diseasome : 3,919
• KEGG : 9,841
• Diseases
• Diseasome : 4,213
• KEGG : 459
• Drugs
• DrugBank : 4,772
• KEGG : 2,482
• SIDER : 924
• Effects
• SIDER : 1,737
• Pathways
• KEGG : 28,442
61,342 Instances Available
for Import
We chose to intentionally simplify the ontology
due to disagreements between researchers
about entity relationships and subclasses.

53. Embedding SPARQL Semantic Results Formatters
 Every piece of content on every instance page is generated
by Semantic Result Formatters interpreting SPARQL
results.
 Most inline properties are embedded in templates returned
by SPARQL formatters.
 All 3 dynamic graph types are interpreting results of
SPARQL queries and injecting a JavaScript template into
the head of the page.
 The outline template takes selected predicates and objects
from a SPARQL query, defined in the query embedding,
and generates an HTML template for the page.

54. Four Initial Templates for Each Instance by Category
1. Custom infobox within outline template
• Visible inline properties
2. Outline template providing instance
information
3. Widget template displaying dynamic
charts or third party services
• Donut charts and disease Twitter feed
4. Broad table SPARQL queries showing
instance relationships
5. Hidden inline properties for other
extensions

55. Demo Links
 http://neurowiki.alleninstitute.org/index.php/Main_Page
 http://neurowiki.alleninstitute.org/index.php/AR
 http://neurowiki.alleninstitute.org/index.php/Propofol
 http://neurowiki.alleninstitute.org/index.php/AIBS:Main_Page
 http://neurowiki.alleninstitute.org/index.php/AIBS:AR
 http://neurowiki.alleninstitute.org/index.php/Frontal_Lobe
 http://neurowiki.alleninstitute.org/index.php/NEUROLEX:Main_Page
 http://neurowiki.alleninstitute.org/index.php/Adrenoleukodystrophy

56. Neurowiki in Action!
 Which drugs are used in Chemotherapy?
 What are the dangers of Propofol?
 How are base entities like Calcium represented?
 How are new inline properties added to entities?
– Can these be searched?
– Can these be queried using ASK?
 Do existing extensions work with the framework?

57. Openness of SMW as a Platform
58

58. Semantic MediaWiki Enables Collaboration
Create and Manage Real
Knowledge
Build Social Semantic
Web Applications
In an Efficient and Cost-
Effective Way
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59. 60

60. Tutorial: Wednesday 4/25
 MediaWiki
– How to Edit, Format Text, Use Template
– Infoboxes, Parser Functions, Extensions…
 Semantic MediaWiki
– Features, usage, queries, patterns
– Extensions: data i/o, forms, maps, visualizations…
 SMW+
– Usability Enhancement, Wiki Admin Tools, Installation Packages
– Enterprise Wiki, Microsoft Office Integration, Triple-store support…
 Edithon
– Supervised individual and group collaboration time
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61. Conference Days (4/26-4/27)
 Two Keynote Talks
– Semantics and Wikis: from Genomes to X Games by Tom Marsh
– Text, Data, Structure, Semantics and Knowledge by Mark
Greaves
 Variety of Presentations
– Open and closed data, including talks on wikidata
– Social and semantics, mash-ups
– R&D: life science, neuroscience, biology, finance…
– News, updates, demos and apps
– Lightning Talks
 Plenty of Group Social Time
– Breakfast, Coffee breaks, Lunch and Dinner
63 – Movie screening, restaurant and bars, …

62. Social and Semantic Web at a Great Value 
 Thanks to our sponsor ai-one and local organizers
 We‟d be able to provide
– Quality lunch
– Drinks and pastry/snacks for coffee breaks (breakfast)
– Conference dinner
– Business relation breakfast on Friday 4/27
 Opportunity to meet a variety of people
– Achievers
– Hackers
– Bar-hoppers
 Register Now! http://bit.ly/scs12
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63. Acknowledgement
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64. (End of Slides)
Backups start here
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