This document discusses semantic wikis and their advantages over traditional wikis. Semantic wikis add structured metadata to wiki pages, allowing knowledge to be made explicit and formal. This facilitates consensus over data, combines low-expressivity data authorship with traditional wiki features, and makes content more interoperable between systems. Semantic MediaWiki is highlighted as a popular open-source semantic wiki platform that extends MediaWiki with typed links and properties to add semantic structure.

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
2

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?
8

9. How Wikipedia Answers – List!
http://en.wikipedia.org/wiki/List_of_fastest_
cars_by_acceleration
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10. And Tables…
10

11. Answer is Hidden Deeply In
11

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
18

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
22

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)
46

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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