This document discusses semantic wikis, which add semantic structure and machine-readable metadata to regular wikis. Semantic wikis address issues with data coherency, access, and usage in traditional wikis. The document outlines the history and development of semantic wikis, how they work by adding semantic annotations, and how they are used for tasks like semantic search and displaying related information. Popular semantic wiki platforms like Semantic MediaWiki are described.

1. Semantic Wikis
Valentin Sviridov
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Some parts are taken from “Semantic Wikipedia”
presentation by Aaron Gallant and Sung Kim

2. Plan
• Introduction
– Why bother?
– What is Semantic Wiki?
– History and people behind
• Practical point of view
– How does it work?
– How is it used?
• Conclusion
– How to take part?
– Q&A
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3. Why bother?
• Traditional Wiki problems
– Data coherency
– Data access
– External data usage
– Tags/categories hell
• Export to RDF
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4. What is Semantic Wiki?
• Model of knowledge
– Machine processing is possible
• Regular Wiki
– Structured text and untyped hyperlinks
• Semantic Wiki
– Identifiable information with typed hyperlinks
– Metadata
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5. MediaWiki Structures
• Wiki Text: Markup language
– Relation between entities
• Hyperlinks : Redirect to different pages
– [[PAGE_NAME]]
• Category: classify pages and gives structures
– [[Category: CATEGORY_NAME]]
• Synonymous
– Redirect mechanism
• Homonymous
– Disambiguation page
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6. MediaWiki Structures
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7. Category
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8. Semantics: Shaken, not Stirred
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9. Typical features and examples
• Features
– Relate data (X is author of Y)
– Assign attributes to pages
– Search and filter (list of books published in French in
1965)
– Automatic updates of dependent pages
• Usage examples
– Bibliography
– Genealogy
– Catalogues
– Biology-related databases
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10. History
• 2001 – Wikipedia launched
• 2003 – Mention of Semantic Wiki
– L. Sauermann. The Gnowsis – Using Semantic Web
Technologies to build a Semantic Desktop. Master’s
thesis, Vienna University of Technology, 2003.
• Middle of 2000s
– PlatypusWiki (2004); Rhizome (2005); IkeWiki (2006); OntoWiki (2006)
• Today
– Semantic MediaWiki is the most widely used
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11. People
• Tim Berners-Lee
– Web creator
– Coined Semantic Web term
• Jimmy Wales and Larry Sanger
– Wikipedia project
• Markus Krötzsch, Denny Vrandečić and Max
Völkel
– Semantic MediaWiki in 2005
• Agile Knowledge Engineering and Semantic
Web (AKSW) research group, University of
Leipzig
– DBpedia and OntoWiki
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12. How does it work?
• Semantics included or placed separately
• Syntax: Wiki, OWL, RDF
• Ontologies: internal or “standard” ones
• Some wikis provide querying and reasoning
support
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13. How is it used?
• Show similar articles
• Derived information
– Place in the hierarchy
• Browse link types: show all capitals
• Semantic search
– SPARQL
– Usual search + refinement
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14. Wild nature Semantic Wikis
• Public wikis
• Internal usage
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15. Semantic Wiki engines
• Semantic MediaWiki
– Semantic Forms
– Semantic Result Formats
– Semantic Maps
• Ontowiki
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16. Semantic MediaWiki
• Extension to MediaWiki: special annotations
• Features
– Automatically-generated lists
– Visual display of information (maps, graphs, …)
– More simple data structure (no “1620s births” any more)
– Searching
– External use: CVS, JSON, SPARQL, RDF
• Syntax: [[Property name: Value]]
– Hyperlinks
• E.g. London  [[capital of: England]]
– Data value
• E.g. London  [[Population: 7,421,328]]
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17. Properties
• Predefined Properties
• Custom Properties
– Declare Properties
• Property Namespace
– E.g. Property: Population
• Define property’s type with has type: attribute
– Possible data types: “String”, “Date”, “Geographic Coordinate”,
“URL”
– E.g. Population  [[has type: Number]]
• Units Definition, Value validation, Property Hierarchy,
etc.
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18. OWL Conversion
• OWL/RDF
– Wiki Page = OWL abstract entity
– Property = OWL property
– Category = OWL class
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19. Example
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Text written with MediaWiki
Text written with Semantic MediaWiki

20. Querying
– Query results and output as part of the wiki
text
– #ask function
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 Query Condition
 Output Values
{{#ask:
[[Category:City]] [[located in::Germany]]
| ?population | ?area#km² = Size in km²
}}

21. Export
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22. What can you do?
• Research
– Data extraction techniques
– Ontologies
• Pass a message
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23. Web 3.0?
• People keep asking what Web 3.0 is. I think
maybe when you've got an overlay of scalable
vector graphics – everything rippling and
folding and looking misty – on Web 2.0 and
access to a semantic Web integrated across a
huge space of data, you'll have access to an
unbelievable data resource ...
Tim Berners-Lee, 2006
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24. Questions?
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