1. Collective Cognition with Semantic
Mediawiki: Lessons and Experiences
Jie Bao, Li Ding and James Hendler
Tetherless World Constellation,
Department of Computer Science
Rensselaer Polytechnic Institute,
Troy, NY, USA
{baojie,dingl,hendler}@cs.rpi.edu
Network-Enabled Cognition workshop, ACITA, 2009 Sep 22, 2009, UMUC, Maryland

2. Goal
• To identify a few common pitfalls and
limitations of Semantic Mediawiki in
– knowledge modeling,
– Knowledge organization and context, and
– Collaboration protocols
• To examine some potential approaches to
solve these problems.
2

3. Wiki and Recognition
• Wiki is among the most prominent of forms on
the Web that harness the distributed, collective
efforts of users to create content online.
– Ideas are formed, indentified or evolved and
– Facts are discovered, refined or removed (for
“wrong” ones)
In the course of a never-ending editing process.
3

4. Collective Cognition
• A hypothetical example: write an outline
for a new South Park episode.
Picture courtesy of Wikipedia
4

5. Collective Cognition
• 9:00pm: show starts
• 9:01pm: Wikipedia page for the episode is created
• 9:01-9:08pm: 10 active users are adding summary when they watch
• 9:08-9:10pm: ad time, some minor reorganization and typo fixing.
• 9:10-9:30pm: repeat the above
• 9:30-10:30pm: a user A is doing major refining, e.g. adding culture
references
• 10:31pm: a user B disagrees with A, undo A’s edit
• 10:32pm: A undos B’s edit
• 10:33pm: B leaves a message on A’s user page, to avoid further edit wars
• 10:43pm: the two agrees to compromise with wording such that “It is implied
that Chef is dead at the end of the episode; however, some others believe
that it is not the case”.
• The next day: user C adds a citation to this South Park episode’s page on a
film’s page with that “South Park episode X is a parody of the this film”.
5

6. Key elements
• Simplicity: least training required to
contribute.
• AAA: anybody can say anything anywhere
• NPOV: neutral point of view (among other
collaboration protocols of Wikipedia)
6

7. Semantic Wiki
• Extensions to Wikis with some Semantic
Web support
– Example: Semantic Mediawiki
Eric Cartman
[[friend of::Butters]] Butters
[[Category:Boy]]
friend of
Cartman
Eric_Cartman friend_of Butters
Eric_Cartman rdf:type Boy
(RDF triple)
7

8. Semantic Wiki
• Fast-growing adoption
– Healthcare
– E-Government
– Entertainment
– Consulting
– Database
– …
• Inside ITA
– OWL modeling with controlled natural language
– Rule modeling
8

9. Semantic Wiki
• Can Semantic wiki reproduces the success of
wiki to be among the most prominent of forms on
the Web that harness the distributed, collective
efforts of users to create content knowledge
online?
• We have seen encouraging success in quite a
few projects
• However, some issues are identified in our real-
world experiences.
9

10. Knowledge Modeling
• Myth: users can do RDF-style (triple-
based) modeling on SMW
• Fact: few is able to do this (at least without
substantial training)
10

11. “Big Fat Page” effects
We gave a 3 hour training on SMW with a group of
undergraduate students (most with no knowledge of
RDF), and let them do a collective annotation task on TV
shows. However, the result is not fully satisfactory
• Difference between categories and properties is not that easy to
understand (see a lot misuse like Category:hug)
• To describe a thing with triples requires “thinking in RDF”, which
needs some experiences.
• It is a big headache to choose the right vocabulary and it is hard to
know what vocabulary to reuse.
As a result, many of the testees simply use the wiki as a notepad,
without adding much semantic annotations, resulting in a long single
“usual” wiki page.
11

12. Schema or not schema?
• Two common knowledge models on a semantic wiki,
– “Schema”-based modeling, often represented in the form of pre-
defined wiki templates, that are used by “common” users of the
wiki to access data via forms or prebuilt queries.
• c.f. “infobox” in Wikipedia
• =>stable, shared knowledge
– Arbitrary RDF-style semantic markup - heavily used by a
selected few elite group
• => less structured, less shared knowledge
• A carefully pre-populated wiki “schema” (template), is as
important as a schema in a database project.
12

13. Template Example
Template as Schema Form for the template
13

14. Organization and Context
• Myth: semantic wiki, like wiki, allows you
to write things freely.
• Fact: SMW does not support AAA
– Every “triple” has to be on its subject’s page.
• E.g., “South Park episode X is a parody of the this
film” can only be said on X’s page.
– Each subject and property of a triple must be
a local page name.
14

15. Organization and Context
Why it may be problematic?
• May require the creation of many trivial, small pages.
• Is troublesome to describe things (e.g., an external URL)
that have no corresponding wiki pages.
• Discourages users due to the difficulty of determining
where to write knowledge (i.e., the best “subject” pages).
• Many users are confused of query-based pages: they do
not know how to track the source of the queried results
when they want to change a query-based page.
15

16. Organization and Context
Potential Solution
• Extending the SMW syntax
– [[Cartman::friend of::Butters]]
• Introducing a context model to SMW
– Context: Where, Who, When
– No more need to use the subject to locate a triple
16

17. Collaboration Protocol
• Myth: semantic wiki, as wiki always does,
allows compromises between different
points of view.
• Fact: Semantic wiki only allows one
version of the (semantic) “truth”.
– A triple can not be both true and not true
17

18. Ontology War
No! Cartman is
only a Fictional
Character
Cartman is a
Boy
http://www.gambling911.com/files/publisher/cat-fight-032609L.jpg
Collaboration Protocol Support Needed!
18

19. Collaboration Protocol
• Avoid edit wars in Wikipedia
– NPOV: allows multiple points
of view co-exist on one page
verifiable sources.
– natural language text can
accommodate and explain
multiple points of view on a
single page
19

20. Collaboration Protocol
Two possible approaches
• To have categories and typed links optionally
contextualized by authors, similar to the tag
contextualizing mechanism in delicious and flickr.
– http://example.com/author/term (contextualized name)
– http://example.com/term (non-contextualized name)
• To introduce a context model of SMW knowledge
statements, so that different versions of truth may be
formally represented with explicitly given sources.
20

21. Conclusions
• Modeling in SMW can be regarded as an evolving
cognition process and schema-based modeling is useful.
• We showed that a context/provenance model is needed
for SMW to support better knowledge organization
• Collaboration protocols: to accommodate two versions of
a fact, provenance of a term and/or triple should be
traceable.
21

22. Solution Summary
• Simplicity: improve user interaction using
forms and templates (schema).
• AAA: Context model
– On-going work: “Semantic History”
• NPOV: Enabled by the context model
22