Coupling SMW with MASTRO Thesis

Coupling Semantic MediaWiki with
MASTRO
Student: Albin Ahmeti
Advisor: Prof. Maurizio Lenzerini
Master thesis 26/01/2011

Outline
• Mediawiki
•Semantic Mediawiki (SMW)
• Coupling SMW with MASTRO
•SMWQuonto Control Panel
• Conclusion
• Future work
Coupling SemanticMediaWiki with MASTRO 2

MediaWiki
• MediaWiki (abbr. MW) is a free server-based software, licensed under the
GNU General Public License, which runs Wikipedia
• It has been widely used in a lots of companies as a content-management
system, it provides fast page processing and short request time
• PHP & Mysql in backend
• It manages content mirroring, concurrent and conflicting page edits
between users
• The articles in Wikipedia are consisted of wiki text, which is actually, a
bunch of plain text and a kind of lightweight markup language

MediaWiki (cont.)
• Creating pages is simplified to minimum, one has just to type “[[Title]]”
and then type the content, e.g. creating a wiki page titled “Rome”,
[[Rome]]

MediaWiki (cont. )
• It distinguishes between pages using namespaces
• Main:
• User:
• Help:
• Talk:
• Usage of templates:
• Transclusion -> {{Template name}}
• Substitution -> {{subst:Template name}}

Semantic MediaWiki
• Semantic MediaWiki (abbr. SMW) is the most popular platform to date
that encodes semantic data to the wiki articles
• Introduces some basic syntax, a sort of metadata that is machine
processable for each of the page constructs (link types)
• SMW is built on top of MediaWiki (MW), it has been developed using
the same technology as MW, i.e. tight coupling

Semantic MediaWiki
• Annotation of pages
Is page-centric oriented:
 Categories
 Properties
 Attributes

Semantic MediaWiki
•Categories
 Are used to classify pages for better retrieval and organization
 Correspond to Classes in OWL DL
[[Category:City]] [[Category:Holy cities]]
•Sub-categories
 Same notation, but defined in the namespace Category:
 Class inclusion in OWL DL -> Intensional knowledge
 Holy Cities ⊑ City

Semantic MediaWiki
• Properties
 Link types (relations) between wiki pages, i.e. hyperlinks
 Correspond to OWL Object Property
Rome is capital of [[Italy]]
Rome is capital of [[capital of::Italy]]
• Subproperties
 are defined in the namespace Property:
 [[subproperty of::Property:Located In]]
 capital of ⊑ Located In

Semantic MediaWiki
•Attributes
 Relations between a wiki page and a datatype
Rome has population 2,700,000.
Rome has population [[population::2,700,000]]
A property can be changed to an attribute, by giving a meaningful datatype
in Property namespace:
[[Has type::number]]
Attributes in wiki pages correspond to OWL Data Type Property, Annotation
Property and Object Property

Semantic MediaWiki
•Querying in SMW (inline queries)
{{#ask: [[Category:City]] [[Located in::Italy]]
|?Population
|?Area
|sort=Population, Area
|order=descending, ascending
}}

Semantic MediaWiki
{{#ask: [[Category:Student]][[degree::!Sapienza]] [[age::>24]][[age::<30]]
|?name
|?surname
|?age
}}
CWA -> easy to evaluate
OWA -> not easy to evaluate, ontology does not have complete information

Semantic MediaWiki
• Architecture of SMW

Semantic MediaWiki
SMW has
• rather limited expressivity
• no disjoint classes
• no disjoint properties
• no functionalities
• no inverses
• query language that does not allow joins and explicit variables
What, if we add more expressivity and keep the reasoning tasks (query answering) polynomial
?

Our approach
•We use QuOnto as a reasoner
• Use expressivity of DL-Lite, reasoning tasks are polynomial wrt to the size
of the ontology:
 query answering
 subsumption
 ontology satisfiability
 instance checking
• Use Union of Conjunctive Queries (UCQs) for posing queries
 can express joins
 allow variables
 coincide with SELECT-PROJECT-JOIN SQL queries
 LOGSPACE wrt to the data complexity

Our approach
• DL-Litecore
B → A | ∃R R → P | P −
C → B | ¬B E → R | ¬R
B ⊑ C
A denotes an atomic concept, P an atomic role and P − its inverse.
B denotes a basic concept, R is a basic role
A(a) P (a, b)
DL-LiteF
(funct R)
DL-LiteR
R ⊑ E

Our approach
•Architecture

Exploration vs. Exploitation 18

Our approach
Besides, we added four types of assertions, not available in SMW:

Our approach
Coupling SemanticMediaWiki with Mastro 20

Our approach
DL-Lite vs OWL DL interpretation of SMW annotations

Our approach
•Query translation
• query translation from #ask to function free positive LP (logic
programming) rules, obtaining minimal Herbrand model
semantics in the process, based on JieBao et al. (captures
SMW 1.4.2)
 n-ary predicates removed
 Adjustments (tunings) to deal with latest SMW 1.5.x
(mainly code-based)

Our approach
Translation from SMW-QL to Logic Program, as defined in the paper
“Knowledge Representation and Query in Semantic MediaWiki: A Formal Study”-JieBao et al.

Our approach
1) map query annotations to Logic counterparts (based on schema)
2) Replace body atoms
3) Perform Depth-First-Search on rules

Our approach
{{#ask: [[Category:Student]]
[[enrolled in:: <q>[[Category:Sapienza]]</q> || DIS]] }}
Q(x) :- L(x)
L(x) :- A1(x) ,A2(x)
A1(x) :- Student(x)
A2(x) :- enrolledIn(x, y), N(y) ... (1)
N(x) :- Sapienza(x)
N(x) :- x:=DIS

Our approach
Replace body of the queries with head definitions (occurring once)
Q(x):- Student(x), enrolledIn(x, y), N(y)
N(x):- Sapienza(x)
N(x):- x:=DIS … (2)

Our approach
• Apply Depth First Search (DFS) on rules (2):
Q(x):- Student(x), enrolledIn(x, y), N(y)
N(x):- Sapienza(x) N(x):- x:=DIS

Our approach
After applying DFS, we got Union Of Conjunctive Queries (UCQs):
Q(x):-Student(x), enrolledIn(x, y), Sapienza(y)
Q(x):-Student(x), enrolledIn(x, ‘DIS’)

Our approach
{{#ask: [[Category:Student]]
[[enrolled in:: <q>[[Category:Sapienza]]</q> || DIS]] }}
• It returns all students that are in class Sapienza, and all its subclasses
(research centers, affiliations, etc.)
• This is fulfilled thanks to the PerfectRef, implemented in QuOnto, so no
special algorithm needed!

SMWQuonto Control Panel
DBMS
it manages ABox
XML file
manages TBox

Semantic data
pushed to QuOnto

AskQL query
posed to QuOnto.
UCQs obtained
Results

Conclusion
•We managed to create a system, which offers a higher level of expressivity,
than the one offered by SMW, by maintaining complexity polynomial
• It can deal with a hundred thousands of pages (instances), e.g. Wikipedia
•We have more expressive query language – UCQ
– Constraining !, <, >, ~ , which can be dealt as well imposing EQL constraints on UCQ –
SparSQL
– Any extension in expressivity of askQL query language, makes the complexity NP-hard
• It is meant to be “proposal” for alternative triple-store used in SMW
• It can be considered as a SMW extension

Future work
• Use SparSQL query language in order to deal with special constructs (!, <, >,
∼), hence by fully capturing the askQL queries.
• Provide a more scalable coupling between the two architectures, e.g.,
SOAP and Web Services
• Grab semantic data from more than one page, using RDF/XML output
• Grab category hierarchy at once, thus by having the taxonomy of the ontology

Questions ?

Coupling SMW with MASTRO Thesis

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