Download - SEMANTIC WEB, OWL & PROTÉGÉ Matthew J Wood CS 570 – Topics in Artificial Intelligence Spring 2013
SEMANTIC WEB, OWL & PROTÉGÉ
Matthew J Wood
CS 570 – Topics in Artificial Intelligence
Spring 2013
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Today’s Web
Most of today’s Web content is suitable for human consumption Even Web content that is generated automatically from
databases is usually presented without the original structural information found in databases
Typical Web uses today people’s seeking and making use of information, searching for and getting
in touch with other people, reviewing catalogs of online stores and ordering products by filling out forms
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Keyword-Based Search Engines
Current Web activities are not particularly well supported by software tools Except for keyword-based search engines (e.g.
Google, AltaVista, Yahoo) The Web would not have been the huge
success it was, were it not for search engines
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Problems of Keyword-Based Search Engines
High recall, low precision. Low or no recall Results are highly sensitive to vocabulary Results are single Web pages Human involvement is necessary to interpret
and combine results Results of Web searches are not readily
accessible by other software tools
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The Key Problem of Today’s Web
The meaning of Web content is not machine-accessible: lack of semantics
It is simply difficult to distinguish the meaning between these two sentences:
I am a professor of computer science.
I am a professor of computer science, you may think. Well, . . .
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The Semantic Web Approach
Represent Web content in a form that is more easily machine-processable.
Use intelligent techniques to take advantage of these representations.
The Semantic Web will gradually evolve out of the existing Web, it is not a competition to the current WWW
What is Semantic Web? Semantic web is a term used more specifically
to refer to format and technologies that enable it.
It defines the collection, structuring and recovery of linked data that are enabled by the technologies that provide a formal description of concepts, terms, and relationships within a given knowledge domain.
What is Semantic Web? Sematic Web is the extension of the World Wide
Web that enables people to share content beyond the boundaries of applications and websites
Semantic web was term coined by Tim Berners-Lee, the inventor of World Wide Web and the director of the World Wide Web Consortium.
He defines it as “a web of data that can be processed directly and indirectly by machines .
Why Semantic Web?
Semantic Web is about common formats for integration and combination of data from diverse sources.
Secondly, it is about language for recording the relationship data and the real world objects.
Semantic Web Components Resource Description Framework (RDF) RDF Schema (RDFS) Simple Knowledge Organization System
(SKOS) SPARQL, an RDF query language Notation3 (N3) N-Triples Turtle (Terse RDF Triple Language) Web Ontology Language (OWL)
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Explicit Metadata
This representation is far more easily processable by machines
Metadata: data about data Metadata capture part of the meaning of data
Semantic Web does not rely on text-based manipulation, but rather on machine-processable metadata
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On HTML
Web content is currently formatted for human readers rather than programs
HTML is the predominant language in which Web pages are written (directly or using tools)
Vocabulary describes presentation
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An HTML Example<h1>Agilitas Physiotherapy Centre</h1>Welcome to the home page of the Agilitas Physiotherapy Centre. Do you feel pain? Have you had an injury? Let our staff Lisa Davenport,Kelly Townsend (our lovely secretary) and Steve Matthews take careof your body and soul.<h2>Consultation hours</h2>Mon 11am - 7pm<br>Tue 11am - 7pm<br>Wed 3pm - 7pm<br>Thu 11am - 7pm<br>Fri 11am - 3pm<p>But note that we do not offer consultation during the weeks of the <a href=". . .">State Of Origin</a> games.
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Problems with HTML
Humans have no problem with this Machines (software agents) do:
How distinguish therapists from the secretary, How determine exact consultation hours They would have to follow the link to the State Of
Origin games to find when they take place.
XML (eXtended Markup Language)
A better representation of data XML is a flexible text format that is widely
used to structure, store, and transport data. XML is different from HTML because it is not
about displaying data. In XML (differently from HTML) you create
your own tags to annotate data. XML is used to create other languages such
as: XHTML, RSS, RDF, OWL, etc.15
An XML Example
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<bookstore> <book category="COOKING"> <title lang="en">Everyday Italian</title> <author>Giada De Laurentiis</author> <year>2005</year>
<price>30.00</price> </book> <book category="CHILDREN">
<title lang="en">Harry Potter</title> <author>J K. Rowling</author>
<year>2005</year> <price>29.99</price>
</book></bookstore>
RDF (Resource Description Framework)
RDF: a standard for describing resources on the Web The meaning of data is encoded in sets of triples. Triples are “subject, predicate, object” statements. Each element of a triple is identified by a URI. URIs represent both resources and relations. RDF is written in XML RDF is to Semantic Web what HTML was to the Web.
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Harry Potter has as author J. K. Rowling.
An RDF Example
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http://en.wikipedia.org/wiki/J._K._Rowling
http://en.wikipedia.org/wiki/ Harry_Potter
dc:creator
<rdf:RDF xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns# xmlns:dc=http://purl.org/dc/elements/1.1/> <rdf:Description rdf:about=“http://en.wikipedia.org/wiki/Harry_Potter”> <dc:creator=“http://en.wikipedia.org/wiki/J._K._Rowling”> </rdf:Description></rdf:RDF>
Ontologies and OWL
An ontology is an explicit description of things and their relations.
OWL serves to write ontologies for the Web. OWL is written in XML and built on top of RDF. You can think of OWL as an object-oriented
language that defines classes, hierarchy of classes, attributes, relations, etc.
OWL is designed to support inference (subsumption and classification)
OWL is more expressive than RDF.19
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Typical Components of Ontologies
Terms denote important concepts (classes of objects) of the domain e.g. professors, staff, students, courses, departments
Relationships between these terms: typically class hierarchies a class C to be a subclass of another class C' if every object in C
is also included in C' e.g. all professors are staff members
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Further Components of Ontologies
Properties: e.g. X teaches Y
Value restrictions e.g. only faculty members can teach courses
Disjointness statements e.g. faculty and general staff are disjoint
Logical relationships between objects e.g. every department must include at least 10 faculty
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Example of a Class Hierarchy
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The Role of Ontologies on the Web
Ontologies provide a shared understanding of a domain: semantic interoperability overcome differences in terminology mappings between ontologies
Ontologies are useful for the organization and navigation of Web sites
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The Role of Ontologies in Web Search
Ontologies are useful for improving the accuracy of Web searches search engines can look for pages that refer to a precise concept
in an ontology
Web searches can exploit generalization/ specialization information If a query fails to find any relevant documents, the search engine
may suggest to the user a more general query. If too many answers are retrieved, the search engine may
suggest to the user some specializations.
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Web Ontology Languages (2)
OWL A richer ontology language relations between classes
e.g., disjointness cardinality
e.g. “exactly one” richer typing of properties characteristics of properties (e.g., symmetry)
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Software Agents
Software agents work autonomously and proactively They evolved out of object oriented and compontent-based
programming
A personal agent on the Semantic Web will: receive some tasks and preferences from the person seek information from Web sources, communicate with other
agents compare information about user requirements and preferences,
make certain choices give answers to the user
A Semantic Web Primer 27
Intelligent Personal Agents
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Semantic Web Agent Technologies
Metadata Identify and extract information from Web sources
Ontologies Web searches, interpret retrieved information Communicate with other agents
Logic Process retrieved information, draw conclusions
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Drawbacks of XML
XML is a universal metalanguage for defining markup It provides a uniform framework for interchange of data
and metadata between applications However, XML does not provide any means of talking
about the semantics (meaning) of data E.g., there is no intended meaning associated with the
nesting of tags It is up to each application to interpret the nesting.
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Requirements for Ontology Languages
Ontology languages allow users to write explicit, formal conceptualizations of domain models
The main requirements are: a well-defined syntax efficient reasoning support a formal semantics sufficient expressive power convenience of expression
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Tradeoff between Expressive Power and Efficient Reasoning Support
The richer the language is, the more inefficient the reasoning support becomes
Sometimes it crosses the border of noncomputability
We need a compromise: A language supported by reasonably efficient
reasoners A language that can express large classes of
ontologies and knowledge.
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Reasoning About Knowledge in Ontology Languages
Class membership If x is an instance of a class C, and C is a
subclass of D, then we can infer that x is an instance of D
Equivalence of classes If class A is equivalent to class B, and class B is
equivalent to class C, then A is equivalent to C, too
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Reasoning About Knowledge in Ontology Languages (2)
Consistency X instance of classes A and B, but A and B are
disjoint This is an indication of an error in the ontology
Classification Certain property-value pairs are a sufficient
condition for membership in a class A; if an individual x satisfies such conditions, we can conclude that x must be an instance of A
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Uses for Reasoning
Reasoning support is important for checking the consistency of the ontology and the knowledge checking for unintended relationships between classes automatically classifying instances in classes
Checks like the preceding ones are valuable for designing large ontologies, where multiple authors are involved integrating and sharing ontologies from various sources
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Reasoning Support for OWL Semantics is a prerequisite for reasoning support Formal semantics and reasoning support are usually
provided by mapping an ontology language to a known logical formalism using automated reasoners that already exist for those
formalisms OWL is (partially) mapped on a description logic, and
makes use of reasoners such as FaCT and RACER Description logics are a subset of predicate logic for
which efficient reasoning support is possible
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Three Species of OWL
W3C’sWeb Ontology Working Group defined OWL as three different sublanguages: OWL Full OWL DL OWL Lite
Each sublanguage geared toward fulfilling different aspects of requirements
OWL DL OWL DL is so named due to its
correspondence with description logic. Description logic (DL) is a family of formal
knowledge representation languages. It is more expressive than propositional logic
It models concepts, roles and individuals, and their relationships
It is used in AI for formal reasoning on the concept of application domain known as Terminological knowledge
Protege Tutorial
What is protege?
Protege is a free, open-source platform to construct domain models and knowledge-based applications with ontologies.
Ontologies range from taxonomies, classifications, database schemas to fully axiomatized theories.
Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce and web services
What can you do with Protégé?
Create a new ontology from scratch Download and extend an existing ontology Export ontologies in a variety of formats
OWL RDF XML Schema
How it works
Objects in the domain are expressed through a series of interrelated classes
Class hierarchy is similar to that used by object-oriented languages such as Java Superclasses Subclasses Sibling Classes Ancestor Classes, etc.
Heavy reliance on inheritance Unlike Java, Protégé supports multiple inheritance
Individuals and Properties
Individual domain objects are expressed as class members
Class members have object properties that relate them to members of the same class or other classes
Also have data properties Expressed by data type – integer, String, etc. If particular data property does not fit a predefined
data type it can be entered as text Ex. Members of the class Soccer_Players have ‘has
fanpage’ data property that is expressed as a URL
Annotations
Provide definitions and comments on the ontology and its contents
Can provide annotations for the entire ontology, a specific class, a member of a class, etc.
How It Works (cont.)
Using Protégé in conjunction with GraphViz software allows users to view the ontology as a semantic network
Protégé relies on semantic reasoners to implement description logic
Semantic Reasoners
Inference engine for description logics Inference process is carried out via forward
and backward chaining Protégé supports various reasoners such as
FaCT++ and HermiT
FaCT++
Semantic reasoner used for OWL DL ontologies
Implemented in C++ and supported by Protege
Converts the KB into an internal representation using various optimization techniques
Uses dependency directed backtracking to check satisfiability of the KB
Install Protege
Go to http://protege.stanford.edu/doc/owl/getting-started.html to download protege (version 3.x)
Protege OWL editor is built with the full installation of protege platform. During the install process, choose the “Basic+OWL” option.
For more details: http://protege.stanford.edu/doc/owl/getting-started.html
Protege There are two main ways of modelling ontologies:
Frame-based OWL
Each has its own user interface Protege Frames editor: enables users to build and populate ontologies that
are frame-based, in accordance with OKBC (Open Knowledge Base Connectivity Protocol). Classes Slots for properties and relationships Instances for class
Protege OWL editor: enables users to build ontology for the Semantic Web, in particular to OWL Classes Properties Instances reasoning
Building an OWL Ontology
E2: Create a new OWL project Start protege File – New Project – OWL/RDF files – Ontology
URI (http://www.pizza.com/ontologies/pizza.owl) – OWL DL – Properties View
A new empty Protege-OWL project has been created.
Save it in your local file as pizza.owl
Named Classes
Go to OWL Classes tab The empty class tree contains one class called owl:Thing,
which is superclass of everything. E3: Create subclasses Pizza, PizzaTopping and
PizzaBase. They are subclasses of owl:Thing. Naming convention
no special naming convention consistency
Disjoint classes
E4: How to say that Pizza, PizzaTopping and PizzaBase classes are disjoint.
1. Select the class Pizza
2. Press “add siblings” button on the disjoint classes widget
3. Add PizzaBase and PizzaTopping
4. Select the class PizzaTopping,
5. Add Pizza and PizzaBase to the disjoint class
E5: Create group of classes
Create ThinAndCrisyBase and DeepPanBase as the subclasses of PizzaBase, and each of them are disjointed.
Select PizzaBase, right click the mouse, select “create subclasses”
Follow the wizard to create these two disjoint classes.
It will save lots of time when there is need to create lots of disjoint classes.
E6: Create some subclasses of PizzaTopping
Select PizzaTopping, Create subclaesses as MeatTopping, VegetableTopping,
CheeseTopping and SeafoodTopping. Make sure that these classes are disjoint to each other.
Select the class MeatTopping, Add disjoint subclasses: SpicyBeefTopping,
PepperoniTopping, SalamiTopping and HamTopping
Select VegetableTopping: Add disjoint subclasses: TomatoTopping, OliveTopping,
MushroomTopping, PepperTopping, OnionTopping, CaperTopping
E6: Creating disjoint subclasses
Select PepperTopping Add disjoint subclasses: RedPepperTopping,
GreenPepperTopping, JalapenoPepperTopping Select CheeseTopping
Add disjoint subclasses: MozzarellaTopping, ParmezanTopping
Select SeafoodTopping Add disjoint subclasses: TunaTopping,
AnchovyTopping and PrawnTopping
OWL Properties
OWL Properties represent relationships between two objects.
There are two main properties: Object properties: link object to object datatype properties: link object to XML Schema
datatype or rdf:literal OWL has another property – Annotation
properties, to be used to add annotation information to classes, individuals, and properties
E7: Create an object property
Switch to the “Properties” tab, Use “Create Object Property” button to create
a new object property. Rename it to hasIngredient
E8: Creating sub-properties
Select hasIngredient property Add hasTopping and hasBase as the
subproperties
Inverse Properties
Each object property may have a corresponding inverse property.
If some property links individual a to individual b, then its inverse property will link individual b to individual a.
E9: Create inverse properties Create a new object property called isIngredientOf
Press “Set inverse property” button, Select “hasIngredient” Then the inverse relation has been set up.
Select hasBase Create the isBaseOf as the inverse property of hasBase isBaseOf is the subproperty of isIngredientOf
Select hasTopping create isToppingOf as the inverse property. isToppingOf is the subproperty
of isIngredientOf
Functional Properties
If a property is functional, for a given individual, there can only be at most one individual to be related via this property. For a given domain, range must be unique
Functional properties are also known as single valued properties.
Inverse Functional Properties
If a property is inverse functional, then its inverse property is functional. For a given range, domain must be unique.
Functional vs. inverse functional properties
FunctionalProperty vs InverseFunctionalProperty
domain range example
Functional
Property
For a given domain
Range is unique
hasFather: A hasFather B, A hasFather C B=C
InverseFunctionalProperty
Domain is unique
For a given range
hasID: A hasID B, C hasID B A=C
Transitive Properties
If a property is transitive, and the property related individual a to individual b, and also individual b to individual c, then we can infer that individual a is related to individual c via property P.
Symmetric Properties
If a property P is symmetric, and the property relates individual a to individual b, then individual b is also related to individual a via property P.
E10: Make the hasIngredient property transitive
Select the hasIngredient property Tick the transitive tick box Select the isIngredientOf property, make sure
that the transitive tick box is ticked.
E11: Make the hasBase property functional
Select the hasBase property Tick the “functional” tick box OWL-DL does not allow datatype properties
to be transitive, symmetric or have inverse properties.
Property domains and ranges
Properties link individuals from the domain to individuals from the range.
OWL uses domain and range as axioms in reasoning.
E12: Specify the range of hasTopping
Select hasTopping Press range button Select PizzaTopping Press OK button PizzaTopping should be displayed in the range
list. When multiple classes are added to the
range, they represent the union of all classes.
E13: Specify Pizza as the domain of the hasTopping property
Select hasTopping property Press add domain button Select Pizza Press OK Pizza is displayed in the domain list.
When multiple classes are added as domain, they represent as the union of these classes.
E14: Specify the domain and range for the isToppingOf property
Select the isToppingOf property Set the domain of the isToppingOf property to
PizzaTopping Set the range of the isToppingOf property to
Pizza.
E15: Specify the domain and range for the hasBase property and its inverse property isBaseOf
Select the hasBase property Specify the domain as Pizza Specify the range as PizzaBase
Select the isBaseOf property Specify the domain as PizzaBase Specify the range as Pizza
Property restrictions
In OWL, properties are used to create restrictions. Restrictions are used to restrict the individuals that
belong to a class Three restrictions:
Quantifier restrictions Existential quantifier ( ) Universal quantifier ( )
Cardinality restrictions hasValue restrictions
E16: Add a restriction to Pizza
Add a restriction to Pizza that specifies a Pizza must have a PizzaBase Select Pizza Select Necessary header to create a necessary
condition Select create a restriction wizard
Select hasBase as restricted property Select someValueFrom as restriction Put PizzaBase into the filler
Add a restriction to Pizza
E18: Creating different kinds of Pizzas
Create a subclass of Pizza called NamedPizza, and a subclass of NamedPizza called MargheritaPizza.
Add comment to MargheritaPizza: A pizza that only has Mozarella and Tomato toppings
E19: Adding restrictions to MargheritaPizza
To specify that MargheritaPizza has at least one MozzarellaTopping. Select MargheritaPizza Go to “Asserted Conditions”, create new restriction. Select someValueFrom Select hasTopping as the property to be restricted. Enter MozzarellaTopping as the filler Press OK button
E20: Adding restrictions to MargheritaPizza
To specify that MargheritaPizza has at least one TomatoTopping. Select MargheritaPizza Go to “Asserted Conditions”, create new restriction. Select someValueFrom Select hasTopping as the property to be restricted. Enter TomatoTopping as the filler Press OK button
E21: Create AmericanPizza
Create AmericanPizza with toppings of pepperoni, mozzarella and tomato.
Through cloning and modifying the description of MargheritaPizza. Select MargheritaPizza Select create clone Add additional restriction to AmericanaPizza
Adding PepperoniTopping Press OK.
E22: Create an AmericanHotPizza and a SohoPizza
An AmericanHotPizza is almost the same as an AmericanaPizza, but has JalapenoPepperTopping on it.
A SohoPizza is almost the same as a MargheritaPizza, but has additional OliveTopping and ParmezanTopping
E23: Make subclasses of NamedPizza disjoint from each other
Select MargheritaPizza Press “add all siblings” button on the
“Disjoints widget” to make the pizzas disjoint from each other.
Using a reasoner Ontology described in OWL-DL can be processed by a reasoner.
Go to owl—preference, to make sure that OWL-DL is selected. The main services offered by a reasoner is to test whether or not
one class is a subclass of another class. By performing such tests on all of the classes, it is possible for a
reasoner to compute the inferred ontology class hierarchy. Another reasoning service is consistency checking – to check
whether or not it is possible for the class to have any instances. A class is deemed to be inconsistent if it cannot possibly have
any instances.
Using Racer
In order to reason over the ontology in Protege-OWL, a DIG compliant reasoner should be installed and started.
In this example, we use Racer, Download at:
http://www.racer-systems.com/products/download/index.phtml
Double click RacerPro to start Racer.
Invoking the reasoner Having started Racer, the ontology can be sent to the reasoner
to automatically compute the classification hierarchy, and also check the logical consistency of the ontology.
In Protege, the manually constructed class hierarchy is called the asserted hierarchy. The automatically computed by the reasoner is called the inferred hierarchy.
Go to OWL – classify taxonomy – to invoke the reasoner If a class has been reclassified, then the class name will appear
in a blue color in the inferred hierarchy. Go to OWL – Check consistency – to invoke the reasoner
If a class has been found to be inconsistent, it’s icon will be circled in red color.
Computing the inferred class hierarchy is also known as classifying the ontology.
Invoke the reasoner
E24: Inconsistent classes
In order to demonstrate the use of the reasoner to detect inconsistencies in the ontology, we will create a class ProbeInconsistentTopping, Which is the subclass of CheeseTopping Select ProbeInconsistentTopping, go to asserted condition to
add named classes, select VegetableTopping and then press OK.
Go to OWL – check consistency
E25: Classify the ontology again To see ProbeInconsistentTopping is
inconsistent.
E26: Remove the disjoint statement
Between CheeseTopping and VegetableTopping to see what happens Select CheeseTopping Go to Disjoint part Select VegetableTopping, right click and “Delete
the selected row”. Classify taxonomy The inconsistency no longer exists.
E27: Fix the ontology
By making CheeseTopping and VegetableTopping disjoint from each other.
SPORTS ONTOLOGICAL EXTENSION IN PROTÉGÉ
Project #1
Used Protégé to extend a general sports ontology (sptcsem.owl)
Focused on adding classes, individuals, and properties related to the game of soccer
Used Fact++ for DL queries