Transcript Introduction

A Practical
Introduction to
Ontologies & OWL
Alan Rector
O p e n G A LE N
BioHealth
Informatics
Group
1
Copyright © 2005 Univ. of Manchester
Speakers
►Alan Rector – Medical Informatics
►Robert Stevens - BioInformatics
►Sean Bechhofer – OntoGrid, COHSE
►Matthew Horridge – CO-ODE
►Nick Drummond – CO-ODE
►Jeremy Rogers - OpenGALEN
►Daniele Turi – IMG, Instance Store
►Katy Wolstencroft – Phosphabase, mygrid
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Copyright © 2005 Univ. of Manchester
Overview (day 1)
►Introduction and Motivation
►plus example app
►OWL Language Overview
►The Web Ontology Language and constructs
►Hands On: Protégé-OWL 1
►Constructing a taxonomy and introduction to reasoning
►Knowledge acquisition
►Elicitation methodologies
►Q&A
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Overview (day 2)
►Ontology Engineering
►Hands On: Protégé-OWL 2
►Using a reasoner for computing a classification
►Formal Modelling Issues
►Why classify?
►Untangling
►Applications
►Architecture and case studies
►Q&A, Open Discussion
►Feedback
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The Car
5
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The Car
Automobile
Voiture
Coche
Araba
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Hard Work using the
Syntactic Web…
Find images of Peter Patel-Schneider, Frank van
Harmelen and Alan Rector…
Rev. Alan M.
Gates,
Associate
Rector of the
Church of the
Holy Spirit, Lake
Forest, Illinois
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Impossible (?) using the
Syntactic Web…
► Complex queries involving background knowledge
► Find information about “animals that use sonar but are not either bats
or dolphins”, e.g., Barn owl
► Locating information in data repositories
► Travel enquiries
► Prices of goods and services
► Results of human genome experiments
► Finding and using “web services”
► Visualise surface interactions between two proteins
► Delegating complex tasks to web “agents”
► Book me a holiday next weekend somewhere warm, not too far
away, and where they speak French or English
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What is the Problem?
Consider a typical web page:
Markup consists of:
rendering
information (e.g.,
font size and
colour)
Hyper-links to
related content
Semantic content is
accessible to humans
but not (easily) to
computers…
9
Copyright © 2005 Univ. of Manchester
What information can we
see…
WWW2002
The eleventh international world wide web conference
Sheraton waikiki hotel
Honolulu, hawaii, USA
7-11 may 2002
1 location 5 days learn interact
Registered participants coming from
australia, canada, chile denmark, france, germany, ghana, hong kong, india,
ireland, italy, japan, malta, new zealand, the netherlands, norway, singapore,
switzerland, the united kingdom, the united states, vietnam, zaire
Register now
On the 7th May Honolulu will provide the backdrop of the eleventh international
world wide web conference. This prestigious event …
Speakers confirmed
Tim berners-lee
Tim is the well known inventor of the Web, …
Ian Foster
Ian is the pioneer of the Grid, the next generation internet …
10
Copyright © 2005 Univ. of Manchester
What information can a
machine see…
WWW2002
The eleventh international world wide web
conference
Sheraton waikiki hotel
Honolulu, hawaii, USA
7-11 may 2002
1 location 5 days learn interact
Registered participants coming from
australia, canada, chile denmark, france,
germany, ghana, hong kong, india, ireland,
italy, japan, malta, new zealand, the
netherlands, norway, singapore, switzerland,
the united kingdom, the united states,
vietnam, zaire
Register now
On the 7th May Honolulu will provide the
backdrop of the eleventh international world
wide web conference This prestigious event 
Speakers confirmed
Tim berners-lee
Tim is the well known inventor of the Web, 
Ian Foster
Ian is the pioneer of the Grid, the next
generation internet 
11
Copyright © 2005 Univ. of Manchester
Solution: XML markup with
“meaningful” tags?
name>WWW2002The eleventh international world wide
webcon</name>
<location>Sheraton waikiki hotel Honolulu, hawaii,
USA</location>
<date>7-11 may 2002</date>
<slogan>1 location 5 days learn interact</slogan>
<participants>Registered participants coming
<
fromaustralia, canada, chile denmark, france,
germany, ghana, hong kong, india, ireland,
italy, japan, malta, new zealand, the
netherlands, norway, singapore, switzerland, the
united kingdom, the united states, vietnam,
zaire
>
</participants
<introduction>Register
nowOn the 7th May Honolulu will
provide the backdrop of the eleventh
international world wide web conference This
prestigious event Speakers confirmed
>
</introduction
speaker>Tim berners-lee</speaker>
<bio>Tim is the well known inventor
<
12
Copyright © 2005 Univ. of Manchester
bio>…
of theWeb,</
But What About…
<conf>WWW2002The eleventh international world wide
webcon</conf>
<place>Sheraton waikiki hotelHonolulu, hawaii,
USA</place>
<date>7-11 may 2002</date>
<slogan>1 location 5 days learn interact</slogan>
<participants>Registered participants coming
fromaustralia, canada, chile denmark, france,
germany, ghana, hong kong, india, ireland, italy,
japan, malta, new zealand, the netherlands, norway,
singapore, switzerland, the united kingdom, the united
states, vietnam, zaire
</participants>
<introduction>Register
nowOn the 7th May Honolulu will
provide the backdrop of the eleventh international world
wide web conference This prestigious event 
</introduction>
berners-lee</speaker>
Speakers confirmed
<speaker>Tim
<bio>Tim is the
13
well known inventor of the Web,…
Copyright © 2005 Univ. of Manchester
Need to Add “Semantics”
► External agreement on meaning of annotations
► E.g., Dublin Core
►Agree on the meaning of a set of annotation tags
► Problems with this approach
►Inflexible
►Limited number of things can be expressed
► Use Ontologies to specify meaning of annotations
► Ontologies provide a vocabulary of terms
► New terms can be formed by combining existing ones
► Meaning (semantics) of such terms is formally specified
► Can also specify relationships between terms in multiple
ontologies
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Copyright © 2005 Univ. of Manchester
Ontology: Origins and
History
Ontology in Philosophy
a philosophical discipline—a branch of philosophy that
deals with the nature and the organisation of reality
► Science of Being (Aristotle, Metaphysics, IV, 1)
► Tries to answer the questions:
What characterizes being?
Eventually, what is being?
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Ontology in Linguistics
Concept
Relates to
activates
Form
Stands for
“Tank“
[Ogden, Richards, 1923]
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Referent
?
Ontology in Computer
Science
► An ontology is an engineering artifact:
► It is constituted by a specific vocabulary used to describe a certain
reality, plus
► a set of explicit assumptions regarding the intended meaning of the
vocabulary.
► Thus, an ontology describes a formal specification of a certain
domain:
► Shared understanding of a domain of interest
► Frmal and machine manipulable model of a domain of interest
“An explicit specification of a conceptualisation” [Gruber93]
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Structure of an Ontology
Ontologies typically have two distinct components:
► Names for important concepts in the domain
► Elephant is a concept whose members are a kind of animal
► Herbivore is a concept whose members are exactly those animals
who eat only plants or parts of plants
► Adult_Elephant is a concept whose members are exactly those
elephants whose age is greater than 20 years
► Background knowledge/constraints on the domain
► Adult_Elephants weigh at least 2,000 kg
► All Elephants are either African_Elephants or Indian_Elephants
► No individual can be both a Herbivore and a Carnivore
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Copyright © 2005 Univ. of Manchester
[Mike Uschold, Boeing Corp]
A semantic continuum
Pump: “a device for
moving a gas or liquid
from one place or
container to another”
(pump has
(superclasses (…))
Shared
human
consensus
Semantics
Text descriptions hardwired;
used at runtime
Semantics
processed and
used at runtime
Implicit
Informal
Formal
(explicit)
Formal
(for humans)
(for machines)
 Further to the right 
• Less ambiguity
• Better inter-operation
• More robust – less hardwiring
• More difficult
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A simple ontology: Pizzas
Pizza
Vegetarian
Pizza
Margherita
Pizza
Spicy Beef
Pizza
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Pizza
Topping
Pizza_base
Vegetable
topping
Tomato
topping
Deep
dish base
Cheese
topping
Mozzarella
topping
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Regular
base
Ontology Design and
Deployment
► Given key role of ontologies in the Semantic Web,
it will be essential to provide tools and services to
help users:
► Design and maintain high quality ontologies, e.g.:
►Meaningful — all named classes can have instances
►Correct — captured intuitions of domain experts
►Minimally redundant — no unintended synonyms
►Richly axiomatised — (sufficiently) detailed descriptions
► Store (large numbers) of instances of ontology classes, e.g.:
Annotations from web pages
► Answer queries over ontology classes and instances, e.g.:
►Find more general/specific classes
►Retrieve annotations/pages matching a given description
► Integrate and align multiple ontologies
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Example Ontology
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Many languages use “object
oriented” model based on:
► Objects/Instances/Individuals
► Elements of the domain of discourse
► Equivalent to constants in FOL
► Types/Classes/Concepts
► Sets of objects sharing certain characteristics
► Equivalent to unary predicates in FOL
► Relations/Properties/Roles
► Sets of pairs (tuples) of objects
► Equivalent to binary predicates in FOL
► Such languages are/can be:
► Well understood
► Formally specified
► (Relatively) easy to use
► Amenable to machine processing
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Aside: Set Based Model Theory
Many logics (including standard First Order Logic) use a model theory based on
Zermelo-Frankel set theory
The domain of discourse (i.e., the part of the world being modelled) is
represented as a set (often refered as )
Objects in the world are interpreted as elements of 
Classes/concepts (unary predicates) are subsets of 
Properties/roles (binary predicates) are subsets of  £  (i.e., 2)
Ternary predicates are subsets of 2 etc.
The sub-class relationship between classes can be interpreted as set inclusion
Doesn’t work for RDF, because in RDF a class (set) can be a member (element)
of another class (set)
In Z-F set theory, elements of classes are atomic (no structure)
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Why it’s hard (1)
► Clash of intuitions
► Subject Matter Experts motivated by custom & practice
►Prototypes & Generalities
► Logicians motivated by logic & computational tractability
►Definitions and Universals
► Transparency & predictability vs
Rigour & Completeness
► Neophytes (you?) caught in the muddled middle
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Why it’s hard (2)
► Conflation of Models
► Meaning:
Correctness of Classification & retrieval
► Indexing:
Task of discovery, search, or finding
► Use:
Task of data entry, decision support, …
► Acquisition:
Task of capturing knowledge
► Assuring quality & managing change
► Quality assurance:
Criteria for whether it is ‘correct’
► Evolution
Coping with change
► Regression testing
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Controlling changes & maintaining
Quality
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Why its hard (3)
► Confusion of terminology and usage
► Religious wars over words and assumptions
► The intersection of
► Linguistics
► Cognitive science
► Software engineering
► Philosophy
► Human Factors
► A jumble of syntaxes
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Vocabulary
► “Class”  “Concept”  “Category”  “Type”
► “Instance”  “Individual”
► “Entity”  “object”, Class or individual
► “Property”  “Slot”  “Relation”  “Relationtype” 
“Attribute”  Semantic link type”  “Role”
► but be careful about “role”
►Means “property” in DL-speak
►Means “role played” in most ontologies
►E.g. “doctor_role”, “student role” …
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An Ontology should be just
the Beginning
Ontologies
Provide
domain
description
Software
agents
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Problemsolving
methods
Declare
structure
The
“Semantic
Web”
Domainindependent
applications
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Databases
Knowledge
bases