Ontology construction II

Course “Ontology Engineering”

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Overview

• Part-whole relations

• Vocabulary representation with SKOS

• Examples of commonly-used ontologies

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PART-WHOLE RELATIONS

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Part-whole relations

• “Mereology” = theory of part-whole– “meros” is Greek for part

• Common in many domains– Human body, cars, installations, documents

• Different from the subclass/generalization relation

• No built-in modeling constructs in OWL• Different types of part-whole relations exist

– With important semantic differences

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UML Aggregation• Aggregation denotes a binary association

in which one side is an "assembly" and the other side a "part".

• "Assembly" and "part" act as predefined roles involved in the aggregation association.

• Cardinality of a part can be defined – precisely one; optional (0-1); many, ...

• No semantics in UML!

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Aggregation example in UML

audiosystem

tape deck

CD player

tuner

amplifier

speakerheadphones

recordplayer

0-1

0-1

0-1

0-1 0-1 2,4

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UML Composition• Sub-type of aggregation

• Existence of part depends on aggregate

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Aggregation vs. generalization

• Similarities:– Tree-like structure– Transitive properties

• Differences:– AND-tree (aggregation) vs. OR-tree

(generalization)– instance tree (aggregation) vs. class tree

(generalization)

Examples: partOf or subClassOf?

• House – Building

• Brick – House

• Antique book – Antique book collection

• Silvio – Married Couple

• Veronica – Married Couple

• Hand – Body part

• Finger ‐ Hand

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Confusion with non-compositional relations• Temporal topological inclusion

– The customer is in the store, but not part of it

• Classification inclusion– A Bond movie is an instance of “film” but part of my

film collection

• Attribution– The height and width of a ship are not part of the ship

• Attachment– A wrist watch is not part of the wrist

• Ownership– I own a bicycle but it is not part of me

Representing part-whole relations

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Representing part-whole relations• Part-whole relation is transitive

– If A is part of B and B is part of C then A is part of C

– But see the caveats later on

• Usually there is a a need to distinguish:– Part in a transitive sense– Direct part

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Basic scheme

• Define a property e.g. partOf and (usually needed) the inverse hasPart

• Define a subproperty of partOf to represent direct parts, e.g. partOfDirect

• Choose the primary property for expressing part-whole: part of or hasPart?– partOf is generally more intuitive. Why?

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Transitivity

• A subproperty of a transitive property is not by definition transitive– Make sure you understand why

• Example: direct-part properties are not transitive

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Part-whole specification with individuals

:Amsterdam a :InhabitatedPlace ; :partOf :North-Holland .

:North-Holland a :Province ; :partOf :Netherlands .

:Place a owl:Class ; rdfs:subClassOf [ a owl:Restriction ; owl:onProperty :partOf ; owl:allValuesFrom :Place ] .

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Part-whole specification with classesAudioSystem hasPart someValuesFrom Amplifier someValuesFrom Loudspeaker someValuesFrom InputSystem

[assume CD, tuner and cassette player defined as subclasses of input system]

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Characteristics of part-whole relations• Vertical relationships

– Existence dependency between whole and part

– Feature dependencies:• Inheritance from part to whole: “defective”• Inheritance from whole to part: “owner”• Systematic relation: weight whole = sum weight

parts

• Horizontal relationships– Constraints between parts

Types of part‐whole relations

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Types of part-whole relations

Based on three distinctions1. Configurability

Functional/structural relation with the other parts or the whole yes/no

2. Homeomerous Parts are same kind as the whole yes/no

3. Invariance Parts can be separated from the whole

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Component-integral

• Functional/structural relation to the whole

• Parts can be removed and are different from whole

• Organization of the parts

• Examples: car wheels, film scenes

• N.B. difference between “wheel” and “car wheel”

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Material-object

• Invariant configuration

• Examples: – A bicycle is partly iron– Wine is partly alcohol– Human body is partly water

• The “made-off” relation

• Relation between part and whole is not known

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Portion-object

• Homeomeric configuration of parts• Examples:

– A lice of bread is part of a loaf of bread– A sip of coffee is part of a cup o coffee

• Portions can be quantified with standard measures (liter, gram, ..)

• Homeomeric: a sip of coffee is coffee (but a bicycle wheel is not a bicycle)– Ingredients of portion and object are the same

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Place-area

• Homeomeric invariant configuration

• Examples:– North-Holland is part of The Netherlands– The Mont Blanc peak is part of the Mont Blanc

mountain– The head is part of the human body (?!)

• Typically between places and locations

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Member-bunch

• No configuration, no invariance, not homeomeric

• Members of a collection• Examples:

– A tree is part of a wood– The hockey player is part of a club

• Differentiate from classification-based collections– A tree is a member of the class of trees

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Member-partnership

• Same as member-bunch, but invariant

• If a part is removed, the whole ceases to exist

• Examples:– Bonny and Clyde– Laurel and Hardy– A married couple

Example: types of part of relations

• Vitamin – Orange

• Branch – Tree

• Student – the class of ’02

• Book – library

• Chair – Faculty Board

• Engine – Car

• Artuicle - newspaper26

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Transitivity of part-whole types

• Transitivity does not (necessarily) hold when traversing different types of part-whole relation– I am a member of a club (member-bunch)– My head is part of me (place-area)– But: my head is not a part of the club

Practical example of ontology modelling

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Use case

:SelectionCommittee a owl:Class ; rdfs:subClassOf [ a owl:Restriction ; owl:onProperty :committeeMember

; owl:allValuesFrom :Person ] . • How can we define that a selection committee

must have two female members?

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Qualified cardinality restrictions (QCRs)• Restriction on the number of values of a

certain type (hence “qualified”)• owl:someValuesFrom is an example of

such a constraint – cardinality of 1 or more of a certain type of

value

• Typically used to specify the component types in some part-of structure

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Workaround for QCRs

1. Define a subproperty of the property on which you want to define a QCR

2. Define a value constraint (using either owl:allValuesFrom or rdfs:range) and a cardinality constraint on the subproperty

• Cumbersome for complex part-whole relations

• QCR constructs in OWL2

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Example workaround

:SelectionCommittee a owl:Class rdfs:subClassOf [ a owl:Restriction ;

owl:onProperty :committeeMemberFemale ; owl:allValuesFrom :FemalePerson ] ; rdfs:subClassOf [ a owl:Restriction ;

owl:onProperty :committeeMemberFemale ; owl:minCardinality "2"^^xsd:int] .

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Literature

• Simple part-whole relations in OWL Ontologies

• Six Different Kinds of Composition

• (A foundation for composition)

Classroom exercise "Bitterness"

• In certain combinations and minimum concentrations one or more amino acids can cause bitterness. Amino acids are divided into three groups: Group I, II and III. Every amino acid has a unique chemical formula.

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SKOS & VOCABULARIES

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Overview

• Commonly used schemas about:– Thesauri (SKOS)– People and what they do and like (FOAF)– Finding documents (Dublin Core)– Time– Provenance

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Thesauri (and vocabularies)

• “Standard” terminology in a particular domain

• Developed by a community over years

• ISO standard for thesauri

• Starting point for ontologies– enrichment

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Example thesauri

• WordNet: lexical resourcehttp://wordnet.princeton.edu/cgi-bin/webwn

• Getty thesauri– AAT: Art & Architecture Thesaurus – TGN: Thesaurus of Geographic Names– ULAN: Union List of Artist Names

• Iconclasshttp://www.iconclass.nl

• MeSH: Medical Subject Headings

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ISO standard for representing thesauri• Term

– Descriptor / Preferred term (USE)– Non-descriptor / Non-preferred term (UF)

• Hierarchical relation between terms– Broader/narrower term (BT/NT)

• Association between terms (RT)

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SKOS: pattern for thesaurus modeling• Based on ISO standard

• RDF representation

• Documentation:http://www.w3.org/TR/swbp-skos-core-guide/

• Base class: SKOS Concept

Classes versus Concepts

• skos:Concepts are “subjects” used to index things, while rdfs:Classes are sets of things themselves– Apart from the meaning of a subject, the ordering of

skos:Concepts can also have to do with how documents are grouped.

• A skos:Concept can correspond to both instance and class

• The narrower skos:Concept can be of a different type than its broader skos:Concept

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Multi-lingual labels for concepts

Difference between WordNet and SKOS

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Documenting concepts

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Semantic relation:broader and narrower• No subclass semantics assumed!

broader vs subClassOf

• Broader is more generic than subClassOf

• Broader can be– Generic (subclass or type)– Partitive (structural, location, membership,

etc.)– Topic implication (e.g. cow milk under cows)

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Semantic relations:related• Symmetric relation

Facets

• Thesauri are often structured into facets, high-level groups of similar concepts– Objects, People, Places, Events, etc.

• Facets typically correspond to fields that are useful in a fielded search engine– Subject, Author, Publisher, etc.

• In SKOS a facet can be modeled with skos:ConceptScheme

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Defining the top level of the hierarchy

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Collections:role-type trees

COMMON ONTOLOGIES

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Friend of a Friend (FOAF)

• Describing people: – names– depictions– friends, acquaintances, relations– organizations– e-mail addresses– webpages– ...

• see http://xmlns.com/foaf/spec/

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Agents: People and Groups

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FOAF Basics

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Agent identity

• When are two Agents the same?– definitely when they have the same URI or openID– probably when they have the same e-mail address...

owl:InverseFunctionalProperty?– maybe when they have the same name...

William of Orange (I the Silent? III of England? the Bishop? of Beax? the pigeon in WWII?)

• AAA, so you have to do disambiguation, also called “smushing”

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FOAF Personal Info

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FOAF Documents

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Dublin Core

• A basic schema to improve resource discovery on the web, i.e. finding stuff.

• Consists of 15 basic elements that are all optional, extensible, and repeatable.

• International and interdisciplinary.

• see http://purl.org/dc/

• Newest version: 1.1

http://dublincore.org/documents/dces/

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Dublin Core 1.0 Elements

– Title

– Creator

– Subject

– Description

– Publisher

– Contributor

– Date

– Type

– Format

– Identifier

– Source

– Language

– Relation

– Coverage

– Rights

think of possible links with: FOAF, SKOS, Creative Commons, MPEG-7, XML Schema, RSS, etc. Facets?

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Element RefinementElement Refinement

Provenance Definition

• Oxford English Dictionary: – the fact of coming from some particular source or

quarter; origin, derivation– the history or pedigree of a work of art, manuscript,

rare book, etc.; – concretely, a record of the passage

of an item through its various

owners.

• The provenance of a piece of data is the

process that led to that piece of data

Open Provenance Model

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Time ontology

• Time point versus time interval– View point as special case of an interval with

identical start and end

• Representation of time and duration concepts

• See

http://www.w3.org/TR/owl-time/

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Allen’s time relations

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