Ontology Engineering: ontology construction II
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Ontology Engineering: ontology construction II

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  • SHIT ik ben de nieuwe part-of lecture in pptx kwijt ….ik heb alleen de pdf nog. Agenda: 3 things -qcr -part-of -ass1
  • Comparison. Build in in uml, not in rdf/owl. Aggregatie no semantics in UML.
  • Instance tree in owl, but not in uml??
  • What are the parts of a car, what is a house made of?
  • Part of is a transitive property, is partOfDirectly also? What is an engine? It is part of a car? What is a car?
  • Remember transitivity of hasAncestor, but not hasParent.
  • Restriction: a place can only be part of a place. Provinces and InhabitedPlaces are Places. You could add some part of directly statements: e.g. Amsterdam part of directly North-Holland.
  • You could decompose these parts further into smaller parts: e.g
  • 1. Engine has clear function in a car. 2. water. 3. Can part be removed, and will the whole still exist?
  • What do you want to say with last line? Not all wheels are part of car?
  • Cannot take the iron out of a nail.
  • Silvio and Veronica
  • What does this say? We want to restrict the cardinality of a property, but only for a certain value. In owl options for cardinality contraints: minCardinality, maxCardinality, cardinality. Options for value contraints: allValuesFrom, someValuesFrom, hasValue. But not two combine the two. Do you see that it is not straightforward?
  • someValuesFrom: existential quantifier: E omgekeerd. Cardinality 1..* allValuesFrom: universal quantifier A omgekeerd. No cardinality. Bike: onproperty haspart somevaluesfrom wheel, somevaluesfrom pedal.
  • What if you want another cardinality than 1…*

Ontology Engineering: ontology construction II Ontology Engineering: ontology construction II Presentation Transcript

  • Ontology construction II Course “Ontology Engineering” 1
  • Overview• Part-whole relations• Vocabulary representation with SKOS• Examples of commonly-used ontologies 2
  • PART-WHOLE RELATIONS View slide
  • 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 4 View slide
  • 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! 5
  • Aggregation example in UML 0-1 audioCD player system record 0-1 player 0-1 tuner 0-1 0-1 2,4 amplifier tape deck head speaker phones 6
  • UML Composition• Sub-type of aggregation• Existence of part depends on aggregate 7
  • Aggregation vs. generalization• Similarities: – Tree-like structure – Transitive properties• Differences: – AND-tree (aggregation) vs. OR-tree (generalization) – instance tree (aggregation) vs. class tree (generalization) 8
  • Examples: partOf or subClassOf?• House – Building• Brick – House• Antique book – Antique book collection• Silvio – Married Couple• Veronica – Married Couple• Hand – Body part• Finger ‐ Hand 9
  • 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 10
  • Representing part-whole relations 11
  • Representing part-wholerelations• 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 12
  • 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? 13
  • Transitivity• A subproperty of a transitive property is not by definition transitive – Make sure you understand why• Example: direct-part properties are not transitive 14
  • Part-whole specification withindividuals: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 ] . 15
  • Part-whole specification withclassesAudioSystem hasPart someValuesFrom Amplifier someValuesFrom Loudspeaker someValuesFrom InputSystem[assume CD, tuner and cassette player defined as subclasses of input system] 16
  • Characteristics of part-wholerelations• 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 17
  • Types of part‐ whole relations 18
  • Types of part-whole relationsBased on three distinctions 1. 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 19
  • 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” 20
  • 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 21
  • 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 22
  • 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 23
  • 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 24
  • 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 25
  • Example: types of part of relations• Vitamin – Orange• Branch – Tree• Student – the class of ’02• Book – library• Chair – Faculty Board• Engine – Car• Artuicle - newspaper 26
  • 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 27
  • Practical example ofontology modelling 28
  • 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? 29
  • 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 30
  • 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 31
  • 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] . 32
  • Literature• Simple part-whole relations in OWL Ontologies• Six Different Kinds of Composition• (A foundation for composition) 33
  • 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. 34
  • SKOS &VOCABULARIES
  • Overview• Commonly used schemas about: – Thesauri (SKOS) – People and what they do and like (FOAF) – Finding documents (Dublin Core) – Time – Provenance 36
  • Thesauri (and vocabularies)• “Standard” terminology in a particular domain• Developed by a community over years• ISO standard for thesauri• Starting point for ontologies – enrichment 37
  • Example thesauri• WordNet: lexical resource http://wordnet.princeton.edu/cgi-bin/webwn• Getty thesauri – AAT: Art & Architecture Thesaurus – TGN: Thesaurus of Geographic Names – ULAN: Union List of Artist Names• Iconclass http://www.iconclass.nl• MeSH: Medical Subject Headings 38
  • ISO standard for representingthesauri• Term – Descriptor / Preferred term (USE) – Non-descriptor / Non-preferred term (UF)• Hierarchical relation between terms – Broader/narrower term (BT/NT)• Association between terms (RT) 39
  • 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 40
  • 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 41
  • Multi-lingual labels forconcepts 42
  • Difference between WordNetand SKOS 43
  • Documenting concepts 44
  • Semantic relation:broader and narrower• No subclass semantics assumed! 45
  • 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) 46
  • Semantic relations:related• Symmetric relation 47
  • 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 48
  • Defining the top level of thehierarchy 49
  • Collections:role-type trees 50
  • COMMON ONTOLOGIES
  • Friend of a Friend (FOAF)• Describing people: – names – depictions – friends, acquaintances, relations – organizations – e-mail addresses – webpages – ...• see http://xmlns.com/foaf/spec/ 52
  • Agents: People and Groups 53
  • FOAF Basics 54
  • 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” 55
  • FOAF Personal Info 56
  • FOAF Documents 57
  • 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/ 58
  • Dublin Core 1.0 Elements – Title – Format – Creator – Identifier – Subject – Source – Description – Language – Publisher – Relation – Contributor – Coverage – Date – Rights – Type think of possible links with: FOAF, SKOS, Creative Commons, MPEG-7, XML Schema, RSS, etc. Facets? 59
  • Element Refinement 60
  • 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 62
  • 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/ 63
  • Allen’s time relations 64