Linked data basic notions!

Transcription

1 Linked data basic notions

2 see

3 RDF RDF stands for Resource Description Framework It is a W3C Recommendation ü RDF is a graphical formalism ( + XML syntax + semantics) ü for representing metadata ü for describing the semantics of information in a machine- accessible way Provides a simple data model based on triples.

4 The RDF Data Model Statements are <subject, predicate, object> triples: ü <Sean,hasColleague,Ian> Can be represented as a graph: Sea n hascolleague Statements describe properties of resources A resource is any object that can be pointed to by a URI: ü The generic set of all names/addresses that are short strings that refer to resources ü a document, a picture, a paragraph on the Web, a book in the library, a real person (?), isbn:// Properties themselves are also resources (URIs) Ia n

5 Linking Statements The subject of one statement can be the object of another Such collections of statements form a directed, labeled graph Paol o hasname Paolo Bouquet hascolleague hascolleague Ilya Marco hashomepage

6 RDF Syntax RDF has an XML syntax that has a specific meaning: Every Description element describes a resource Every attribute or nested element inside a Description is a property of that Resource We can refer to resources by URIs <Description about="some.uri/person/paolo_bouquet"> <hascolleague resource="some.uri/person/marco_ronchetti"/> <hasname rdf:datatype="&xsd;string">paolo Bouquet</hasName> </Description> <Description about="some.uri/person/marco_ronchetti"> <o:hashomepage> </Description> <Description about="some.uri/person/fausto_giunchiglia"> <o:hascolleague resource="some.uri/person/fausto_giunchiglia"/> </Description>

7 What does RDF give us? A mechanism for annotating data and resources. Single (simple) data model. Syntactic consistency between names (URIs). Low level integration of data.

8 RDF(S): RDF Schema RDF gives a formalism for meta data annotation, and a way to write it down in XML, but it does not give any special meaning to vocabulary such as subclassof or type ü Interpretation is an arbitrary binary relation RDF Schema extends RDF with a schema vocabulary that allows you to define basic vocabulary terms and the relations between those terms ü Class, type, subclassof, ü Property, subpropertyof, range, domain ü it gives extra meaning to particular RDF predicates and resources ü this extra meaning, or semantics, specifies how a term should be interpreted

9 RDF(S) Examples RDF Schema terms (just a few examples): ü Class; Property ü type; subclassof ü range; domain These terms are the RDF Schema building blocks (constructors) used to create vocabularies: ü <Person,type,Class> ü <hascolleague,type,property> ü <Professor,subClassOf,Person> ü <Carole,type,Professor> ü <hascolleague,range,person> ü <hascolleague,domain,person>

10 RDF/RDF(S) Liberality No distinction between classes and instances (individuals) <Species,type,Class> <Lion,type,Species> <Leo,type,Lion> Properties can themselves have properties <hasdaughter,subpropertyof,haschild> <hasdaughter,type,familyproperty> No distinction between language constructors and ontology vocabulary, so constructors can be applied to themselves/each other <type,range,class> <Property,type,Class> <type,subpropertyof,subclassof>

11 RDF(S) Inference rdf:type rdfs:class Person rdfs:subclassof rdfs:subclassof Academi c rdf:type rdf:type rdf:subclassof Lecturer

12 RDF(S) Inference rdf:type rdfs:class Academic rdfs:subclassof rdf:type rdfs:type Lecturer rdf:type Sean

13 What does RDF(S) give us? Ability to use simple schema/vocabularies when describing our resources. Consistent vocabulary use and sharing. Simple inference

14 Problems with RDF(S) RDF(S) is too weak to describe resources in sufficient detail ü No localised range and domain constraints ü Can t say that the range of haschild is Person when applied to Persons and Elephant when applied to Elephants ü No existence/cardinality constraints ü Can t say that all instances of Person have a mother that is also a Person, or that Persons have exactly 2 parents ü No transitive, inverse or symmetrical properties ü Can t say that ispartof is a transitive property, that haspart is the inverse of ispartof or that touches is symmetrical Difficult to provide reasoning support ü No native reasoners for non-standard semantics ü May be possible to reason via FO axiomatisation

15 Solution Extend RDF(S) with a language that has the following desirable features identified for Web Ontology Language ü Extends existing Web standards ü Such as XML, RDF, RDFS ü Easy to understand and use ü Should be based on familiar KR idioms ü Of adequate expressive power ü Formally specified ü Possible to provide automated reasoning support That language is OWL.

16 Introduction to OWL Marco Ronchetti Università di Trento Italy

17 Languages Work on Semantic Web has concentrated on the definition of a collection or stack of languages. ü These languages are then used to support the representation and use of metadata. Basic machinery to represent the extra semantic information needed for the Semantic Web ü XML ü RDF ü RDF(S) ü OWL ü OWL RDF(S) RDF XML Annotation Integration Inference

18 OWL: Web Ontology Language RDF/RDF(S) DAML DAML-ONT Joint EU/US Committee Frames OIL DAML+OIL W3C OWL Description Logics OntoKnowledge+Others

19 Ontology A heavily overloaded term with several different meanings in different disciplines: ü Philosophy ü Linguistics ü Computer Science)

20 Ontology - Philosophy Ontology deals with the nature and organisation of reality (Aristotele) Tries to answer the questions: What characterizes being? What is being?

21 Ontology - Linguistics a concept, is the mediator that relates the symbol to its object Concept of TANK activates Relates to Symbol "Tank" Stands for Referent "Semiotic triangle"

22 Ontology - Computer Science Rudi Studer(98)

23 A Semantic continuum Further to the right: Less ambiguity Better inter-operation More robust More difficult

24 Basic terms Individuals - objects in the domain of interest Properties - binary relations on individuals Classes - (concepts) sets that contain individuals

25 Structure of an Ontology Ontologies typically have two distinct components: Names for important concepts in the domain ü Elephant is a concept whose members are a kind of animal ü Herbivore is a concept whose members are exactly those animals who eat only plants or parts of plants ü Adult_Elephant is a concept whose members are exactly those elephants whose age is greater than 20 years Background knowledge/constraints on the domain ü Adult_Elephants weigh at least 2,000 kg ü All Elephants are either African_Elephants or Indian_Elephants ü No individual can be both a Herbivore and a Carnivore

26 Ontology Languages There are a wide variety of languages for Explicit Specification ü Graphical Notations ü Semantic Networks ü Topic Maps ü UML ü RDF

27 Ontology Languages There are a wide variety of languages for Explicit Specification ü Graphical Notations ü Semantic Networks ü Topic Maps ü UML ü RDF ü Logic Based ü Description Logics ü Rules ü First Order Logic ü Conceptual Graphs

28 Requirements for Ontology Languages Ontology languages allow users to write explicit, formal conceptualizations of domain models The main requirements are: ü a well-defined syntax ü efficient reasoning support ü a formal semantics ü sufficient expressive power ü convenience of expression

29 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: ü A language supported by reasonably efficient reasoners ü A language that can express large classes of ontologies and knowledge.

30 Was nt RDF(S) enough? OWL RDF(S) RDF XML Annotation Integration Inference

31 Reasoning About Knowledge in Ontology Languages Class membership ü 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 ü If class A is equivalent to class B, and class B is equivalent to class C, then A is equivalent to C, too

32 Reasoning About Knowledge in Ontology Languages (2) Consistency ü X instance of classes A and B, but A and B are disjoint ü This is an indication of an error in the ontology Classification ü 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

33 Uses for Reasoning Reasoning support is important for ü checking the consistency of the ontology and the knowledge ü checking for unintended relationships between classes ü automatically classifying instances in classes Checks like the preceding ones are valuable for ü designing large ontologies, where multiple authors are involved ü integrating and sharing ontologies from various sources

34 Reasoning Support for OWL Semantics is a prerequisite for reasoning support Formal semantics and reasoning support are usually provided by ü mapping an ontology language to a known logical formalism ü using automated reasoners that already exist for those formalisms OWL is (partially) mapped on a description logic, and makes use of reasoners such as Pellet and RACER Description logics are a subset of predicate logic for which efficient reasoning support is possible

35 Limitations of the Expressive Power of RDF Schema Local scope of properties ü rdfs:range defines the range of a property (e.g. eats) for all classes ü In RDF Schema we cannot declare range restrictions that apply to some classes only ü E.g. we cannot say that cows eat only plants, while other animals may eat meat, too

36 Limitations of the Expressive Power of RDF Schema (2) Disjointness of classes ü Sometimes we wish to say that classes are disjoint (e.g. male and female) Boolean combinations of classes ü Sometimes we wish to build new classes by combining other classes using union, intersection, and complement ü E.g. person is the disjoint union of the classes male and female

37 Limitations of the Expressive Power of RDF Schema (3) Cardinality restrictions ü E.g. a person has exactly two parents, a course is taught by at least one lecturer Special characteristics of properties ü Transitive property (like greater than ) ü Unique property (like is mother of ) ü A property is the inverse of another property (like eats and is eaten by )

38 Three Species of OWL W3C sweb Ontology Working Group defined OWL as three different sublanguages: ü OWL Full ü OWL DL ü OWL Lite Each sublanguage geared toward fulfilling different aspects of requirements

39 OWL Full (FOP) It uses all the OWL languages primitives It allows the combination of these primitives in arbitrary ways with RDF and RDF Schema OWL Full is fully upward-compatible with RDF, both syntactically and semantically OWL Full is so powerful that it is undecidable ü No complete (or efficient) reasoning support

40 OWL DL OWL DL (Description Logic) is a sublanguage of OWL Full that restricts application of the constructors from OWL and RDF ü Application of OWL s constructors to each other is disallowed ü Therefore it corresponds to a well studied description logic OWL DL permits efficient reasoning support But we lose full compatibility with RDF: ü Not every RDF document is a legal OWL DL document. ü Every legal OWL DL document is a legal RDF document.

41 Aside: Description Logics A family of logic based Knowledge Representation formalisms ü Descendants of semantic networks and KL-ONE ü Describe domain in terms of concepts (classes), roles (relationships) and individuals Distinguished by: ü Formal semantics (typically model theoretic) ü Decidable fragments of FOL ü Closely related to Propositional Modal & Dynamic Logics ü Provision of inference services ü Sound and complete decision procedures for key problems ü Implemented systems (highly optimised)

42 DL Semantics Model theoretic semantics. An interpretation consists of ü A domain of discourse (a collection of objects) ü Functions mapping ü classes to sets of objects ü properties to sets of pairs of objects ü Rules describe how to interpret the constructors and tell us when an interpretation is a model. In a DL, a class description is thus a characterisation of the individuals that are members of that class.

43 OWL Lite An even further restriction limits OWL DL to a subset of the language constructors ü E.g., OWL Lite excludes enumerated classes, disjointness statements, and arbitrary cardinality. The advantage of this is a language that is easier to ü grasp, for users ü implement, for tool builders The disadvantage is restricted expressivity

44 Closed World Assumption OWL currently adopts the open-world assumption: ü A statement cannot be assumed true on the basis of a failure to prove it ü On the huge and only partially knowable WWW, this is a correct assumption Closed-world assumption: a statement is true when its negation cannot be proved ü tied to the notion of defaults, leads to nonmonotonic behaviour

45 Unique Names Assumption Typical database applications assume that individuals with different names are indeed different individuals OWL follows the usual logical paradigm where this is not the case ü Plausible on the WWW One may want to indicate portions of the ontology for which the assumption does or does not hold

46 Properties Symmetric (A p B) (B p A) Transitive (A p B), (B p C) (A p C)

47 Properties Functional (A p B), (A p C) B=C Inverse Functional

48 Existential Restriction Prop ClassA (someveluefrom) Every individual must have at least one prop releshionship with a member of class A (Necessary condition) (Open World Assumption)

49 Universal Restriction Prop ClassA (allveluesfrom) If relation for prop exists, it must be with an element of ClassA

50 Combining Universal & Existential Prop ClassA Prop ClassA Every individual has prop with at least one element in class A, and no individual has prop with elements not belonging to class A Necessary and sufficient condition Definition

51 Closure Axiom Prop (ClassA ClassB) Prop ClassA Prop ClassB Every individual has prop with at least one element in either class A or Class B, and with no other classes.

52 Tools Editors ü Protégé OWL, SWOOP, ICOM, TopQuadrant Composer, OntoTrack, NeOn ü Tend to present the user with frame-like interfaces, but allow richer expressions ü Offer the possibility of using reasoners. Reasoners ü DL style reasoners based on tableaux algorithms ü Racer, FaCT++, Pellet ü Based on rules or F-logic ü F-OWL, E-Wallet.. APIs and Frameworks ü Jena, WonderWeb OWL-API, Protégé OWL API, OWLIM

53 Protégé ü Is a knowledge modelling environment ü Is free, open source software ü Is developed by Stanford Medical Informatics ü Has a large user community ü Supports development of plugins to allow backend / interface extensions (e.g. reasoners) ü supports OWL

54 Credits A Practical Introduction to Ontologies & OWL Duncan Hall & Nick Drummonds A Semantic Web Primer Grigoris Antoniou & Frank van Harmelen Ontology Languages for the Semantic Web Sean Bechhofer A Practical Guide To Building OWL Ontologies Using The Protege-OWL Plugin and CO-ODE Tools Matthew Horridge et al.

55 An African Wildlife Ontology Class Hierarchy

56 An African Wildlife Ontology Schematic Representation Βranches are parts of trees

57 An African Wildlife Ontology Properties <owl:transitiveproperty rdf:id="is-part-of"/> <owl:objectproperty rdf:id="eats"> <rdfs:domain rdf:resource="#animal"/> </owl:objectproperty> <owl:objectproperty rdf:id="eaten-by"> <owl:inverseof rdf:resource="#eats"/> </owl:objectproperty>

58 An African Wildlife Ontology Plants and Trees <owl:class rdf:id="plant"> <rdfs:comment>plants are disjoint from animals. </rdfs:comment> <owl:disjointwith="#animal"/> </owl:class> <owl:class rdf:id="tree"> <rdfs:comment>trees are a type of plant. </ rdfs:comment> <rdfs:subclassof rdf:resource="#plant"/> </owl:class>

59 An African Wildlife Ontology Branches <owl:class rdf:id="branch"> <rdfs:comment>branches are parts of trees. </rdfs:comment> <rdfs:subclassof> <owl:restriction> <owl:onproperty rdf:resource="#is-part-of"/> <owl:allvaluesfrom rdf:resource="#tree"/> </owl:restriction> </rdfs:subclassof> </owl:class>

60 An African Wildlife Ontology Leaves <owl:class rdf:id="leaf"> <rdfs:comment>leaves are parts of branches. </ rdfs:comment> <rdfs:subclassof> <owl:restriction> <owl:onproperty rdf:resource="#is-part-of"/> <owl:allvaluesfrom rdf:resource="#branch"/> </owl:restriction> </rdfs:subclassof> </owl:class>

61 An African Wildlife Ontology Carnivores <owl:class rdf:id="carnivore"> <rdfs:comment>carnivores are exactly those animals that eat also animals.</rdfs:comment> <owl:intersectionof rdf:parsetype="collection"> <owl:class rdf:about="#animal"/> <owl:restriction> <owl:onproperty rdf:resource="#eats"/> <owl:somevaluesfrom rdf:resource="#animal"/> </owl:restriction> </owl:intersectionof> </owl:class>

62 An African Wildlife Ontology Herbivores <owl:class rdf:id="herbivore"> <rdfs:comment> Herbivores are exactly those animals that eat only plants or parts of plants. </rdfs:comment> <rdfs:comment> Try it out See book for code. <rdfs:comment> </owl:class>

63 An African Wildlife Ontology Giraffes <owl:class rdf:id="giraffe"> <rdfs:comment>giraffes are herbivores, and they eat only leaves.</rdfs:comment> <rdfs:subclassof rdf:type="#herbivore"/> <rdfs:subclassof> <owl:restriction> <owl:onproperty rdf:resource="#eats"/> <owl:allvaluesfrom rdf:resource="#leaf"/> </owl:restriction> </rdfs:subclassof> </owl:class>

64 An African Wildlife Ontology Lions <owl:class rdf:id="lion"> <rdfs:comment>lions are animals that eat only herbivores.</rdfs:comment> <rdfs:subclassof rdf:type="#carnivore"/> <rdfs:subclassof> <owl:restriction> <owl:onproperty rdf:resource="#eats"/> <owl:allvaluesfrom rdf:resource="#herbivore"/> </owl:restriction> </rdfs:subclassof> </owl:class>

65 An African Wildlife Ontology Tasty Plants owl:class rdf:id="tasty-plant"> <rdfs:comment>plants eaten both by herbivores and carnivores </rdfs:comment> <rdfs:comment> Try it out See book for code. <rdfs:comment> </owl:class>

66 A Printer Ontology Class Hierarchy

67 A Printer Ontology Products and Devices <owl:class rdf:id="product"> <rdfs:comment>products form a class. </rdfs:comment> </owl:class> <owl:class rdf:id="padid"> <rdfs:comment>printing and digital imaging devices form a subclass of products.</rdfs:comment> <rdfs:label>device</rdfs:label> <rdfs:subclassof rdf:resource="#product"/> </owl:class>

68 A Printer Ontology HP Products <owl:class rdf:id="hpproduct"> <owl:intersectionof> <owl:class rdf:about="#product"/> <owl:restriction> <owl:onproperty rdf:resource="#manufactured-by"/> <owl:hasvalue> <xsd:string rdf:value="hewlett Packard"/> </owl:hasvalue> </owl:restriction> </owl:intersectionof> </owl:class>

69 A Printer Ontology Printers and Personal Printers <owl:class rdf:id="printer"> <rdfs:comment>printers are printing and digital imaging devices.</rdfs:comment> <rdfs:subclassof rdf:resource="#padid"/> </owl:class> <owl:class rdf:id="personalprinter"> <rdfs:comment>printers for personal use form a subclass of printers.</rdfs:comment> <rdfs:subclassof rdf:resource="#printer"/> </owl:class>

70 A Printer Ontology HP LaserJet 1100se Printers <owl:class rdf:id="1100se"> <rdfs:comment>1100se printers belong to the 1100 series and cost $450.</rdfs:comment> <rdfs:subclassof rdf:resource="#1100series"/> <rdfs:subclassof> <owl:restriction> <owl:onproperty rdf:resource="#price"/> <owl:hasvalue><xsd:integer rdf:value="450"/> </owl:hasvalue> </owl:restriction> </rdfs:subclassof> </owl:class>

71 A Printer Ontology Properties <owl:datatypeproperty rdf:id="manufactured-by"> <rdfs:domain rdf:resource="#product"/> <rdfs:range rdf:resource="&xsd;string"/> </owl:datatypeproperty> <owl:datatypeproperty rdf:id="printingtechnology"> <rdfs:domain rdf:resource="#printer"/> <rdfs:range rdf:resource="&xsd;string"/> </owl:datatypeproperty>

72 Summary OWL is the proposed standard for Web ontologies OWL builds upon RDF and RDF Schema: ü (XML-based) RDF syntax is used ü Instances are defined using RDF descriptions ü Most RDFS modeling primitives are used

73 Summary (2) Formal semantics and reasoning support is provided through the mapping of OWL on logics ü Predicate logic and description logics have been used for this purpose While OWL is sufficiently rich to be used in practice, extensions are in the making ü They will provide further logical features, including rules