Goals. Introduction to Ontologybased. Service Semantics. Functional Semantics. Need more than XML Schema. Non-functional Semantics

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1 Goals Introduction to Ontologybased Semantics Semantic Web, ontologies, RDF, OWL, N3 With thanks to Declan O Sullivan To provide some insight into the usefulness of ontologies To provide an understanding of the features of RDFS and OWL and their use in automated reasoning To provide an outline of the N3 syntax Use N3 to express RDFS and OWL sufficient for later examples and exercises on service semantics Service Semantics WSDL provides the syntax we need for interoperating with a service, but little in the way of semantics Examining this example raises many questions about functional and non-functional semantics <message name= getcheapestflightrequest"> <part name= origin" type="xsd:string"/> <part name= destination" type="xsd:string"/> <part name= date" type="xsd:date"/> </message> <message name= getcheapestflightresponse"> <part name= flight" type="xsd:string"/> <part name= time" type="xsd:time"/> <part name= cost type= xsd:float /> </message> <porttype name= cheapestflight"> <operation name="getcheapestflight"> <input message= getcheapestflightrequest"/> <output message= getcheapestflightresponse"/> </operation> </porttype> Functional Semantics What do origin and destination strings represent? Country, city, airport, restrictions (airline, national, regional)? What does flight string represent? Airline, flight number, plane type? What does time string represent? Departure time? Note xsd:time probably is adequate - supports timezone information What does cost float represent? Currency, to how many decimal points? Non-functional Semantics Availability Can we assume 24x7x365 availability globally for web service unless otherwise stated Channels WSDL binding to SOAP supports this WSDL says nothing about: Charging Styles Settlement Service Quality Security and Trust Ownership and Rights Need more than XML Schema XML is Syntax DTDs talk about element nesting XML Schema schemas give you data types need anything else? => write comments! XML DTDs and XML Schemas are sufficient for exchanging data between parties who have agreed to meaning of terms beforehand Domain Semantics are complex: implicit assumptions, hidden semantics sources seem unrelated to the non-expert Need Structure and Semantics beyond XML trees! employ richer OO models make domain semantics and glue knowledge explicit use ontologies to fix terminology and conceptualization avoid ambiguities by using formal semantics (logics) 1

2 Informally: What is an Ontology? Defines the terms used to describe and represent an area of knowledge Used by people, databases, applications that need to share domain information Ontologies include computer-usable definitions of basic concepts in the domain and the relationships among them They encode knowledge in a domain and knowledge that spans domains Ontology: A definition An "ontology defines the common words and concepts (meaning) used to describe and represent an area of knowledge. An ontology can range from a Taxonomy (knowledge with minimal hierarchy or a parent/child structure) to a Thesaurus (words and synonyms) to a. Conceptual Model (with more complex knowledge) to a Logical Theory (with very rich, complex, consistent and meaningful knowledge). A well-formed ontology is one that is expressed in a well-defined syntax that has a well-defined machine interpretation consistent with the above ontology definition An explicit description of a domain Concepts (aka: class, set, type, predicate) event, gene, gammaburst, atrium, molecule, cat vermin Properties of concepts and relationships between them (aka: slot) rodent Taxonomy: generalisation ordering among concepts isa, mouse partof, subprocess Relationship, Role or Attribute: functionof, hasactivity location, eats, size animal domestic dog cat cow eats isa relationships An explicit description of a domain Constraints or axioms on properties and concepts: value: integer domain: cat cardinality: at most 1 animal range: 0 <= X <= 100 cows are larger than dogs cats cannot eat only vegetation vermin domestic cats and dogs are disjoint cat dog Values or concrete domains rodent cow eats integer, strings mouse An explicit description of a domain Nominals Similar to abstract classes/types Concepts that cannot have instances Instances that are used in conceptual definitions ItalianDog = Dog bornin Italy Individuals or Instances sulphur, trpa Gene, felix Ontology versus Knowledge Base An ontology = concepts+properties+axioms+values+ nominals A knowledge base = ontology+instances vermin animal dog cat cow rodent eats mouse mickey jerry domestic felix tom describe the vocabulary related to a generic domain by specializing the concepts introduced in the top-level ontology. Types of Ontologies describe very general concepts like space, time, event, which are independent of a particular problem or domain. It seems reasonable to have unified top-level ontologies for large communities of users. describe the vocabulary related to a generic task or activity by specializing the top-level ontologies. These are the most specific ontologies. Concepts in application ontologies often correspond to roles played by domain entities while performing a certain activity. 2

3 Ontologies - Some Examples General purpose ontologies: WordNet / EuroWordNet, The Upper Cyc Ontology, 2-1/index.html IEEE Standard Upper Ontology, Domain and application-specific ontologies: RDF Site Summary RSS, UMLS, KA2 / Science Ontology, RETSINA Calendering Agent, AIFB Web Page Ontology, Web-KB Ontology, 2.cs.cmu.edu/afs/cs.cmu.edu/project/theo- 11/www/wwkb/ Dublin Core, Meta-Ontologies Semantic Translation, nto/st/index.html RDFT, FT/0.27/RDFT.rdfs Evolution Ontology, xamples/evolution.rdfs Ontologies in a wider sense Agrovoc, Art and Architecture, tools/vocabulary/aat/ UNSPSC, DTD standardizations, e.g. HR-XML, Semantic Web Initiative of W3C, strongly driven by Sir Tim Berners Lee To date Web has been developed as a medium for document manipulation by people Aim to augment the web pages with data targeted at computers, and add documents targeted solely at computers, e.g. semantic web service descriptions Challenges Agreeing on standard Markup Language OWL standardisation progressing Generating sufficient common ontologies that can be referred to people in their own ontologies (e.g. definition of food, definition of person etc.) Availability of indexing crawlers or web service repositories to take advantage of new approach Tool support for people creating own ontologies Tool support for automatic markup of documents for end users, e.g. incorporation into Word or Frontpage etc. Tool support for automatic markup of web services for end users, e.g. incorporation into.net, J2EE etc. Subject Property Resource Description Framework (RDF) RDF is a W3C recommendation that enables encoding, exchange and reuse of structured metadata in XML Triples of assertions can be expressed using XML tags A bit like Subject, Property, Object of a sentence Concept RDF statement property E.g. Cabernet Sauvignon grape, is a type of, Wine grape <rdf:description rdf:about="cabernet Sauvignon grape > <rdf:type rdf:resource= #Wine grape" /> </rdf:description> Object Each resource can be assigned a different Universal Resource Identifier (URI) Thus different meanings for the same term can be assigned different URIs Reference: RDF Primer. W3C draft technical note, 2002 Value Concept Notational Verbosity Semantic Web relies on a stack of languages XML for document formatting and referencing elements of other document XML Schema for encoding data types RDF semantic description triple RDFS definition of classes, properties and subclasses in RDF OWL add assertions about relationships between classes/properties All aim to support machine processing and inference over the WWW BUT. Results in an incredibly verbose XML-based syntax! Fine for computers, bad for people Need less verbosity for sketching out ideas, presenting examples and teaching ontologies N3 Ontology Notation Compact, text based language for playing around with ontologies Python Platform CWM allows inference and exporting to correct XML formats, e.g. RDF Statements are all: Subject- Property- Object. Everything is a URI: <#pat> <#knows> <#jo>. We will use N3 for our examples and exercises Semantically equivalent to RDF, RDFS and OWL Same vocab, less clutter Syntactic shortcuts Several objects with same subject and predicate separated by, Several statements about same subject separated by ; <#pat> <#child> <#al>, <#chaz>, <#mo>; <#age> 24 ; <#eyecolour> blue. 3

4 Anonymous Definitions Sometime want to declare something exists but without specifying a way to refer to it elsewhere Use square brackets [ ] <#pat> <#child> [ <#age> 4 ], [ <#age> 3 ]. Sharing Concepts Using ontologies to share concepts is central to Semantic Web Ontology developers should use existing defined concepts whenever possible Use URIs to define name spaces Assuming previous declarations were in ontology: In a new ontology we can pf: pf:pat <#employer> <#bigcorp>. In these examples we assume the following rdf: rdfs: owl: xsd: < By convention we assume : <#> so that above becomes pf:pat :employer :bigcorp List shorthand In RDF a collection of things is indicated using rdf:collection rdf:bag - unordered collection rdf:seq ordered collection rdf:alt collection of alternative values In N3 lists are white space separated and enclosed in parentheses ( ) :sibling rdf:alt ( :sister :brother ). Making Vocabularies RDFS defines the terms of resources and classes: everything in RDF is a resource classes are also resources, but they are also a collection of possible resources (i.e., individuals/instances) Relationships are defined among resources: typing : an individual belongs to a specific class subclassing : instance of one is also the instance of the other a bit like in object-based programming but the same resource can be subclass of multiple classes OWL supports classes and subclassing, but with richer semantics Relationships between classes, between properties and between classes and properties Much improved inference capabilities about relationships and subsumption of classes Based on Description Logic [Ivan Herman] Example: Defining terms and a subclass relationship Define the term Room Define term Restroom and state that a Restroom is a subclass of Room Note: owl:thing is a predefined OWL Class and is the root of all classes [Tim Berners Lee] :Room rdf:type rdfs:class Or replacing rdf:type with a :Room a rdfs:class :Restroom a owl:class; rdfs:subclassof :Room. Properties Property is a special class (rdf:property) i.e., properties are also resources so properties can existing in their own right, separate from any class yet declared unlike OO class attributes Properties declare relationship between two things :sister a rdf:property Properties are constrained by their range and domain i.e., what individuals can be on the left or on the right :sister rdfs:domain :Person rdfs:range :Woman There is also a possibility for a sub-property :stepsister rdfs:subpropertyof :sister Note, by convertion we start class identifiers with upper case, property identifiers with lower case [Ivan Herman] 4

5 Defining Properties in RDFS In RDF Schema the rdf:property is used both to Relate one Resource to another Resource For example, a accessrestrictedtogender property can relate a Restroom to a Gender Relate a resource to a rdfs:literal or datatype For example, a latitude property relates a Room to a xsd:string type OWL provides different statements for two cases owl:objectproperty is used to relate a resource to another What range :accessrestrictedtogender a owl:objectproperty; of values `what rdfs:range :Gender; classes is this rdfs:domain :Restroom. property associated owl:datatypeproperty is used to relate a resource to a rdfs:literal or XML with schema data type :latitute a owl:datatypeproperty rdfs:range < rdfs:domain :Place Class Properties in OWL Associate the property (defined elsewhere) with the Class by using combination of rdfs:subclassof and owl:onproperty Define local restrictions on that property using owl:restriction Cardinality restrictions can be stated on a property with respect to a particular class mincardinality: at least the given number maxcardinality: at most the given number Cardinality: exactly the given value :Wine a owl:class; rdfs:subclassof :PotableLiquid; rdfs:subclassof [ owl:restriction [ owl:onproperty :madefromgrape; owl:mincardinality 1 ]]; rdfs:subclassof [ owl:restriction [ owl:onproperty :locatedin owl:mincardinality 1 ]]. Assertions between Classes OWL provides several other mechanisms for defining classes owl:equivalentclass allows you to state that two classes are synonymous owl:disjointwith allows you to state that an instance of this class cannot be an instance of another E.g. Man and Woman could be stated as disjoint classes owl:unionof allows you specify that a class contains things that are from more than one class (similar to AND) E.g. Restroom could be defined as a union of MensRoom and LadiesRoom owl:intersectionof allows you to specify that a class contains things that are both one thing and another (similar to OR) owl:complementof allows you specify that a class contains things that are not other things (similar to NOT) E.g. Children are not SeniorCitizens Examples of Assertions Between Classes equivalentclass and unionof :AtomicPlaceInBuilding a owl:class; rdfs:subclassof AtomicPlace; owl:equivalentclass owl:class [ owl:unionof [ :Room :Hallway :Stairway :OtherPlaceInBuilding ]]. disjointwith :Stairway a owl:class; rdfs:subclassof :AtomicPlaceInBuilding; owl:disjointwith :Room; owl:disjointwith :Hallway. In addition OWL allows you state that a property is Symmetric If the pair (x.y) is an instance then it can be deduced that (y,x) is also an instance. Example, property adjacentroom property of Room or friend property of person Transitive If a property is transitive, then if the pair (x.y) is an instance of P and (y,z) is an instance of P then it can be deduced that (x,z) is also an instance. Example, property isspatiallysubsumedby Functional If a property is functional, then it has no more than one value for each individual, that is it can have 0 or 1 Example, property Address of a Building InverseOf One property may be stated to be the inverse of another property. It can be deduced that if the property P1 is stated to be the inverse of P2, then if X is related to Y via P2 then Y is related to X via P1 Example, property spatiallysubsumes InverseFunctionalProperty Only one thing can have instance of that property, e.g. coordinates Summary Example :LargeConferenceRoom a :Room; :address G.02 ; :spatiallysubsumedby O Reilly Institute :adjacentroom SmallConferenceRoom :coordinates 44,55. We can deduce: 1. The O Reilly Institute spatially subsumes the Large Conf Room (since spatiallysubsumedby is an inverse property) 2. The Small Conference Room is adjacent to Large Conference Room (since adjacentroom is symmetric) 3. Only the Large Conference Room can be found at coordinates 44,55 (since coordinates is inverse functional) 4. The Large Conference Room has only one address (since address is functional) 5

6 Hierarchy of Properties rdf:property owl:objectproperty owl:datatypeproperty owl:functionalproperty owl:inversefunctionalproperty owl:symmetricproperty owl:transitiveproperty Specifying Restrictions on range of values rdfs:range allows restriction on values of a property to a class and all its subclasses OWL allows for further restrictions to be specified allvaluesfrom provides for a local range restriction somevaluesfrom states that at least one value for that property is of specified type hasvalue states that the property is required to have a particular instance as a value Summary of Class Properties rdfs:class owl:class owl:restriction Properties: subclassof: rdfs:class Properties: intersectionof: rdf:list unionof: rdf:list complementof: owl:class oneof: rdf:list equivalentclass: owl:class disjointwith: owl:class Properties: onproperty: rdf:property allvaluesfrom: rdfs:class hasvalue: somevaluesfrom: rdfs:class cardinality: xsd:nonnegativeinteger mincardinality: xsd:nonnegativeinteger maxcardinality: xsd:nonnegativeinteger Instance Document Annotations Sometimes useful to explicitly annotate instance documents sameas: Two individuals may be stated to be the same. For example :BoardRoom a :Room; owl:sameindividualas :LargeConferenceRoom differentfrom: An individual may be stated to be different from other individuals alldifferent: A number of individuals may be stated to be mutually distinct For example, Large and Small Conference Rooms are both of type room, but we want to make clear they are distinct rooms Summary An OWL document contains the following kind of information: Class hierarchy info: an OWL document defines class/subclass relationships. Synonym info: an OWL document identifies equivalent classes and equivalent properties. Class association info: an OWL document maps one or more classes to one or more classes, via a property (i.e., domain/range info). Property metadata info: an OWL document contains a lot of metadata for properties. Class definition info: an OWL document specifies the composition of David [DARPA Lewis 2003] Symmetric: if P(x,y) then P(y,x) inverseof: if P1(x,y) then P2(y,x) Transitive: if P(x,y) and P(y,z) then P(x,z) Functional: if P(x,y) and P(x,z) then y=z InverseFunctional: if P(x,y) and P(z,y) then x=z allvaluesfrom: P(x,y) has y=allvaluesfrom(c) somevaluesfrom: P(x,y) has y=somevaluesfrom(c) hasvalue: P(x,y) and y=hasvalue(i) cardinality: cardinality(p) = n mincardinality: mincardinality(p) = n maxcardinality: maxcardinality(p) = n equivalentproperty: P1 = P2 intersectionof: C = intersectionof(c1, C2, ) unionof: C = unionof(c1, C2, ) complementof: C = complementof(c1) oneof: C = oneof(i1, I2, ) equivalentclass: C1 = C2 disjointwith: C1!= C2 sameindividualas: I1 = I2 differentfrom: I1!= I2 AllDifferent: I1!= I2, I1!= I3, I2!= I3, Thing: C1, C2,, I1, I2,, P1, P2, Summary of OWL Capabilities (by Roger Costello and Rob Simmons) InverseFunctional P x y 1 x Functional P 1 InverseFunctional & Functional P x y 1 1 LEGEND Properties: P, P1, P2, P3, Generic classes: C, C1, C2, C3, Specific classes: x, y, z Instances: I, I1, I2, I3, A non-negative integer: n P(x,y) is read as: property P relates domain x to range y y 6

7 References [Ludascher 03] Bertram Ludascher, CSE-291 course, University of California, San Diego [Carole Goble, Nigel Shadbolt, Ontologies and the Grid Tutorial] [DARPA 2003] Tutorial by Costello and Jacobs of MITRE funded by DARPA [Ivan Herman] [Tim Berners Lee] The OWL Guide provides a description of OWL, with many examples: Here is the URL to the OWL Reference document: 7