OWL. Web Ontology Languagge

Size: px

Start display at page:

Download "OWL. Web Ontology Languagge"

Brendan Holt
5 years ago
Views:

1 OWL Web Ontlgy Languagge

2 Origins 2 DAML OIL RDF DAML = DARPA Agent Markup Language OIL = Ontlgy Inference Layer DAML+OIL OWL

3 Purpse The purpse f OWL is identical t RDF Schemas - t prvide an XML vcabulary t define classes, their prperties and their relatinships amng classes. RDF Schema enables us t express very rudimentary relatinships and has limited inferencing capability. OWL enables us t express much richer relatinships, thus yielding a much enhanced inferencing capability. A benefit f OWL is that it facilitates a much greater degree f inference making than with RDF Schemas.

4 Requirements Ontlgy languages allw users t write explicit, frmal cnceptualizatins f dmains mdels. The main requirements are: 1. a well-dened syntax, a necessary cnditin fr machine-prcessing f infrmatin 2. a well-defined semantics describes precisely the meaning f knwledge 3. efficient reasning supprt 4. sufficient expressive pwer 5. cnvenience f expressin.

5 Frmal Semantics Class membership: If x is an instance f a class C, and C is a subclass f D, then we can infer that x is an instance f D. Equivalence f classes: If class A is equivalent t class B, and class B equivalent t class C, then A is equivalent t C, t. Cnsistency: Suppse we have declared x t be an instance f the class A. Further suppse that - A is a subclass f B C - A is a subclass f D - B and D are disjint Then we have an incnsistency because A shuld be empty, but has the instance x. This is an indicatin f an errr in the ntlgy. Classicatin: If we have declared that certain prperty-value pairs are sufficient cnditin fr membership f a class A, then if an individual x satisfies such cnditins, we can cnclude that x must be an instance f A.

6 Semantics Semantics is a prerequisite fr reasning supprt: Derivatins such as the previus can be made mechanically, instead f being made by hand. Reasning supprt is imprtant because it allws ne t check the cnsistency f the ntlgy and the knwledge; check fr unintended relatinships between classes. autmatically classify instances in classes Autmated reasning supprt allws ne t check many mre cases than what can be dne manually. Checks like the abve are valuable fr designing large ntlgies, where multiple authrs are invlved; integrating and sharing ntlgies frm varius surces.

7 RDF & RDF Schema Using RDF Schema we cannt declare range restrictins that apply t sme classes nly. Fr example, we cannt say that cws eat nly plants, while ther animals may eat meat, t. Disjintness f classes: Smetimes we wish t say that classes are disjint. Fr example, male and female are disjint. But in RDF Schema we can nly state subclass relatinships, e.g. female is a subclass f persn. Blean cmbinatins f classes: Smetimes we wish t build new classes by cmbining ther classes using unin, intersectin and cmplement. Fr example, we may wish t define the class persn t be the disjint unin f the classes male and female. RDF Schema des nt allw such definitins.

8 RDF & RDF Schema Cardinality restrictins: Smetimes we wish t place restrictins n hw many distinct values a prperty may r must take. Fr example, we wuld like t say that a persn has exactly tw parents, and that a curse is taught by at least ne lecturer. Again such restrictins are impssible t express in RDF Schema. Special characteristics f prperties: Smetimes it is useful t say that a prperty is transitive (like greater than"), unique (like is mther f"), r the inverse f anther prperty (like eats" and is eaten by").

9 An Ontlgy Language we need an ntlgy language that is richer than RDF Schema, a language that ffers these features and mre. In designing such a language ne shuld be aware f the tradef between expressive pwer and efficient reasning supprt. Generally speaking, the richer the language is, the mre inefficient the reasning supprt becmes, ften crssing the brder f nncmputability. Thus we need a cmprmise, a language that can be supprted by reasnably efficient reasners, while being sufficiently expressive t express large classes f ntlgies and knwledge.

10 OWL OWL FULL OWL DL OWL LITE

11 OWL FULL The entire language is called OWL Full, and uses all the OWL languages primitives. It als allws t cmbine these primitives in arbitrary ways with RDF and RDF Schema. The advantage f OWL Full is that it is fully upward cmpatible with RDF, bth syntactically and semantically: any legal RDF dcument is als a legal OWL Full dcument, and any valid RDF/RDF Schema cnclusin is als a valid OWL Full cnclusin. the language has becme s pwerful as t be undecidable, dashing any hpe f cmplete (let alne efficient) reasning supprt

12 OWL DL restricts the way in which the cnstructrs frm OWL and RDF can be used. The advantage f this is that it permits efficient reasning supprt. The disadvantage is that we lse full cmpatibility with RDF: an RDF dcument will in general have t be extended in sme ways and restricted in thers befre it is a legal OWL DL dcument. Cnversely, every legal OWL DL dcument is still a legal RDF dcumen

13 OWL LITE An ever further restrictin limits OWL DL t a subset f the language cnstructrs. Fr example, OWL Lite excludes enumerated classes, disjintness statements and arbitrary cardinality (amng thers). The advantage f this is a language that is bth easier t grasp (fr users) and easier t implement (fr tl builders). The disadvantage is f curse a restricted expressivity.

14 Cmpatibility Every legal OWL Lite ntlgy is a legal OWL DL ntlgy. Every legal OWL DL ntlgy is a legal OWL Full ntlgy. Every valid OWL Lite cnclusin is a valid OWL DL cnclusin. Every valid OWL DL cnclusin is a valid OWL Full cnclusin.

15 OWL, RDF, and RDFS OWL still uses RDF and RDF Schema t a large extent: all varieties f OWL use RDF fr their syntax instances are declared as in RDF, using RDF descriptins and typing infrmatin

16 Header Rt Elements Assertins

17 Class Elements defined using a wl:class element disjint

18 Class Elements Equivalence

19 Prperty Elements In OWL there are tw kinds f prperties: 1. Object prperties which relate bjects t ther bjects. Examples are istaughtby, supervises etc. 2. Datatype prperties which relate bjects t datatype values. Examples are phne, title, age etc. OWL des nt have any predefined data types, nr des it prvide special denifitin facilities. Instead it allws ne t use XML Schema data types, thus making use f the layered architecture the Semantic Web

20 Prperty

21 Prperty

22 Prperty Restrictins

23 Prperty Restrictins

24 Prperty Restrictins

25 Prperty Restrictins

26 Special Prperty

OWL a glimpse. OWL a glimpse (2) requirements for ontology languages. requirements for ontology languages

OWL a glimpse. OWL a glimpse (2) requirements for ontology languages. requirements for ontology languages OWL a glimpse OWL Web Ontology Language describes classes, properties and relations among conceptual objects lecture 7: owl - introduction of#27# ece#720,#winter# 12# 2# of#27# OWL a glimpse (2) requirements