1. Introduction to Ontologies focussing on OWL Nick Drummond

2. Overview Getting to Know OWL How Can I Recognise OWL? OWL Constructs Overview –More About Classes –More About Properties Reasoners & Inference Is OWL Dangerous? –Common Mistakes –The Open World Problem Creating & Using OWL Where Can I find Examples?

3. Getting to Know OWL OWL is the Web Ontology Language It’s part of the Semantic Web framework It’s a standard

4. OWL Has Explicit Semantics Can therefore be used to capture knowledge in a machine understandable way

5. Class (BlueThing) does not mean anything Class (BlueThing complete owl:Thing restriction (hasColour someValuesFrom (Blue)) ) OWL Helps Us… Describe something, rather than just name it.

6. Lite partially restricted to aid learning curve lite DL = Description Logic Description Logics are a fragment of First Order Logic (FOL) that can be reasoned with DL Full unrestricted use of OWL constructs, but cannot reason Full OWL comes in 3 Flavours

7. OWL is often thought of as an extension to RDF which is not strictly true OWL is a syntax independent language that has several common representations –Abstract Syntax –N3 –RDF/XML Many tools try to completely abstract away from the syntax How Can I Recognise OWL?

8. One of the clearer human-readable syntaxes Class(SpicyPizza complete annotation(rdfs:label "PizzaTemperada"@pt) annotation(rdfs:comment "Any pizza that has a spicy topping is a SpicyPizza"@en) Pizza restriction(hasTopping someValuesFrom(SpicyTopping)) ) OWL Syntax: abstract syntax

9. Recommended for human-readable fragments default:SpicyPizza a owl:Class ; rdfs:comment "Any pizza that has a spicy topping is a SpicyPizza"@en ; rdfs:label "PizzaTemperada"@pt ; owl:equivalentClass [ a owl:Class ; owl:intersectionOf (default:Pizza [ a owl:Restriction ; owl:onProperty default:hasTopping ; owl:someValuesFrom default:SpicyTopping ]) ]. OWL Syntax: N3

10. Recommended for serialisation PizzaTemperada Any pizza that has a spicy topping is a SpicyPizza OWL Syntax: RDF/XML

11. Tools “Hiding the Syntax” In the tools, you are more likely to find OWL looking more like a tree of classes And their descriptions

12. PersonCountry Class (concept) Animal Individual (instance) Belgium Paraguay China Latvia Elvis Hai Holger Kylie S.Claus Rudolph Flipper lives_in has_pet arrow = relationship label = Property has_pet OWL Constructs Overview

13. Eg Mammal, Tree, Person, Building, Fluid, Company Classes are sets of Individuals aka “Type”, “Concept”, “Category”, “Kind” Membership of a Class is dependent on its logical description, not its name Classes do not have to be named – they can be logical expressions – eg things that have colour Blue OWL Constructs: Classes

14. Eg hasPart, isInhabitedBy, isNextTo, occursBefore Properties are used to relate Individuals We often say that Individuals are related along a given property Relationships in OWL are binary: Subject  predicate  Object Individual a  hasProperty  Individual b nick_drummond  givesTalk  owl_overview_talk_Dec_2005 OWL Constructs: Properties

15. Eg me, you, this talk, this room Individuals are the objects in our domain of interest aka “Instance”, “Object” Individuals may be (and are likely to be) a member of multiple Classes OWL Constructs: Individuals

16. Describing a Class Hierarchy Types of Class Describing the Classes –Relationships in OWL More About Classes

17. Describing a Class Hierarchy 2 important things to say about classes: –Where can we put them? –Where can’t we put them? Animal Shark Hot Air Balloon?

18. Subsumption is the primary axis (relationship) in OWL Superclass/subclass relationship, “isa” All members of a subclass must be members of its superclasses Animal subsumes Shark Animal is a superclass of Shark Shark is a subclass of Animal All Sharks are also Animals owl:Thing superclass of all Classes Shark Animal Subsumption in OWL Where can we put this class?

19. Where can’t we put this class? Regardless of where they exist in the hierarchy, OWL assumes that classes can overlap Animal Hot Air Balloon = individual By default, an individual could be both an Animal and a Hot Air Balloon at the same time Disjointness in OWL

20. Where can’t we put this class? Stating that 2 classes are disjoint means Hot Air Balloon = individual Something cannot be both an Animal and a Hot Air Balloon at the same time Animal Disjointness in OWL Hot Air Balloon can never be a subclass of Animal (and vice-versa) This can help us find errors

21. Types of Class owl:Thing (everything) owl:Nothing (nothing) Animal (primitive named class) hasDangerLevel some Dangerous (anonymous class - restriction) DangerousAnimal (defined named class)

22. Primitive vs Defined Blue Things Sharks “Smart Class” Acts like a query Describe the necessary features of the members Eg live underwater Like primitive, but also: define necessary conditions that are also sufficient to recognise a member Eg have colour Blue “Natural Kinds” “All things that have colour blue are members of this class” “All sharks live underwater, but not everything that lives underwater is a shark”

23. Anonymous Classes Made up of logical expressions –Unions and Intersections (Or, And) –Complements (Not) –Enumerations (specified membership) –Restrictions (related to Property use) The members of an anonymous class are the set of Individuals that satisfy its logical definition

24. Relationships in OWL In OWL-DL, relationships can only be formed between Individuals or between an Individual and a data value. (In OWL-Full, Classes can be related, but this cannot be reasoned with) Relationships are formed along Properties We can restrict how these Properties are used: –Globally – by stating things about the Property itself –Or locally – by restricting their use for a given Class

25. Restrictions Restrictions are a type of anonymous class They describe the relationships that must hold for members (Individuals) of this class

26. An example Existential restriction on primitive class Shark: necessarily hasMouthPart some Teeth SharkTeeth hasMouthPart “Every member of the Shark class must have at least one mouthpart from the class Teeth”

27. An example Existential restriction on primitive class Shark: necessarily hasMouthPart some Teeth SharkTeeth hasMouthPart “There can be no member of Shark, that does not have at least one hasMouthPart relationship with an member of class Teeth”

28. Restriction Types  Existential, someValuesFrom “Some”, “At least one”  Universal, allValuesFrom “Only”  hasValue“equals x”  Cardinality“Exactly n”  Max Cardinality“At most n”  Min Cardinality“At least n”

29. Different Types: –Object Property relates Individuals to Individuals –Datatype Property relates Individuals to data (int, string, float etc) –Annotation Property for attaching metadata to classes, individuals or properties More About Properties

30. Property Characteristics Domain and range can be set A property hierarchy can be created Inverse properties can be set Properties can be: –Transitive –Functional –Inverse Functional –Symmetric

31. Reasoner: A clever (probably magic) black box designed by clever people Best to let them worry about how they work ? ? ? ! ! ! Reasoners & Inference

32. Reasoners: Inference Reasoners are used to infer information that is not explicitly contained within the ontology You may also hear them being referred to as Classifiers Standard reasoner services are: –Consistency Checking –Subsumption Checking (Automatic Subsumption) –Equivalence Checking –Instantiation Checking

33. Consistency Checking Shark (primitive class) Animal and eats some (Person and Seal) Person Seal Inconsistent = cannot contain any individuals Disjoint (Person, Seal) Person and Seal = empty Cannot have some empty

34. Automatic Classification Trivial example DangerousAnimal (defined class) Animal and hasMouthPart some Teeth Shark (primitive class) Animal and hasMouthPart some Fangs Teeth Fangs

35. When to use a Reasoner We often use one during development as an ontology compiler. A well designed ontology can be compiled to check its meaning is that intended Or at publish time – so many inferences are already made for the user apps Or at runtime in applications as a querying mechanism (esp. useful for smaller ontologies)

36. Reasoners and the tools Many of the editing tools and APIs support the use of reasoners implementing the DIG interface This means that the reasoner you choose is independent of the application using it, so you can choose the implementation you want depending on your needs (eg some may be more optimised for speed/memory, others may have more features) These reasoners typically set up a service running locally or on a remote server Protégé-OWL, for example can connect to reasoners over an http:// connection

37. Yes, in the wrong hands!! 3 major issues –Because of the explicit semantics its important that OWL be used as intended –Learning OWL is non-trivial and some common mistakes are made by most beginners –OWL operates under the Open World Assumption Is OWL Dangerous?

38. Use OWL Correctly As we’ve seen, OWL is more than just a syntax Please do not decide to interpret it in your own way Doing this makes reuse impossible

39. Common Modelling Mistakes Some of the common mistakes made when modelling have been enumerated They include: –Misuse of property domain and range –Misunderstanding of intersections and other constructs –Not understanding the Open World Assumption –Misuse/lack of of disjoints See OWL Pizzas: Common errors & common patterns http://www.co-ode.org/resources/papers/

40. Open World Assumption In a closed world (like DBs), the information we have is everything On the Semantic Web, we want people to be able to extend our models. In this open world, we assume there can always more information added later Where a database, for example, returns a negative if it cannot find some data, the reasoner makes no assumption about the completeness of the information it is given The reasoner cannot determine something does not hold unless it is explicitly stated in the model

41. Open World Assumption hasMouthPart some Do sharks have a trunk? Can sharks fly hot air balloons?

42. Closure hasMouthPart some hasMouthPart only Sharks definitely cannot have trunks (as long as Trunks are disjoint from Teeth) But someone could still extend our description to say that Sharks can fly Hot Air Balloons

43. Issues Editors Programming APIs Storage Reasoners Creating & Using OWL

44. Issues Suitability for purpose –Open vs Closed World problems –When to use a reasoner How to expose/hide the ontology –Interfaces/ontology services Ontology Development Methodologies –Small team, tight knit –Open “folksonomies”

45. Editing the RDF/XML by hand is probably not recommended (as we have seen) Ontologies range in size, but because of their explicit nature they require verbose definitions Thankfully we have tools to help us reduce the syntactic complexity However, the tools are still in the process of trying to reduce the semantic complexity Building ontologies in OWL is still hard Editing OWL

46. OWL Editors SWOOP http://www.xml.com/pub/a/2004/07/14/onto.html

47. Is a knowledge modelling environment Is free, open source software Is developed by Stanford Medical Informatics Has a large user community (approx 30k) http://protege.stanford.edu

48. core is based on object oriented modelling has an open architecture that allows other modelling languages to be built on top supports development of plugins to allow backend / interface extensions supports OWL through the Protégé-OWL plugin

50. Programming with OWL Protégé OWL API Wonderweb OWL API Jena pOWL API

51. API features Parsing / Serialisation Model Manipulation Reasoning Querying Modularisation

52. Storage of OWL Files (RDF/XML) Databases (triplestores) –3Store –Sesame –Jena –InstanceStore (Individuals)

53. Reasoners FaCT++ Pellet RACER

54. The w3c OWL pages are a good place to start The w3c Semantic Web Best Practices and Deployment Working Group Tutorials and courses run by Manchester and other establishments generate a large number of examples (eg CS646) Where Can I Find Examples?

55. Example Ontologies OBO – Open BioMedical Ontologies The Gene Ontology Bio tutorial and Pizza tutorial examples on the CO-ODE site Libraries are commonly published on OWL editor websites Search using Google or Swoogle

56. Example Applications PizzaFinder (dummy query application) COHSE – dynamic hyperlinking using ontologies Protein Phosphatase Modelling – ask Robert Stevens OWL Validator GONG (Gene Ontology Next Generation) AKT http://www.aktors.org/ http://www.aktors.org/ The Semantic Web Challenge http://challenge.semanticweb.org/ http://challenge.semanticweb.org/

57. For tutorial materials, examples and links to some of the tools go to the CO-ODE site http://www.co-ode.org/ (in)famous pizza tutorial Where Do I Go Next?