Ontology 101 PHIN Ontology Workshop August 2008

Ontology 101 Agenda What is (an) Ontology? What do we mean when we use the word? The main types of Ontologies Basics of Frames Basics of OWL Ontology uses in applications When to use what?

Ontology Defined Ontology is the study of the categories of things that exist or may exist in some domain. Ontology is the product of such a study, and is a catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D. -John F. Sowa

Ontology Defined…Again ”An ontology is a formal, explicit specification of a shared conceptualisation.” -(Gruber, 1993)

What Do we Mean by Ontology? "An explicit representation in a formal specification of the objects, concepts and other entities that are assumed to exist in some area of interest and the relationships that hold among them.“ –(OntoReason, 2006)

“Things” People call Ontologies Folksonomy –The collection of public “tags” resulting from social categorization – think keywords, Del.icio.us Taxonomy –A structured hierarchy of classes connected by is-a relations – for example Ethnicity list Thesaurus –Adds equivalence relations (broader than, narrower than, etc) and associative relations (preferred term, related term, etc)

What is a KnowledgeBase? An Ontology populated with instances of interest in the domain of discourse and any rules that are included. Instances need not be individuals May be classes, abstract or concrete

Ontology Types General (Upper Level Ontologies) Core Ontology - ontology consisting only of the minimal concepts required to understand the other concepts (Dublin Core for example) Domain Ontology – Covers a particular domain as fully as possible (FMA) Task - Covers a task or specific sets of tasks within a domain (OTR Ontology) Application (TB Message Validation Ontology)

Ontology Types Top Level Ontology (Upper Ontology) –Abstract categorization of all things in the world common across domains Basic Formal Ontology (BFO) Suggested Upper Merged Ontology (SUMO) Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) Cyc General Formal Ontology (GFO)

General Formal Ontology

Core Ontology

Domain Ontology

Task Ontology

Application Ontology

Common Ontology Tools Protégé – OKBC (Frames) and OWL 1.0 Protégé 4 – OWL 1.1 Semantic Works – Altova RDF and OWL TopBraid Composer – RDF, OWL 1.0, OWL 1.1 CMap COE – OWL 1.0 OntoEdit – F-Logic Ontolingua - Ontolingua

TopBraid Maestro

Protégé 4

Protégé Frames

Ontology Term Definitions Frames –Frame Any named data structure or object in a frame based ontology including classes, slots, instances and facets. –Class A representation for a conceptual grouping of similar terms. A class can be thought of as a collection of individuals. –Metaclass A representation for a conceptual grouping of similar classes where the classes are instances of the metaclass. –Instance An individual in the ontology that cannot be further subdivided –Form A visualization artifact to group metaclasses, classes, and slots in a huma readable format –Slot A role or property of an individual or a class. –Facet A restriction or constraint on a slot. The most common are Cardinality, Minimum-Cardinality, Maximum-Cardinality, and Value-Type.

Ontology Term Definitions Frames Domain –The collection of objects that can be used to satisfy the value of a slot. Range –The objects allowed to have a particular slot as a defined relation

Class Object Super-Class Class Sub-Class Slot

MetaClass Object Allows the grouping of slots to serve as a model for instances of the metaclass (classes). Allows for very complex modeling by nesting metaclasses and classes as deeply as needed.

Slots and Facets Slot Range Domain Facet

Frames Important Points Can use metaclass structures so supports very complex models (HL7 V3 nested datatypes) Uses Closed World assumptions –If it is not in the ontology it is assumed not to exist Cannot apply automated inference reasoners (we have some basic consistency checking (hierarchy, deduplication) wizards that we have written)

RDF RDF Resource Description Framework –An XML specification of triples (Resource, Property, Value) to exchange web metadata Mary Tom Jane parent child

Web Ontology Language Language for defining and instantiating Web Ontologies May include descriptions of classes, along with their related properties and instances. Designed for use by applications that need to process the content of information instead of just presenting information to humans. Facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. Based on earlier languages OIL and DAML+OIL, and is now a W3C recommendation.

RDF and OWL Species RDF Schema –(sub)classes, individuals (sub)properties, domain, range OWL Lite –conjunction, (in)equality cardinality 0/1, XML Schema datatypes inverse, transitive, symmetric allValuesFrom, someValuesFrom OWL DL –negation, disjunction hasValue, enumerated types, full cardinality OWL Full –metaclasses

Which OWL Species to Use? OWL Lite for simple taxonomy type ontologies OWL DL when reasoning is important. Uses decidable subset of first order logic to classify individuals. OWL Full when metaclasses are required. Non-decidable in some cases

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

OWL Term Definitions Classes – Corresponds to classes in Frames. May be disjoint which means they cannot have the same parents. Must be explicitly stated Individuals – Corresponds to Instances in Frames but there is no Unique Name Assumption !! Properties – Corresponds to slots in Frames but there are several types

OWL Properties Object Properties – –Link individuals to each other DataType Properties – –Link individuals to data literals, for example Bill hasAge 25 Annotation Property – –for attaching metadata to classes, individuals or properties OWL Properties are binary Subject  predicate  Object Individual a  hasProperty  Individual b Cecil_Lynch  givesTalk  Ontology_101

OWL Object Property Types Properties link two individuals together –example, hasParent links the individual Jane to the individual Mary Properties can have inverses –example, the inverse of hasParent is isChild. Properties can be functional, i.e. have a single value –Example, hasBiologicalMother would be a functional property Can be transitive, i.e. –Property P relates individual a to individual b and also individual b to individual c thus it can be inferred that a is related to c Symmetric property – –If a is related to b by property P, then b is also related to a by property P, i.e, if hasSibling relates Bill to Nancy and also relates Nancy to Bill Reflexive property- –The property must be true of itself for instance hasKnowledgeAbout must be true of Bill even if true of people Bill knows

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”

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

Reasoners Have a standard interface (DIG) FACT++ Pellet –Both of the above are open source and bundled with Protégé RacerPro –Commercial offering one of the fastest –

OWL 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

OWL Issues 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 Nick Drummond

Ontology Uses in Applications Rapidly becoming the standard for decision support knowledge foundation –To share common understanding of the structure of information among people or software agents –To enable reuse of domain knowledge –To make domain assumptions explicit –To separate domain knowledge from the operational knowledge –To analyze domain knowledge Noy and McGuinness

Concrete Uses Drive application menus Provide automated validity checking Serve up complex object constructs Repository for learning resources Filter for and exclude uninteresting data Provide the repository for expert knowledge that can be applied to surveillance reasoning

So when to use Frames and When to Use OWL? We use Frames for object modeling –Forms allow us to view the objects in their relationships. No real need to reason over the objects –Use external rules for “classification” We use OWL for terminologies –Consistency checking over large vocabulary sets (SNOMED) –Classifying lab tests (LOINC)

Common Points Both OWL and Frames have a wide range of available special function plug-ins available Both are in the Eclipse framework Both are Java based applications with Java API’s Both can be used with stand alone files or with the most popular backend databases such as MySQL, PostGres and Oracle OWL can also use Jena and Sesame RDF databases

More Info Protégé OWL Tutorial – tutorial.phphttp:// tutorial.php Protégé Frames Tutorial – tutorial-noy-mcguinness-abstract.htmlhttp://www-ksl.stanford.edu/people/dlm/papers/ontology- tutorial-noy-mcguinness-abstract.html

Questions?