Cornell CS Semantic Web Ontologies & Data Models CS 502 – Carl Lagoze – Cornell University Acknowledgements: Eric Miller Dieter Fensel

Cornell CS Components of the Semantic Web

Cornell CS What is an Ontology? A formal specification of conceptualization shared in a community Vocabulary for defining a set of things that exist in a world view Formalization allows communication across application systems and extension Parallel concepts in other areas: –Domains: database theory –Types: AI –Classes: OO systems –Types/Sorts: Logic Global vs. Domain-specific

Cornell CS XML and RDF are ontologically neutral No standard vocabulary just primitives –Resource, Class, Property, Statement, etc. Compare to classic first order logic –Conjunction, disjunction, implication, existential, universal quantifier

Cornell CS Components of an Ontology Vocabulary (concepts) Structure (attributes of concepts and hierarchy) Logical characteristics of concepts & attributes –Domain and range restrictions –Properties of relations (symmetry, transitivity)

Cornell CS Wordnet On-line lexical reference system, domain- independent >100,000 word meanings organized in a taxonomy with semantic relationships –Synonymy, meronymy, hyponymy, hypernymy Useful for text retrieval, etc.

Cornell CS CYC Effort in AI community to accommodate all of human knowledge!!! Formalizes concepts with logical axioms specifying constraints on objects and classes Associated reasoning tools Contents are proprietary but there is OpenCyc –

Cornell CS Ontologies for the Web Lots of Participants and $$$ –Web Ontology Working Group –Distributed Agent Markup Language –Ontology Inference Layer –OntoWeb –Schemas Project DAML+OIL – develop standard for encoding ontologies on top of RDF Schema

Cornell CS Extending RDF(S) with DAML+OIL RDFS DAML+ OIL Class, sub-class definition Property (attribute), sub-property definition Domain, range constraints Class definition: Conjunction, disjunction, negation Property constraints: universality, existence, cardinality Properties of properties: transitivity, symmetry

Cornell CS DAML class building operations disjointWith –No vegetarians are carnivores sameClassAs (equivalence) Enumerations (on instances) –The Ivy League is Cornell, Harvard, Yale, …. Boolean set semantics (on classes) –Union (logical disjunction) –Intersection (logical conjunction) –complimentOf (logical negation) All non-carnivores are vegetarians

Cornell CS DAML property building operations & restrictions Unique Property: subject identifies object Unambiguous Property: object identifiers subject Inverse of –hasChild is inverse of hasParent Transitivity (e.g., descendent relationship) Cardinality (exact, max, min)

Cornell CS DAML+OIL DataTypes Full use of XML schema data type definitions Examples –Define a type age that must be a non-negative integer –Define a type clothing size that is an enumeration “small” “medium” “large”

Cornell CS DAML+OIL Instance Creation Create individual objects filling in slot/attribute/property definitions Bill

Cornell CS Language Comparison DTDXSDRDF(S)DAML+OIL Bounded lists (“X is known to have exactly 5 children”) X Cardinality constraints (Kleene operators) XXX Class expressions (unionOf, complementOf) X Data types XX Enumerations XXX Equivalence (properties, classes, instances) X Formal semantics (model-theoretic & axiomatic) X Inheritance XX Inference (transitivity, inverse) X Qualified contraints (“all children are of type person” X Reification XX

Cornell CS Some useful RDF tools JENA toolkit for manipulating RDF models – RDFSviz for visualizing ontologies expressed as RDF schema – W3C RDF validation service for parsing and view RDF instances –

Cornell CS But modeling the way things “are” is not always enough ABC – Modeling how things (or their descriptions) change

Cornell CS ABC Example Leo Tolstoy, who was born in Moscow in 1828, authored a manuscript called “War and Peace” in In 1860, that manuscript as the book “Illustrated War and Peace”, was published by Russia Publishers, with Tolstoy supplying the illustrations.

Cornell CS ABC Model Overview (Digital) objects have inherent lifecycle characteristics –Model creation, evolution, and transformation of objects over time. Notions of temporality are given first-class status Measuring utility of metadata through query- ability –Ability to answer who, what, when, where comments that are difficult in simpler models Descriptions provide a world context From ambiguous to exact information – only say what you know

Cornell CS Entities and their Properties Entities are anchor points for set of properties Entities "change" by modification of property sets –Model does not distinguish between "change of nature" and "change of description" Dual facets of Entities –Universal – object and its property set that is "global" to the description –Existential – object instances and their property sets that are periodic ("stateful")

Cornell CS Situations Establish a time period –granularity determined by the longevity of entity state within situation Situations and actualities –Situations provide context for associating entities in their existential facet. –Entities can exist out of situation to express their universal properties

Cornell CS Events Transition marker point between situations –Always have a time property Levels of increasing knowledge –Something happened at a time (that caused change in situation) –Type thing happened at some time –Anchor point for multiple actions (verbs) within a happening.

Cornell CS Events, Actions, Agents Events provide a context for associating actions ("verbs"), 1-n Actions provide a context for participation of agents, 1-n Participation type can be specialized for domain

Cornell CS Causality – verbs & predicates Association of actions to Actualities in preceding situation is weak Increasing knowledge of association (esp. important in rights management) –involves –hasTool –hasPatient

Cornell CS Intellectual Property Notion of "ability to copy" is the determining factor Promote abstraction to work and actuality to manifestation and item