BBY 464 Semantic Information Management Spring 2016 Ontologies

BBY 464 Semantic Information Management (Spring 2016) Ontologies and OWL: Web Ontology Language Yaşar Tonta & Orçun Madran [yasartonta, orcunmadran]@gmail. com Hacettepe University Department of Information Management

Semantic Web

From Syntactic to Semantic Interoperability

Ontologies

Ontologies (cont’d) • Definition and classification of concepts and entities, and the relationships between them • Based on basic elements of RDF • Adds more vocabulary for describing properties and classes

Classes • • • Person Country Animal Book Author. . .

Instances

Properties • Person has first name, middle initial, last name, birthdate, age. . . as properties • Book has author, title, place of publication. . . as properties • . . .

Relations

More vocabulary? • Relationship between classes (eg, disjoint. With) • Equality (eg, same. As) • Richer properties (eg, symmetrical) • Class property restrictions (eg, all. Values. From)

Relationship between classes • disjoint. With – resources belonging to one class cannot belong to the other <Person> <disjoint. With> <Country> • complement. Of – members of one class are all the resources that do not belong to the other <Inanimate. Things> <complement. Of> <Living. Things>

Equality • same. As – indicates that two resources actually refer to the same real-world thing or concept <tonta> <same. As> <yasartonta> • Equivalent class – indicates that two classes have the same set of members <Coop. Board. Members> <equivalent. Class> <Coop. Residents>

Richer properties • Symmetric – a relationship between A and B is also true between B and A <David. Beckham> <married. To> <Victoria. Beckham> implies <Victoria. Beckham> <married. To> <David. Beckham> • Transitive – a relationship between A and B and between B and C is also true between A and C <piston> <is. Part. Of> <engine> <is. Part. Of> <automobile> implies <piston> <is. Part. Of> <automobile>

Class property restrictions • Define the members of a class based on their properties • all. Values. From – resources with properties that only have values that meet this criteria – Example: Property: has. Parents, all. Values. From: Human – Resources that meet this criteria can be defined as also being members of the Human class

Class property restrictions (cont’d) • some. Values. From – resources with properties that have at least one value that meets criteria – Example: Property: has. Graduated, some. Values. From: College – Resources that meet this criteria can be defined as being members of the College. Graduates class

Seems complicated? Why do it? • These capabilities allows systems to express and make sense of first-order logic – All humans are mortal – Socrates is a human – Therefore, Socrates is mortal

First-order logic? • But, first, let’s describe propositional logic • “Yaşar is professor”. This is a proposition in classical logic and it is either true or false. • So is “Orçun is professor” • These two propositions can only be combined with defined operators • Let’s call these two propositions p and q, respectively • p=>q (if Yaşar is professor, then Orçun is professor, too) • p∧q; p∨q; ≠p • Above propositions will produce either true or false.

First-order logic? (cont’d) • First-order logic uses quantifiers (or variables) to model. • Take “Yaşar is professor”, for example. • Yaşar (a) =>Professor (a) • Interpretation: There exists an a whose name is Yaşar and who is professor. • What kind of “a” is this? Is it applicable to all “a”s? Is it true for every case? • No. (Otherwise, all persons with the name Yaşar should be professor!)

First-order logic? (cont’d) • There are two symbols in first-order logic: • (every, all) and (there exists such that) • a(Yaşar (a) ∧ Professor(a) -> There exists such a’s whose name is Yaşar and who is Professor • a a (Children’s librarian (a) => Librarian (a) -> For all a’s, if a is Children’s librarian, then a is at the same time is Librarian

Inferences • Create new triples based on existing ones • Deduce new facts based on stated facts <piston> <is. Part. Of> <engine> <is. Part. Of> <automobile> implies <piston> <is. Part. Of> <automobile>

Vocabularies

Data

OWL: Web Ontology Language • Three flavors of OWL • OWL Lite: uses a subset of the capabilities • OWL DL: uses all capabilities, but some are used in restricted ways • OWL Full: unrestricted use of capabilities; no guarantee that all resulting statements are valid.

OWL

Web Protege

Beer Ontology

Bib. Frame

DCterms

CIDOC CRM

Exercise • Pls visit webprotege. stanford. edu and register (free). • Make yourselves familiar with various types of ontologies created using OWL and explore the classes, properties and relationships defined. • The next step would be to create your own ontology using OWL and upload it to webprotege web site (details coming).

Sources used • R. Lovinger, RDF & OWL, http: //www. slideshare. net/rlovinger/rdf-andowl? qid=c 254 fb 47 -da 1 e-4335 -99 a 9199 b 2 b 65 ecba&v=&b=&from_search=1 • D. Willems, What is an ontology? http: //www. slideshare. net/don_willems/what-areontologies/2 COMMIT_EFOODLABIn_computer_science_and • Ş. E. Şeker, Birinci derece mantık (First order logic), http: //bilgisayarkavramlari. sadievrenseker. com/2010/03/2 4/birinci-derece-mantik-first-order-logic/