This document discusses ontologies, which organize and describe related items to represent semantics. An ontology has several components: classes (collections, concepts), individuals (instances, objects), attributes (aspects, properties), values/properties (specific data for attributes), and relations (how individuals/classes relate). Good ontologies have well-defined syntax, structure, semantics, and pragmatics. They are useful for categorizing large amounts of data to improve integration and allow machine interpretation.
2. What is an Ontology? Definition: “ Ontologies are ways of organising and describing related items, and are used to represent semantics.” “ Ontology involves discovering categories and fitting objects into them in ways that makes sense.”
4. Components Classes– Collections, concepts Individuals – Instances or objects. The basic objects Attributes – aspects, properties, features Values / Properties– Individual related specific data. Value of the properties / attributes Relations – ways in which individuals/classes relate to one another Events – the changing of attributes or relations
11. Components Classes– Collections, concepts Individuals – Instances or objects. The basic objects Attributes – aspects, properties, features Values / Properties– Individual related specific data. Value of the properties / attributes
13. Components Classes– Collections, concepts Individuals – Instances or objects. The basic objects Attributes – aspects, properties, features Values / Properties– Individual related specific data. Value of the properties / attributes Relations – ways in which individuals/classes relate to one another
15. Components Classes– Collections, concepts Individuals – Instances or objects. The basic objects Attributes– aspects, properties, features Values / Properties– Individual related specific data. Value of the properties / attributes Relations – ways in which individuals/classes relate to one another Events – the changing of attributes or relations
17. What makes a good Ontology? Syntax Identified with form, format and structure of the data. Programs such as RDF (research development framework) OWL (ontology web framework) SQL and Java all improve the form and format of the ontology Structure Databases, semantic web and ontologies require good structure to organise and contain elements of the model. Semantics Semantic interpretation is the mapping between some structured subset of data and the set of objects with respect to the intended meaning of those objects and the relationships. Pragmatics Intent of the semantics and actual semantic usage. There is very little pragmatics expressed or even expressible in programming or database languages, but will become important.
18. The need for Ontologies With increasing levels of data, the need to categorise it and develop a framework and understanding of it increases. Allows greater level of integration. Able to express the semantics of your data, document collections, and systems using the same semantic resource that is machine interpretable. Re-use previously developed versions, bring in different or related ontologies, and extend the ontology. This helps to establish community wide common semantics.
19. Closing Comments Ontologies are used to improve the structure and data used in a web page Categorise s and develops data into a structure that makes sense. Complicated but becoming essential to generate full use of data Needs to be machine interpretable. Machines cannot make assumptions like humans
21. References Deitel, P.J. Deitel, H.M. (2008). Internet &World Wide Web How to Program. 4th ed. New Jersey: Pearson Education Inc. 96. Daconta, M. Obrst, L. Smith, K (2003). The Semantic Web. A Guide to the eFuture of XML, Web services, and Knowledge Management. Indianapolis: Wiley Publishing Inc. 181-238