1. Lecture 7: Semantic Web and Ontologies in Enterprises Dr. Taysir Hassan A. Soliman December 7, 2015 INF411 Information Engineering Information Systems Dept. Faculty of Computers & Information

2. Agenda Semantic Web Ontologies

3. Ontology

4. 4 Semantic Technology Semantic technology as a software technology allows the meaning of information to be known and processed at execution time. For a semantic technology there must be a knowledge model of some part of the world that is used by one or more applications at execution time.

5. (In)famous “Layer Cake”  Data Exchange  Semantics+reasoning  Relational Data ? ? ??? Relationship between layers is not clear OWL DL extends “DL subset” of RDF

6. 6 Semantic Web Content: New “Users” applications agents

7. 7 Semantic Web: Resource Integration Shared ontology Web resources / services / DBs / etc. Semantic annotation

8. 8 Web resources / services / DBs / etc. Shared ontology Web users (profiles, preferences) Web access devices Web agents / applications External world resources Smart machines and devices Industrial and business processes Semantic Web: which resources to annotate ? Multimedia resources

9. URI, HTML, HTTP Static WWW Serious Problems in information finding extracting representing interpreting and maintaining RDF, RDF(S), OWL Semantic Web

10. Semantic Web Technology Tim Berners-Lee has a vision of a Semantic Web which – has machine-understandable semantics of information, and – millions of small specialized reasoning services that provide support in automated task achievement based on the accessible information

11. The Semantic Web The semantic Web is essentially based on ontologies formal consensual – ontologies are formal and consensual specifications of conceptualizations… shared and common – providing a shared and common understanding of a domain that can be communicated across people and application systems

12. Semantic Web Technology Ontologies glue together two essential aspects that help to bring the web to its full potential: – ontology define a formal semantics for information allowing information processing by a computer – ontologies define a real-world semantics allowing to link machine processable content with meaning for humans based on consensual terminology

14. Ontology... Long history coming from Philosophy - Aristoteles – “The metaphysical study of the nature of being and existence” Pick up by the Artificial Intelligence – “ a shared and common understanding of some domain that can be communicated between people and application systems ” - Gruber

15. Introduction There is a discipline Ontology, which is the philosophical study of ‘being’. There are specific ontologies used in knowledge management (KM), knowledge representation and computer science that describe a system of objects or concepts in some domain. An ontology is a specification of a conceptualisation.

16. 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 Global vs. Domain‐specific

17. Ontology Definition 1.A collection of classes that represent related concepts. Ontology is organized using a hierarchy and a set of relationships between its classes. 2.Method of formally representing knowledge as a set of concepts within a domain, and the relationships which hold between them. 3.High-level knowledge and data representation structure. Ontologies provide a formal frame to represent the knowledge related with a complex domain, as a qualitative model of the system.

18. Ontology Definition (Cont…) 4. Set of classes, relations, functions, etc. that represents knowledge of a particular domain 5. A data model that represents the entities that are defined and evaluated by its own attributes, and organized according to a hierarchy and a semantic. 6. A set of concepts such as things, events, and relations, which are specified in a representative way in order to create an agreed-upon vocabulary for exchanging information.

19. Ontologies in KM are used to define properties of and relationships between the concepts. Ontologies are used by people (e.g. by experts) and by computers (e.g. in semantic web applications). Remember that an ontology is an engineering artifact that has to have a machine processable format that faithfully adheres to the logic.

20. Ontology Dimension Map

21. Why using ontologies? 1.To share common understanding of the structure of information among people or software agents 2.To enable reuse of domain knowledge 3.To make domain assumptions explicit 4. To separate domain knowledge from the operational knowledge 5.To analyze domain knowledge

22. 1. Sharing common understanding of the structure of information among people or software agents suppose several different Web sites contain medical information or provide medical e- commerce services. If these Web sites share and publish the same underlying ontology of the terms they all use, then computer agents can extract and aggregate information from these different sites.

23. 2. To enable reuse of domain knowledge was one of the driving forces behind recent surge in ontology research. For example, models for many different domains need to represent the notion of time. This representation includes the notions of time intervals, points in time, relative measures of time, and so on.

24. 3. To make domain assumptions explicit Hard-coding assumptions about the world in programming-language code makes these assumptions not only hard to find and understand but also hard to change, in particular for someone without programming expertise.

25. 4. To separate domain knowledge from the operational knowledge We can describe a task of configuring a product from its components according to a required specification and implement a program that does this configuration independent of the products and components themselves

26. 5. To analyze domain knowledge Is possible once a declarative specification of the terms is available. Formal analysis of terms is extremely valuable when both attempting to reuse existing ontologies and extending them

27. Why using ontologies? Ontologies for information systems were first proposed to contribute to solving the issues with data integration: an ontology provides the common vocabulary for the applications that is at one level of abstraction higher up than conceptual data models.

30. Ontology of measurements http://qudt.org/ Quantities, Units, Dimensions and Data Types Ontologies A Quantity Kind is any observable property that can be measured and quantified numerically. Familiar examples include physical properties such as length, mass, time, force, energy, power, electric charge, etc.

31. Kinds of ontologies Knowledge Representation ontologies – capture the representation primitives used to formalize knowledge in KR paradigm – such as: Frame-Ontology General/Common ontologies – vocabulary related to things, events, time, space, etc. – such as: meter and inch exchange table Meta-ontologies – reusable across domains – such as: mereology ontology (Borst, 97)

32. Kinds of ontologies Domain ontologies – vocabularies about the concepts in a domain – such as: the theory or elementary principles governing the domain Task ontologies – a systematic vocabulary of the terms used to solve problems associated with tasks that may or may not from the same domain – such as: scheduling task ontology Domain-task ontology – task ontology reusable in a given domain – such as: scheduling task ontology for flight schedule Application ontology – necessary knowledge for modeling a particular domain – such as: ????

33. Ontology Applications Knowledge Management Enterprise Application Integration e-Commerce

34. Example of ontology development of a PC: Class Designing Initial Design - One and Only one Hierarchy….Is it good…?…..NO Refinement….Ended in TWO main Hierarchies - Computer component and Computer…with 290 classes… Many Small Hierarchies to support the main hierarchies …But Why?… Types can not be designed using the existing editors Reference: users.encs.concordia.ca/~mah_rahm/ontology.ppt

35. Class Hierarchy … Top Down Design (1/2)

37. Enterprise Architecture & Semantic Models

38. Main components of an Ontology Five kinds of components: – classes: concepts of the domain or tasks, which are usually organized in taxonomies in univ-ontology: student and professor are two classes – relations: a type of interaction between concepts of the domain such as: subclass-of, is-a, component-of, substitute-of

39. Main components of an Ontology (Cont.) Five kinds of components: – Attributes: – axioms model sentences that are always true such as: if the student attends both A and B course, then he or she must be a second year student – instances to represent specific elements such as: Student called Peter is the instance of Student class

40. Instances * Instances are specific instances of the concepts or objects. Example 1 (Instances). – In the Movie ontology, individuals can be a specific film (Sherlock Holmes: A Game of Shadows), a specific director (Guy Ritchie), a specific actor (Robert Downey). The film genre (Action) is not an individual. Individuals represent the ground or atomic level of the ontology. An ontology may have no individuals, only classes.

41. Classes Classes, types or categories are sets of individuals. Example (Classes). In the Movie ontology, movie genre (e.g. Comedy, Drama), types of person (Actor, Director) are classes. All ontologies have at least two classes: – Thing representing the class of all concepts (i.e. the universe or domain). – Nothing representing the empty set (a subset of any set).

42. Attributes Concepts can be described by the set of common attributes, such as parts of an object. Example 3 (Attributes): A movie can be described by the set of ‘parts’ it has, such as Script, Director, Actors, Music. Attributes can be other concepts in their own right (i.e. individuals or classes), but they define the context for other concepts.

43. Relations Relations define how pairs of concepts can be related. Example 4 (Relations): Subclasses are related to their superclasses by relation SubclassOf or IS-A. – The fact that a movie has a director or an actor can be expressed by relation HAS or HAS-PART.

44. Examples of Domain Ontologies CContology : Customer Complaint Ontology http://www.jarrar.info/CContology/ Movie Ontology : http://www.movieontology.org/ Music Ontology : http://musicontology.com/ Disease Ontology : http://diseaseontology.sourceforge.net/ Gene Ontology : http://www.geneontology.org/ Plant Ontology : http://www.plantontology.org/

45. Another Example

54. Example: Pizza

55. Ontology for CRM