1. Semantic Web محمد احمدی نیا ahmadinia@gmail.com

2. 2 Of 73 Outline  Why Semantic Web?  What is Semantic Web?  Semantic Web Main Technologies  XML  RDF  RDFs  OWL

3. 3 Of 73 Mom Physician’s Agent Lucy’s Agent required treatment Schedule appointment Insurance Co. Provider sites Rating in-plan? close-by? Specialist? Pete’ Agent Driving schedule Semantic Web Scenario

4. 4 Of 73 The Vision  The World Wide Web (the syntactic web) is a big and impressive success story, both in terms of  the amount of available information and  the growth rate of human users  It has entered most areas of our daily life and business.

5. 5 Of 73 The Vision  This success is based on its simplicity  It’s easy to publish information on the web  It’s easy to access information (but if you know where they are)

6. 6 Of 73 Why Semantic Web?  Tasks often require to combine data on the Web:  hotel and travel information may come from different sites  searches in different digital libraries  Humans combine these information easily even if  different terminologies are used  the information is incomplete, or buried in images, videos, …  But Machines?

7. 7 Of 73 Impossible using the Syntactic Web…  Complex queries involving background knowledge  Find information about “animals that use sonar but are not either bats or dolphins”  Locating information in data repositories  Travel enquiries  Prices of goods and services  Results of human genome experiments  Finding and using “web services”  Delegating complex tasks to web “agents”  Book me a holiday next weekend somewhere warm, not too far away, and where they speak French or English

8. 8 Of 73 What is the Problem?

9. 9 Of 73 Challenge  Query  What is the name of a person who is a member of an organization in Iran, and likes a kind of sport?

10. 10 Of 73 Why Semantic Web?  (Some) data should be available for machines for further processing  Metadata: Data about data  Data should be possibly combined, merged on a Web scale  Machines may also need to reason about that data

11. 11 Of 73 What is Semantic Web?  Tim Berners-Lee:  “The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” 2001

12. 12 Of 73 Semantic Web  “The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users” 2001

13. 13 Of 73 Current Web

14. 14 Of 73 Current Web  Resources  identified by URI's  untyped  Links  href, src,...  limited, non-descriptive  User  Exciting world - semantics of the resource, however, gleaned from content  Machine:  Very little information available - significance of the links only evident from the context around the anchor.

15. 15 Of 73 Semantic Web

16. 16 Of 73 Semantic Web  Resources  Globally Identified by URI's  Extensible  Relational  Links  Identified by URI's  Extensible  Relational  User  Even more exciting world, richer user experience  Machine  More processable information is available (Data Web)  Computers and people  Work, learn and exchange knowledge effectively

17. 17 Of 73 Semantic Web Technologies  The Semantic Web extends the Web through the use of standards, markup languages and related processing tools

18. 18 Of 73 Semantic Web Architecture

19. 19 Of 73 A Simple Web Page  Markup consists of:  rendering information (e.g., font size and colour)  Hyper-links to related content  Semantic content is accessible to humans but not (easily) to computers…

20. 20 Of 73 Challenge  Query  What is the name of a person who is a member of an organization in Iran, and likes a kind of sport?

21. 21 Of 73 What information can we see… Hi! My name is Ali! This is my homepage. I am a student at Ferdowsi University of Mashhad. I like football.

22. 22 Of 73 The Page Source Code in HTML Ali's Homepage Hi! My name is Ali! This is my homepage. I am a student at Ferdowsi University of Mashhad. I like football. “http://um.ac.ir

23. 23 Of 73 What information can a machine see… ………………….. ……….................... …………………………………………..…… …………………...............................

24. XML

25. 25 Of 73 XML  eXtensible Markup Language  XML allows users to add arbitrary structure to their documents but says nothing about what the structures mean

26. 26 Of 73 Solution: XML “meaningful” tags …………………………. …………………. …………………….. …………… ………………………………………………………………… …………………….

27. 27 Of 73 27 HTML vs. XML  HTML is for humans  HTML describes web pages  Browsers ignore and/or correct as many HTML errors as they can, so HTML is often sloppy  XML is for computers  XML describes data  The rules are strict and errors are not allowed  In this way, XML is like a programming language  Current versions of most browsers can display XML  However, browser support of XML is spotty at best

28. 28 Of 73 28 XML Building blocks  The XML declaration looks like this:  Identify the nature of the content they surround  General format:  …  Empty element:  XML Elements have Relationships  Elements are related as parents and children David Matuszek

29. 29 Of 73 29 XML Applications  XML is used to Exchange Data  Reduce the complexity of interpreting data  XML can be used to Store Data  Accessible to more applications  XML can be used to Create new Languages, e.g. :  WML (Wireless Markup Language), MusicXML

30. 30 Of 73 30 XML Validation  "Well Formed" XML document  correct XML syntax  "Valid" XML document  “well formed”  Conforms to the rules of a DTD  XML DTD  defines the legal building blocks of an XML document  Can be inline in XML or as an external reference  XML Schema  an XML based alternative to DTD, more powerful  Support namespace and data types

31. 31 Of 73 31 An Example XML with DTD <!DOCTYPE note [ ]> Tove Jani Reminder Don't forget me this weekend

32. 32 Of 73 32 XML Schemas  “Schema” is a general term  DTDs are a form of XML schemas  When we say “XML Schemas,” we usually mean the W3C XML Schema Language  This is also known as “XML Schema Definition” language, or XSD.

33. 33 Of 73 But What if? …………………………. …………………. …………………….. …………………… ………………………………………………………………… …………….

34. RDF

35. 35 Of 73 RDF  Resource Description Framework  A data model oMeaning encoded in sets of ‘triples’: entities have properties which have values oEach triple: subject-predicate-object oEntities, properties and values all have distinct URIs

36. 36 Of 73 RDF Model  A model is a collection of statements  Statement := (predicate,subject,object)  Predicate is a resource  Subject is a resource  Object is either a resource or a literal SubjectObject Predicate Statement

37. 37 Of 73 RDF Ali Ferdowsi University of Mashhad studentOF http://um.ac.ir hasHomePage

38. 38 Of 73 RDF http://um.ac.ir

39. 39 Of 73 Example We are looking for a woman who works for one of my client and her son studies at University of Rovaniemi

40. 40 Of 73 40 XML vs. RDF  RDF is not just an XML dialect.  XML:  Has a tree structure data model.  Only nodes are labeled.  RDF:  Has a graph structure data model.  Both edges (properties) and nodes (subjects/objects) are labeled.

41. 41 Of 73 Challenge  Query  What is the name of a person who is a member of an organization in Iran, and likes a kind of sport?

42. 42 Of 73 But…  What is the relation between  a Student and a Person?  Football and Sport?  University and College?  University and Website?  Ontology is the solution

43. Ontology

44. 44 Of 73 Ontology  To answer the query it is required to tell the machine that  There is a class of objects named ‘Student’  There is a class of objects named ‘Person’  Each Student is a Person  Each Person has a Name  There is a class of objects named ‘Sport Type’  Football is a kind of Sport  There is an instance of a Student that its Name is “Ali”  ….

45. 45 Of 73 Ontology  Philosophy  The study of what is, what has to be true for something to exist, the kinds of things that can exist  AI and computer science  Co-opted the term. Something exists if it can be represented, described, defined (in a formal, hence, machine-interpretable way).

46. 46 Of 73 Ontology  Ontologies are about vocabularies and their meanings, with explicit, expressive, and well-defined semantics, possibly machine-interpretable.  “Ontology is a formal specification of a conceptualization.” Gruber, 1993  Main elements of an ontology:  Concepts  Relationships  Hierarchical  Logical  Properties  Instances (individuals)

47. 47 Of 73 Ontology

48. 48 Of 73 Ontologies in the Semantic Web  Provide shared data structures to exchange information between agents  Can be explicitly used as annotations in web sites  Can be used for knowledge-based services using other web resources

49. 49 Of 73 Ontology  Ontology Languages  RDFS (RDF Schema)  OWL  SHOE  DAML+OIL

50. 50 Of 73 RDF Schema (RDFS)  RDF gives a formalism for meta data annotation, and a way to write it down in XML, but it does not give any special meaning to vocabulary such as subClassOf  RDF Schema allows you to define vocabulary terms and the relations between those terms in special domain  it gives “extra meaning” to particular RDF predicates and resources  this “extra meaning”, or semantics, specifies how a term should be interpreted

51. 51 Of 73 Core Classes & Properties Core Classes Core Properties rdfs:Resource rdfs:Literal rdfs:Statement rdfs:Class rdfs:Property rdfs:Type rdfs:SubClassOf rdfs:SubPropertyOf rdfs:Domain rdfs:Range rdfs:Label rdfs:Comment

52. 52 Of 73 RDF &RDFS (a sample) زبانهای برنامه سازی وب

53. 53 Of 73 RDFS Sample Code <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"> The class of professor All professors are academic staff members. The class of academic staff members The class of staff members زبانهای برنامه سازی وب

54. 54 Of 73 RDFS Sample Code … The class of courses It relates only courses to lecturers. Inherits its domain ("course") and range ("lecturer") from its superproperty "involves" زبانهای برنامه سازی وب

55. 55 Of 73 Problems with RDFS  RDFS too weak to describe resources in sufficient detail  No localised range and domain constraints  Can’t say that the range of hasChild is person when applied to persons and elephant when applied to elephants  No existence/cardinality constraints  Can’t say that all instances of person have a mother that is also a person, or that persons have exactly 2 parents  No transitive, inverse or symmetrical properties  Can’t say that isPartOf is a transitive property, that hasPart is the inverse of isPartOf or that touches is symmetrical ……  Difficult to provide reasoning support  No “native” reasoners for non-standard semantics  May be possible to reason via FO axiomatisation

56. 56 Of 73 OWL (Ontology Web Language)  OWL is now a W3C Recommendation  The purpose of OWL is identical to RDFS i.e. to provide an XML vocabulary to define classes, properties and their relationships.  RDFS enables us to express very rudimentary relationships and has limited inferencing capability.  OWL enables us to express much richer relationships, thus yielding a much enhanced inferencing capability.  The benefit of OWL is that it facilitates a much greater degree of inference than you get with RDF Schema.

57. 57 Of 73 Origins of OWL RDF DAML+OIL DARPA Agent Markup Language A W3C Recommendation OIL OWL All influenced by RDF Ontology Inference Layer EU/NSF Joint Ad hoc Committee DAML OWL Lite OWL DL OWL Full

58. 58 Of 73 OWL  OWL and RDF Schema enable rich machine-processable semantics XML/DTD/XML Schemas RDF Schema OWL Semantics Syntax RDFS OWL

59. 59 Of 73 Full: Very expressive, no computation guarantees DL (Description Logic): Maximum expressiveness, computationally complete Lite: Simple classification hierarchy with simple constraints. Versions of OWL  Depending on the intended usage, OWL provides three increasingly expressive sublanguages OWL Full OWL DL OWL Lite

60. 60 Of 73 OWL Ontologies  What’s inside an OWL ontology  Classes + class-hierarchy  Properties (Slots) / values  Relations between classes (inheritance, disjoints, equivalents)  Restrictions on properties (type, cardinality)  Characteristics of properties (transitive, equivalence, symmetry …)  Annotations  Individuals  Reasoning tasks: classification, consistency checking

61. 61 Of 73 owl:Class  Top-most class: owl:Thing

62. 62 Of 73 Properties  What is a Property?  e.g., has_father, has_pet, service_number  a collection of relationships between individuals (and data)  a way of describing a kind of relationship between individuals  an object in the world (OWL Full)

63. 63 Of 73 OWL Properties Object Properties Ana  has_father  David Is range a literal / typed value ? then ERROR Data type Properties Ana  age  25  XML Schema data types supported  DB people happy

64. 64 Of 73 Defining Properties  ObjectProperty  DatatypeProperty  rdfs:subPropertyOf  rdfs:domain  rdfs:range 

65. 65 Of 73 Describing classes in OWL Complex Classes  Intersection of classes (owl:intersectionOf)  OR (A  B)  Union of classes (owl:unionOf)  AND (A  B)  Complement (owl:complementOf)  NOT  Enumeration (owl:oneOf)  Disjoint Classes (owl:disjointWith)

66. 66 Of 73 Describing classes in OWL Restrictions on Property Classes  Properties:  allValuesFrom: rdfs:Class (lite/DL owl:Class)  hasValue: specific Individual  someValuesFrom: rdfs:Class (lite/DL owl:Class)  minCardinality: xsd:nonNegativeInteger (in lite {0,1})  maxCardinality: xsd:nonNegativeInteger (in lite {0,1})

67. 67 Of 73 Describing properties in OWL OWL vs. RDFS  RDF Schema provides some of predefined properties:  rdfs:range used to indicate the range of values for a property.  rdfs:domain used to associate a property with a class.  rdfs:subPropertyOf used to specialize a property.  …  OWL provides additional predefined properties:  owl:cardinality (indicate cardinality)  owl:hasValue (at least one of the specified property values)  …  OWL provides additional property classes, which allow reasoning and inferencing:  owl:FunctionalProperty  owl:TransitiveProperty  …

68. 68 Of 73 OWL Cardinality  min Cardinality  max Cardinality  “Cardinality”  When min = max  has Value  belongs to the class if it has the value

69. 69 Of 73 An Example OWL ontology

70. 70 Of 73 Semantic Web: Now  Numerous web technologies, languages, formats, and standards which provide the inferastructure  URI, XML, XML Schema, RDF, RDFS, OWL, SPARQL, SerQL, HTTP, Microformats, RDFa,

71. 71 Of 73 Semantic Web: Now  A large body of research and activity is related to ontologies, since they play a main role  Ontology engineering issues and tools  ontology development, ontology selection, ontology matching, ontology evaluation, ontology partitioning,….  Numerous Ontologies are developed in different domains, e.g. FOAF, DOAP, SIOC, SKOS, …

72. 72 Of 73 Semantic Web: Now  Semantic Web technologies are used as an enabler in different areas to develop small semantic web applications  Ontology-based …..  Ontology-enabled …  Semantic-Web-Enabled …  Semantic ….

73. 73 Of 73 Semantic Web: Now  Semantic Web Search Engines  Swoogle, SWSE, Watson, Falcons, Yahoo! Microsearch, ….