1. The Semantic Web Riccardo Rosati Dottorato in Ingegneria Informatica Sapienza Università di Roma a.a. 2006/07

2. The Semantic Web - course overview2 Overview the aim of this course is to provide an introduction to the Semantic Web...... with emphasis on two aspects: emphasis on AI-related aspects, in particular knowledge representation and reasoning emphasis on database-related aspects, in particular data integration

3. The Semantic Web - course overview3 Overview Lecture 1: Introduction to the Semantic Web Lecture 2: The XML layer Lecture 3: The RDF layer Lecture 4: The Ontology layer 1 –Description Logics, OWL Lecture 5: The Ontology layer 2 –reasoning in OWL, OWL species

4. Overview Lecture 6: The Ontology layer 3 –OWL technologies: OWL Tools, QuOnto Lecture 7: The rule layer Lecture 8: The RDF layer 2 – RDF semantics Lecture 9: The Ontology layer 4 –query answering in OWL Lecture 10: Handling inconsistency (Jan Chomicki)

5. Lecture 1 Introduction to the Semantic Web

6. 6 What is the Semantic Web? “The Semantic Web is a Web of actionable information—information derived from data through a semantic theory for interpreting the symbols.” “The semantic theory provides an account of ‘meaning’ in which the logical connection of terms establishes interoperability between systems” (Shadbot, Hall, Berners-Lee, The Semantic Web revisited, IEEE Intelligent Systems, May 2006)

7. Introduction to the Semantic Web7 The Semantic Web: why? search on the Web: problems......due to the way in which information is stored on the Web Problem 1: web documents do not distinguish between information content and presentation (“solved” by XML) Problem 2: different web documents may represent in different ways semantically related pieces of information this leads to hard problems for “intelligent” information search on the Web

8. Introduction to the Semantic Web8 Separating content and presentation Problem 1: web documents do not distinguish between information content and presentation problem due to the HTML language problem “solved” by current technology –stylesheets (HTML, XML) –XML stylesheets allow for separating formatting attributes from the information presented

9. Introduction to the Semantic Web9 Separating content and presentation XML: eXtensible Mark-up Language XML documents are written through a user- defined set of tags tags are used to express the “semantics” of the various pieces of information

10. Introduction to the Semantic Web10 XML: example HTML: Seminari di Ingegneria del Software Teacher: Giuseppe De Giacomo Room: 7 Prerequisites: none XML: Seminari di Ingegneria del Software Giuseppe De Giacomo 1AI, 1I none

11. Introduction to the Semantic Web11 Limitations of XML XML does not solve all the problems: legacy HTML documents different XML documents may express information with the same meaning using different tags

12. Introduction to the Semantic Web12 The need for a “Semantic” Web Problem 2: different web documents may represent in different ways semantically related pieces of information different XML documents do not share the “semantics” of information idea: annotate (mark-up) pieces of information to express the “meaning” of such a piece of information the meaning of such tags is shared!  shared semantics

13. Introduction to the Semantic Web13 The Semantic Web initiative viewpoint: the Web = a web of data goal: to provide a common framework to share data on the Web across application boundaries main ideas: ontology standards “layers”

14. Introduction to the Semantic Web14 The Semantic Web Tower

15. Introduction to the Semantic Web15 The Semantic Web Layers XML layer RDF + RDFS layer Ontology layer Proof-rule layer Trust layer

16. Introduction to the Semantic Web16 The XML layer XML (eXtensible Markup Language) –user-definable and domain-specific markup URI (Uniform Resource Identifier) –universal naming for Web resources –same URI = same resource –URIs are the “ground terms” of the SW W3C standards

17. Introduction to the Semantic Web17 The RDF + RDFS layer RDF = a simple conceptual data model W3C standard (1999) RDF model = set of RDF triples triple = expression (statement) (subject, predicate, object) subject = resource predicate = property (of the resource) object = value (of the property) => an RDF model is a graph

18. Introduction to the Semantic Web18 The RDF + RDFS layer Example of RDF graph: http://www.w3.org/TR/REC-rdf-syntax/ “Ora Lassila” dc:Creator “1999-02-22” dc:Date “W3C” dc:Publisher

19. Introduction to the Semantic Web19 The RDF + RDFS layer RDFS = RDF Schema “vocabulary” for RDF W3C standard (2004) example: Person StudentResearcher subClassOf Jeen type hasSuperVisor domain range Frank type hasSuperVisor RDFS RDF

20. Introduction to the Semantic Web20 The Ontology layer ontology = shared conceptualization  conceptual model (more expressive than RDF + RDFS)  expressed in a true knowledge representation language OWL (Web Ontology Language) = standard language for ontologies

21. Introduction to the Semantic Web21 The proof/rule layer beyond OWL: proof/rule layer rule: informal notion rules are used to perform inference over ontologies rules as a tool for capturing further knowledge (not expressible in OWL ontologies)

22. Introduction to the Semantic Web22 The Trust layer SW top layer: support for provenance/trust provenance: –where does the information come from? –how this information has been obtained? –can I trust this information? largely unexplored issue no standardization effort

23. Introduction to the Semantic Web23 The Semantic Web: main ingredients underlying web layer (URI, XML) –reusing and extending web technologies basic conceptual modeling language (RDF) ontology language (OWL) rules/proof reusing and extending AI technologies –knowledge representation –automated reasoning...and database technologies –data integration

24. Introduction to the Semantic Web24 The Semantic Web from an AI perspective the notion of ontology the role of logic and Description Logics the role of rule-based formalisms... (agent technology)

25. Introduction to the Semantic Web25 The notion of ontology ontology = shared conceptualization of a domain of interest shared vocabulary => simple (shallow) ontology (complex) relationships between “terms” => deep ontology AI view: –ontology = logical theory (knowledge base) DB view: –ontology = conceptual model

26. Introduction to the Semantic Web26 Ontologies: example class-def animal% animals are a class class-def plant% plants are a class subclass-of NOT animal% that is disjoint from animals class-def tree subclass-of plant% trees are a type of plants class-def branch slot-constraint is-part-of% branches are parts of some tree has-value tree max-cardinality 1 class-def defined carnivore% carnivores are animals subclass-of animal slot-constraint eats% that eat any other animals value-type animal class-def defined herbivore% herbivores are animals subclass-of animal, NOT carnivore % that are not carnivores, and slot-constraint eats % they eat plants or parts of plants value-type plant OR (slot-constraint is-part-of has-value plant)

27. Introduction to the Semantic Web27 Ontologies: the role of logic ontology = logical theory why? –declarative –formal semantics –reasoning (sound and complete inference techniques) well-established correspondence between conceptual modeling formalisms and logic

28. Introduction to the Semantic Web28 Ontologies and Description Logics OWL is based on a fragment of first-order predicate logic (FOL) Description Logics (DLs) = subclasses of FOL –only unary and binary predicates –function-free –quantification allowed only in restricted form –(variable-free syntax) –decidable reasoning DLs are one of the most prominent languages for Knowledge Representation

29. Introduction to the Semantic Web29 Ontologies and Description Logics expressive abilities of DLs have been widely explored reasoning in DLs has been extensively studied DL reasoners have been developed and optimized  DLs as a central technology for the SW

30. Introduction to the Semantic Web30 Rule-based formalisms Prolog Logic programming Constraint (logic) programming Production rules Datalog... Rule language for SW not standardized yet RIF (Rule Interchange Format) W3C working group

31. Introduction to the Semantic Web31 The SW from a database perspective ontology as a virtual database schema ontology-based information access the Semantic Web as a framework for data integration

32. Introduction to the Semantic Web32 Virtual data integration abstract model of a virtual data integration system: triple (G,S,M) G = global information schema S = set of data sources M = mapping between sources and global schema 1.the data sources are autonomous and heterogeneous information systems 2.the global schema is a virtual conceptualization of the domain of interest 3.the mapping is a declarative specification of the relationship between sources and global schema

33. Introduction to the Semantic Web33 Ontology-based information access ontology = virtual global information schema ontology language = conceptual modeling language the Web = distributed, heterogeneous, autonomous set of data sources but : data integration considers different formalisms for expressing schema and data the architecture of a data integration system is centralized

34. Introduction to the Semantic Web34 Ontology-based information access the data integration approach can be generalized to non-centralized architectures => peer data management systems despite the differences in the formalisms adopted, there is a tight relationship between the SW and data integration => dealing with incomplete information

35. Introduction to the Semantic Web35 The Semantic Web and data integration similarity between data integration and the SW: global schema = ontology sources = web sites (data) mapping = ?? however: different languages different technologies => the SW is essentially a data integration technology

36. Introduction to the Semantic Web36 Very quick overview of SW technologies main current technologies and standards for the SW: RDF RDFS OWL

37. Introduction to the Semantic Web37 RDF RDF = Resource Description Framework RDF data model is an abstract, conceptual layer (independent of XML) RDF data model = set of RDF triples triple = (subject, predicate, object) –subject = resource –predicate = property (of the resource) –object = value (of the property) standardized in 1999

38. Introduction to the Semantic Web38 RDFS RDFS = RDF Schema set of predefined predicates: –subClassOf –subPropertyOf –domain –range –......with predefined semantics! standardized in 2004

39. Introduction to the Semantic Web39 OWL OWL = Web Ontology Language the OWL family is constituted by 3 different languages (with different expressive power): –OWL Full –OWL-DL –OWL-Lite technology at an early stage –standardized in 2004 –reasoning techniques and tools are very recent –“optimization” of reasoning is largely unexplored

40. Introduction to the Semantic Web40 OWL vs. RDFS class-def subclass-of property-def subproperty-of domain range class-def subclass-of property-def subproperty-of domain range class-expressions AND, OR, NOT role-constraints has-value, value-type cardinality role-properties trans, symm... class-expressions AND, OR, NOT role-constraints has-value, value-type cardinality role-properties trans, symm... RDF(S) OWL

41. Introduction to the Semantic Web41 From RDFS to OWL Full with respect to the relative expressive power: OWL Full > OWL-DL > OWL-Lite > RDFS