1. 1 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 1 Conceptual Modelling: ER, UML and OWL - and the Semantic Web Bettina Berendt Katholieke Universiteit Leuven, Department of Computer Science http://www.cs.kuleuven.ac.be/~berendt/teaching/2009-10-1stsemester/adb/ Last update: 30 September 2009

2. 2 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 2 Motivation I: Wouldn‘t it be nice? The entertainment system was belting out the Beatles' "We Can Work It Out" when the phone rang. When Pete answered, his phone turned the sound down by sending a message to all the other local devices that had a volume control. His sister, Lucy, was on the line from the doctor's office: "Mom needs to see a specialist and then has to have a series of physical therapy sessions. Biweekly or something. I'm going to have my agent set up the appointments." Pete immediately agreed to share the chauffeuring. At the doctor's office, Lucy instructed her Semantic Web agent through her handheld Web browser. The agent promptly retrieved information about Mom's prescribed treatment from the doctor's agent, looked up several lists of providers, and checked for the ones in-plan for Mom's insurance within a 20-mile radius of her home and with a rating of excellent or very good on trusted rating services. It then began trying to find a match between available appointment times (supplied by the agents of individual providers through their Web sites) and Pete's and Lucy's busy schedules. (The emphasized keywords indicate terms whose semantics, or meaning, were defined for the agent through the Semantic Web.) Tim Berners-Lee, James Hendler and Ora Lassila (2001). The Semantic Web. A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American. http://www.sciam.com/article.cfm?id=the-semantic-web http://www.sciam.com/article.cfm?id=the-semantic-web

3. 3 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 3 Motivation II: Can I have a meaningful answer please?

4. 4 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 4 Here‘s the answer

5. 5 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 5 BTW, here‘s what Google says

6. 6 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 6 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL

7. 7 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 7 Data and information n Datum / Data l Fact or concept from reality, in a form suitable for communicating it, interpreting it, and processing it n Information l Interpreted data Example: The length of the road is 400 km InterpretationData (based on Henk Olivié: Gegevensbanken – 01. 2006/07)

8. 8 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 8 Data, information, and knowledge Data represents a fact or statement of event without relation to other things. n Ex: It is raining. Information embodies the understanding of a relationship of some sort, possibly cause and effect. n Ex: The temperature dropped 15 degrees and then it started raining. Knowledge represents a pattern that connects and generally provides a high level of predictability as to what is described or what will happen next. n Ex: If the humidity is very high and the temperature drops substantially the atmospheres is often unlikely to be able to hold the moisture so it rains. (This is from knowledge-management theory. If you want to know about wisdom, check the Web page: G. Bellinger, D. Castro, & A. Mills: Data, Information, Knowledge, and Wisdom. http://www.systems-thinking.org/dikw/dikw.htm ) http://www.systems-thinking.org/dikw/dikw.htm

9. 9 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 9 „Knowledge“ as used in this course Data represents a fact or statement of event without relation to other things. n Ex: It is raining. Information embodies the understanding of a relationship of some sort, possibly cause and effect. n Ex: The temperature dropped 15 degrees and then it started raining. Knowledge represents a pattern that connects and generally provides a high level of predictability as to what is described or what will happen next. n Ex: If the humidity is very high and the temperature drops substantially the atmospheres is often unlikely to be able to hold the moisture so it rains.  This definition of „knowledge“ corresponds to that used in  Data mining (aka „knowledge discovery (in databases)“)  (in particular symbolic) AI (e.g., „knowledge-based systems“)  It is not the only definition; e.g., cognitive psychology generally assumes that only people can have knowledge, such that computers can only possess (different types of) information.

10. 10 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 10 Computerizing data, information, and knowledge: Databases and knowledge bases n Databases l = data + interpretation (metadata)  focus on data and information = focus on the retrieval of data and information n Knowledge bases l a special kind of database l provide the means for the computerized collection, organization, and retrieval of knowledge  focus on knowledge = focus on the inferences that can be made from data+information

11. 11 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 11 Combining data and knowledge from different sources: The importance of conceptual models n To combine data from different databases: l know + integrate their conceptual models n To combine data from databases and knowledge bases: 1. understand the commonalities and differences of their conceptual meta-models Simplified: n database conceptual models = entities + relations n knowledge base conceptual models = entities + relations + rules for inferencing 2. integrate these conceptual models (as for databases)

12. 12 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 12 Conceptual modelling as a part of database design

13. 13 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 13 Conceptual database schemas and conceptual models in general n Conceptual schema: l a concise description of the data requirements of the users l includes detailed descriptions of the entity types, relationships, and constraints l does not include implementation details l can be used to communicate with non-technical users (Elmasri, R. & Navathe, S.B. (2007). Fundamentals of Database Systems. Boston: Addison Wesley. 5th Edition. p. 60) n Conceptual model l a theoretical construct that represents something, with a set of variables and a set of logical and quantitative relationships between them. l describes the semantics of the modelled domain l Models in this sense are constructed to enable reasoning within an idealized logical framework l Often in the form of an ontology, or having an ontology as a part –Ontology (a simple definition): ~ schema plus axioms for inference

14. 14 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 14 UML recap – class diagrams in a nutshell (what‘s missing?) (more details: see hyperlinked slideset)

15. 15 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 15 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL

16. 16 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 16 Recall: Wouldn‘t it be nice... (or: motivation I: personal agents) The entertainment system was belting out the Beatles' "We Can Work It Out" when the phone rang. When Pete answered, his phone turned the sound down by sending a message to all the other local devices that had a volume control. His sister, Lucy, was on the line from the doctor's office: "Mom needs to see a specialist and then has to have a series of physical therapy sessions. Biweekly or something. I'm going to have my agent set up the appointments." Pete immediately agreed to share the chauffeuring. At the doctor's office, Lucy instructed her Semantic Web agent through her handheld Web browser. The agent promptly retrieved information about Mom's prescribed treatment from the doctor's agent, looked up several lists of providers, and checked for the ones in-plan for Mom's insurance within a 20-mile radius of her home and with a rating of excellent or very good on trusted rating services. It then began trying to find a match between available appointment times (supplied by the agents of individual providers through their Web sites) and Pete's and Lucy's busy schedules. (The emphasized keywords indicate terms whose semantics, or meaning, were defined for the agent through the Semantic Web.) Tim Berners-Lee, James Hendler and Ora Lassila (2001). The Semantic Web. A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American. http://www.sciam.com/article.cfm?id=the-semantic-web http://www.sciam.com/article.cfm?id=the-semantic-web

17. 17 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 17 Problems with current search engines (or: motivation II) Current search engines = (mostly) keywords: n low precision (… and recall?) n sensitive to vocabulary n insensitive to implicit content

18. 18 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 18 Search engines on the Semantic Web - goals n concept search instead of keyword search n semantic narrowing/widening of queries n query-answering over >1 document n document transformation operators  Let‘s look at current solution approaches 

19. 19 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 19 Resolving content problems: Example homonymy A page about jaguars (Solution approach I) OR...

20. 20 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 20 Homonymy: Solution approach II

21. 21 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 21 Homonymy: Solution approach III

22. 22 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 22 Resolving quality problems How to find out whether a page is good, important, etc.? OR (PageRank)

23. 23 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 23 Reasoning over > 1 Web pages (1a)

24. 24 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 24 Reasoning over > 1 Web pages (1b)

25. 25 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 25 What are the conditions for this to return meaningful results?

26. 26 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 26 Reasoning over > 1 Web pages (2a)

27. 27 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 27 Reasoning over > 1 Web pages (2b)

28. 28 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 28 How does that work? n Wolfram Alpha is an online service that answers factual queries directly by computing the answer from structured data, rather than providing a list of documents or web pages that might contain the answer. n Users submit queries and computation requests via a text field. n Wolfram Alpha then computes and infers answers and relevant visualizations from a core knowledge base of curated, structured data.knowledge base curatedstructured data (http://en.wikipedia.org/wiki/Wolfram_alpha)http://en.wikipedia.org/wiki/Wolfram_alpha

29. 29 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 29 Document transformation operators?

30. 30 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 30 Semantic non-interoperability has real consequences...

31. 31 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 31 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL

32. 32 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 32 A motivating example: Bridging the Terminology Gap using OWL A key problem in achieving interoperability is to be able to recognize that two pieces of data are talking about the same thing, even though different terminology is being used. The following slides presents an example to show how OWL may be used to bridge the "terminology gap".

33. 33 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 33 Interested in Purchasing a Camera Scenario: n I am interested in purchasing a camera with a 75-300mm zoom lens size, that has an aperture of 4.5-5.6, and a shutter speed that ranges from 1/500 sec. to 1.0 sec. n I launch my personal "Web Bot" which crawls the Web looking for Web sites that can fulfill my request. n Assume that there exists an OWL Camera Ontology, which the Web Bot can "consult" upon its travels across the Web.

34. 34 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 34 Is this document relevant? <PhotographyStore rdf:ID="Hunts" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> Malden, MA 617-555-1234 <SLR rdf:ID="Olympus-OM-10" xmlns="http://www.camera.org#"> 75-300mm zoom 4.5-5.6 0.002 1.0 seconds 325 USD The Web Bot finds this document at a Web site: Is it relevant? (Note: SLR = Single Lens Reflex)

35. 35 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 35 A Match? Match? To determine if there is a match, these questions must be answered: 1. What's the relationship between "SLR" and "Camera"? 2. What's the relationship between "focal-length" and "size"? 3. What's the relationship between "f-stop" and "aperture"? <PhotographyStore rdf:ID="Hunts" xmlns:rdf="&rdf;#"> Malden, MA 617-555-1234 <SLR rdf:ID="Olympus-OM-10" xmlns="http://www.camera.org#"> 75-300mm zoom 4.5-5.6 0.002 1.0 seconds 325 USD I am interested in purchasing a camera with a 75-300mm zoom lens size, that has an aperture of 4.5-5.6, and a shutter speed that ranges from 1/500 sec. to 1.0 sec.

36. 36 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 36 Relationship between SLR and Camera? The Web Bot "consults" the OWL Camera Ontology. This OWL statement tells the Web Bot that a SLR is a type of Camera: <PhotographyStore rdf:ID="Hunts" … Hunts.xml Web Bot Camera.owl "Relationship between Camera and SLR?" "SLR is a type of Camera."

37. 37 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 37 Relationship between focal-length and lens size? This OWL statement tells the Web Bot that focal-length is equivalent to lens size: "focal-length is synonymous with (lens) size. focal-length is to be used within a Lens. focal-length has a value that is a string."

38. 38 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 38 Relationship between f-stop and aperture? This OWL statement tells the Web Bot that f-stop is equivalent to aperture: The Web Bot now recognizes that the XML document it found at the Web site - is talking about Cameras, and it - does show the lens size, and it - does show the aperture for the camera, and - the values for lens size, aperture, and shutter speed are met. Thus, the Web Bot recognizes that the XML document is a match!

39. 39 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 39 Semantic Definitions Separate from Application! <SLR rdf:ID="Olympus-OM-10" xmlns="http://www.camera.org#"> 75-300mm zoom 4.5-5.6 0.002 1.0 seconds 325 USD Hunts.xml Web Bot (application) "Relationship between Camera and SLR?" "SLR is a type of Camera." "Relationship between aperture and f-stop?" "f-stop is synonymous with aperture." "Relationship between size and focal-length?" "focal-length is synonymous with size." Camera.owl Semantic Definitions

40. 40 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 40 Summary: Interoperability despite terminology differences! The example demonstrated how a Web Bot application was able to dynamically process an XML document from a Web site, despite the fact that the XML document used terminology different than was used to express the request. This interoperability was achieved by using the OWL Camera Ontology! This example also demonstrated the architectural design principle of cleanly separating the application code (e.g., Web Bot) from the semantic definitions (e.g., Camera.owl).

41. 41 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 41 The Semantic Web: overview n The semantic web is an evolving extension of the World Wide Web in which web content can be expressed not only in natural language, but also in a format that can be read and used by software agents, thus permitting them to find, share and integrate information more easily.World Wide Web web contentnatural languagereadsoftware agentsintegrate n It derives from W3C director Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange.W3CSir Tim Berners-Leedatainformationknowledge n At its core, the semantic web comprises a philosophy, a set of design principles, collaborative working groups, and a variety of enabling technologies.working groups n Some elements of the semantic web are expressed as prospective future possibilities that have yet to be implemented or realized. n Other elements of the semantic web are expressed in formal specifications. n Some of these include Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain.Resource Description FrameworkRDF/XMLN3TurtleN-TriplesRDF SchemaWeb Ontology Languageformal descriptionconcepts termsrelationshipsknowledge domain

42. 42 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 42 The Semantic Web layer cake (T. Berners-Lee talk at XML 2000) RDF: W3C Rec. 2004 OWL: W3C Rec. 2004

43. 43 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 43 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL

44. 44 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 44 What is RDF ? RDF is a data model l the model is domain-neutral, application-neutral l the model can be viewed as directed, labeled graphs or as an object-oriented model (object/attribute/value) RDF data model is an abstract, conceptual layer independent of XML l consequently, XML is a transfer syntax for RDF, not a component of RDF l RDF data might never occur in XML form

45. 45 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 45 RDF model RDF “statements” consist of resources (= nodes) which have properties which have values (= nodes,strings) http://www.w3.org/TR/REC-rdf-syntax/ “Ora Lassila” author = subject = predicate = object “http://www.w3.org/TR/REC-rdf-syntax/ has the author Ora Lassila” resource value property

46. 46 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 46 RDF Model Example http://www.w3.org/TR/REC-rdf-syntax/ “Ora Lassila” dc:Creator “1999-02-22” dc:Date “W3C” dc:Publisher

47. 47 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 47 Complex values So far, values of properties have been strings A graph node (corresponding to a resource) also can be the value of a property n arbitrarily complex tree and graph structures are possible n syntactically, values can be embedded (i.e. lexically in-line) or referenced (linked) Example : http://www.w3.org/TR/REC-rdf-syntax/ “Ora Lassila” dc:Creator “ora.lassila@nokia.com” p:EMail p:Name

48. 48 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 48 Complex values (continued) Corresponding triples { “http://www.w3.org/TR/PR-rdf-syntax/”, dc:Creator, x } { x, p:Name, “Ora Lassila” } { x, p:EMail, “ora.lassila@nokia.com” } http://www.w3.org/TR/REC-rdf-syntax/ “Ora Lassila” dc:Creator “ora.lassila@nokia.com” p:EMail p:Name

49. 49 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 49 Containers Containers are collections n they allow grouping of resources (or literal values) It is possible to make statements about the container (as a whole) or about its members individually Different types of containers exist n bag - unordered collection n seq - ordered collection (= “sequence”) n alt - represents alternatives It is also possible to create collections based on URI patterns n for example, all files in a particular web site Duplicate values are permitted n there is no mechanism to enforce unique value constraints

50. 50 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 50 Containers (continued) http://www.w3.org/TR/REC-rdf-syntax “Ora Lassila” rdf:_1 rdf:Seq dc:Creator rdf:Type “Ralph Swick” rdf:_2

51. 51 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 51 Higher-order statements One can make RDF statements about other RDF statements n example: “Ralph believes that the web contains one billion documents” Higher-order statements n allow us to express beliefs (and other modalities) n are important for trust models, digital signatures,etc. n also: metadata about metadata n are represented by modeling RDF in RDF itself

52. 52 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 52 Reification n RDF is not really second-order n But it does provide a built-in predicate vocabulary for reification http://www.w3.org/TR/REC-rdf-syntax“Ora Lassila” dc:Creator “Library of Congress” dc:Creator The dotted box corresponds to the following statements { x, rdf:predicate, “dc:creator” } { x, rdf:subject, “http://www.w3.org/TR/RED-rdf-syntax } { x, rdf:object, “Ora Lassila” } { x, rdf:type, “rdf:statement” }

53. 53 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 53 Reification pers05 ISBN... Author-of NYT claims ISBN... Any statement can be an object graphs can be nested - reification

54. 54 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 54 RDF Schema Defines small vocabulary for RDF: Class, subClassOf, type Property, subPropertyOf domain, range Vocabulary can be used to define other vocabularies for your application domain Person StudentResearcher subClassOf Jeen type hasSuperVisor domain range Frank type hasSuperVisor

55. 55 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 55 RDF Schema syntax in XML

56. 56 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 56 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL

57. 57 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 57 What is an ontology? (A commonly accepted informal definition and one formal definition) An ontology is „an explicit specification of a shared conceptualisation.“ (Gruber, 1993)

58. 58 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 58 Ontologies, decentralization, and bottom-up engineering Communities of users (application builders,...) can n Re-use existing ontologies l Established domain-specific ontologies (e.g., real-estate, medicine, bioinformatics) l All kinds: see the Semantic Web search engine http://swoogle.umbc.edu/ http://swoogle.umbc.edu/ l „The big one“: Cyc, see www.cyc.comwww.cyc.com n Link to existing ontologies (  Ontology matching / alignment) n Extend existing ontologies

59. 59 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 59 Ontologies as conceptual models / schemas; or: Database (knowledge base) = Ontology + Instances My Life and Times Illusions First and Last Freedom Paul McCartney Richard Bach J. Krishnamurti June, 1998 1972 1974 title author date BookCatalogue My Life and Times Paul McCartney June, 1998

60. 60 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 60 OWL vs. Database Advantages of using OWL to define an Ontology: n Extensible: much easier to add new properties. Contrast with a database - adding a new column may break a lot of applications n Portable: much easier to move an OWL document than to move a database. Advantages of using a Database to define an Ontology: n Mature: the database technology has been around a long time and is very mature.

61. 61 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 61 (insert the OWL tutorial slides by Costello and Jacobs here, „OWL.ppt“ as hyperlinked on the course page)

62. 62 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 62 Agenda Basics: Modelling – from data to knowledge Challenges in decentralised environments (e.g., Web) The vision of the Semantic Web Semantic Web layer “RDF/RDFS” Semantic Web layer “ontologies”: OWL “Semantic Web 2”: Linked Data

63. 63 Berendt: Advanced databases, first semester 2009, http://www.cs.kuleuven.ac.be/~berendt/teaching 63 References / background reading; acknowledgements See the long versions of this slide set