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The Semantic Web

The Semantic Web. A Brief Introduction Dr. Randy M. Kaplan. A Quote.

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The Semantic Web

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  1. The Semantic Web A Brief Introduction Dr. Randy M. Kaplan

  2. A Quote • I have always imagined the information space as something to which everyone has immediate and intuitive access, not just to browse but to create ... Machines become capable of analyzing all the data on the web - the content, and links, and transaction between people and computers. 2

  3. A Quote (continued) • ... When the Semantic web does emerge the day-to-day mechanisms of trade, bureaucracy, and our daily lives will be handled by machines talking to machines, leaving people to provide the inspiration and intuition. • Tim Berners-Lee, 2000 3

  4. What is the Semantic Web • Semantic = meaning • Semantic Web = meaningful web? • The term semantic web is a vision • Computers - Software - People • Find, read, and understand data over the WWW to accomplish useful goals for users 4

  5. Semantic Web • Make data anywhere on the web accessible and understandable to people and machines • Informally defined • Fluid • Evolving • Not a working system 5

  6. Semantic web • Ideas • Machine-readable-data-view • Data on the web is used by machine • Used for automation, integration, and reuse (W3C 2003) 6

  7. Semantic web • Ideas • Intelligent Agents • Allow intelligent agents to retrieve and manipulate pertinent information 7

  8. Semantic web • Ideas • Distributed Database View • The Semantic Web does for data what HTML did for textual information systems 8

  9. Semantic web • Ideas • Distributed Database View • Represent all databases • Represent logic rules to link databases together to add value 9

  10. Semantic web • Ideas • Distributed Database View • Transform the web from a large interlinked book to large interlinked database 10

  11. Semantic web • Ideas • Automated Infrastructure • Berners-Lee argues that the Semantic web is infrastructure and not software 11

  12. Semantic web • Ideas • Servant of Humanity • Allow software relieve us of much of the burden of finding, extracting, integrating, and indexing information on the web 12

  13. Semantic web • Ideas • Better Annotation • Web as we know it augmented with annotations that are machine-readable and linked 13

  14. Semantic web • Ideas • Improved Searching • Possible to access web resources by content rather than keywords 14

  15. Semantic web • Ideas • Web Services • Semantic Web will be called upon to provide services that in turn provide useful behavior • Agents automate procedures that are currently performed manually 15

  16. Semantic web • Recurring Themes • Indexing and retrieving • Meta data • Annotation • Web as Database • Machine retrieval of data 16

  17. Semantic web • Recurring Themes • Web-based services • Discovery of services • Agents 17

  18. Semantic Web • Videos • http://www.youtube.com/watch?v=mVFY52CH6Bc • http://www.youtube.com/watch?v=OGg8A2zfWKg 18

  19. Semantic web • Scenario • During her stay in Honolulu Clara runs into several interesting people and they trade vCards. In the evening Clara reviews the days activities on her digital assistant. The assistant pops up a note with a link to one of the vCards that reads, “This guy’s profile seems to match the position advertisement that Bill put on our intranet. Can I notify Bill’s assistant?” • Clara asked her digital assistant to explain. “I used his company directory for finding his DAML enhanced vita: he’s got the required skills as a statistician who led the data mining group of the database department at Montana U for the requirement of a researcher who worked in machine learning.” Clara asked the assistant to provide evidence. “I checked his affiliation with the university of Montana, he is cited several times in their web pages: reasonably trusted; I checked his publication records from publishers DAML sources and asked bill assistant a rating of the journals: highly trusted. More details?” • Clara asked the assistant to inform Bill’s assistant 19

  20. Semantic web • Questions about the scenario - • What sorts of information must the agent have access to in order to perform these tasks? • What sorts of processing must the agent do in order to perform these tasks? 20

  21. Semantic web • Foundations • Resources • Standardized Addressing • Small set of commands • Scalability and large networks 21

  22. Semantic web • Foundations • Openness, completeness, and consistency • Web and Semantic Web 22

  23. Semantic web • Resources • A resource is intended to represent any idea that can be referred to • We think of these as tangible packages of data • The notion of resource is more general 23

  24. Semantic web • Resources • Generality of Resources • A resource can change over time and still be the same resource • A resource can also be a reference to a real or fictitious person 24

  25. Semantic web Trust Logic & Proof Ontology RDF Schema RDF XML Schema XML 25

  26. Semantic Web Trust Logic & Proof Ontology RDF Schema RDF XML used to define new languages that are used to interchange data on the web XML Schema XML 26

  27. Semantic Web Trust Logic & Proof Ontology RDF Schema A schema defines a language and is used to make sure statements in the language are written correctly RDF XML Schema XML 27

  28. Semantic Web RDF = resource description framework Trust Logic & Proof Ontology RDF Schema RDF A language that is capable of describing all sorts of information and meta-data XML Schema XML 28

  29. Semantic Web Trust When designing specific RDF-based application languages defines specific elements of the special language Logic & Proof Ontology RDF Schema RDF XML Schema XML 29

  30. Semantic Web An ontology defines the vocabulary and usage of words in the context of the specific vocabulary Trust Logic & Proof Ontology RDF Schema RDF XML Schema XML 30

  31. Semantic Web Logical reasoning is used to establish the consistency and correctness of datasets Trust Logic & Proof Ontology RDF Schema RDF XML Schema Logical reasoning is also necessary to infer conclusions which are not necessarily XML 31

  32. Provide authentication of identity Trust Logic & Proof Ontology RDF Schema RDF Create evidence that data, service, and agents are trustworthy XML Schema XML 32

  33. RDF • W3C’s candidate language to provide a standard way to model, describe, and exchange information about resources 33

  34. RDF • Three capabilities • Describe most kinds of data that will be available • Describe the structural design of data sets • Describe relationships between bits of data 34

  35. RDF • Uses a simple data model • Three things • Resources • Statements • Simple sentences in SVO order 35

  36. RDF • Example • “Billy lives in Chicago.” • Billy = subject • Lives = verb • Chicago = object 36

  37. Statements in RDF • Statement is sometimes called a triple (because it has three parts) • Subject is called the subject • Verb is called the predicate (alt. Property) • Object is called the object (alt. Value) 37

  38. Statements in RDF Subject Predicate Object (person-1, name, “William Sparks”) Triple 38

  39. Statements in RDF • A value in a statement can be - • A number • A string • Such a value is called a LITERAL • A value in a statement may also be another resource 39

  40. Identifying Resources in RDF • RDF needs a standard widely used way to identify resources • RDF uses the URI (Uniform Resource Identifier) • URIs can be used to identify a concept, tangible thing, chunk of data 40

  41. Identifying Resources in RDF • Identifying things is complicated • May never be a general solution • Names are not unique (many Robert Smith in the U.S.) • Same name - not the same person 41

  42. Identifying Resources in RDF • To identify a resource - • A URI is paired with or associated with a resource and not any other resource • How this is accomplished in NOT specifed • May not be a good way to identify a resource 42

  43. Identifying Resources in RDF • Alternative - • Identify a resource as the same as some other resource • The other resource is well-known • Use the right predicate (from a trusted source) 43

  44. Identifying Resources in RDF • Alternative • Identify a resource by its properties and relationships with other resources 44

  45. Identifying Resources in RDF • Example using properties • 2003 New York Yankees had one general manager • If it were known that a person had been the general manager of the Yankees during that time, the individual would be uniquely identified 45

  46. Identifying Resources in RDF • Suppose the pairing of a URI with a resource is described in a document • Question: How can this document be found? • RDF provides no standard method for answering this question 46

  47. Identifying Resources in RDF • To deal with the problem of locating the document, an informal approach is sometimes adopted • Use a URL to retrieve the document • One must remember that the document may not be the actual resource 47

  48. Identifying Resources in RDF • Example • The type of resource that is an RDF statement is identified by its URI: • http://www.w3.org/1999/02/22-rdf-syntax-ns#Statement 48

  49. Identifying Resources in RDF • At this URI there is a document • The document contains the following RDF fragment among others 49

  50. Identifying Resources in RDF • <!-- • This is the RDF schema for the RDF data model as described in • The Resource Description Framework (RDF) Model and Syntax • Specifications http://www.w3c.org/TR/REC-rdf-syntax --> • <s:Class rdf:ID=”Statement” • S:comment=”A triple consisting of a predicate, a subject, • And an object.” /> • <s:Class rdf:ID=”Property” • A:comment=”A name of a property, defining specific meaning • For the property” /> 50

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