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The Semantic Web Week 12 Term 1 Recap

The Semantic Web Week 12 Term 1 Recap. Lee McCluskey, room 2/07 Email lee@hud.ac.uk Department of Computing And Mathematical Sciences Module Website: http://scom.hud.ac.uk/scomtlm/chs2533. SW - Fundamental Idea - 1.

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The Semantic Web Week 12 Term 1 Recap

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  1. The Semantic WebWeek 12Term 1 Recap Lee McCluskey, room 2/07 Email lee@hud.ac.uk Department of Computing And Mathematical Sciences Module Website: http://scom.hud.ac.uk/scomtlm/chs2533

  2. SW - Fundamental Idea - 1 • When implementing a typical software application most of the “semantics” of the data we use in bound up with the procedures we write to manipulate that data. • So ‘data files’ only make sense to the methods we write to manipulate them • Relational data bases are a bit better and open to multi-use – but even here the programmer embeds what the relations ‘mean’ in the application code. • Current data on the internet is largely unstructured and not amenable to processing. The data is by definition very rich and inherently structured.

  3. SW - Fundamental Idea - 2 • A requirement of the semantic web is to have all public (www) ‘data’ encoded in a way that ANY application program can use it – even programs that have no encoding to anticipate the meaning of the data. • A second (dual) requirement of the semantic web is to have all public (www) processes or services encoded in a way that ANY application program can use then - even programs that have no encoding to anticipate the meaning of them. • The meaning of the data / processes will therefore have to be encoded • .. To be program-independent (declarative) • .. To be accessible to the client program • So all programs using the SW will have to ‘understand’ HOW to extract the meaning of data / services ie understand the data or services’s meta-languages. This meta-language will have to be Universal.

  4. SW - Fundamental Idea - 3 • ‘SOLUTION’: • Convention for syntax of meta-data => tags/attributes via XML • Convention for data language defn (what tagged data in what order) => XML Schema / DTDs • Convention for relating data items => URI, RDF • Convention for standardising names (tags) => vocabularies, ontologies • Convention for giving meaning to vocabularies => using (description) logics, OWL, DAML, KIF

  5. Related Modules + Subject Area Client- Server and Dist Systems OO Modelling Artificial Intelligence Shared services UML OO Classes Logic and reasoning Advance Databases SEMANTIC WEB Conceptual Schema and Description logics Semantic notations Ontologies Advanced Information Systems Language Specification And Implementation

  6. recap WEEK 1 lecture: Introduction to the Module WEEK 2 lecture: Introduction to the Semantic Web WEEK 3 lecture: XML / XML Schema WEEK 4 lecture: RDF and RDFS WEEK 5 lecture: RDFS / Introduction to Ontologies WEEK 6 lecture: Capturing Conceptual Knowledge with Logic WEEK 7 lecture: FOL WEEK 8 lecture: Reasoning with FOL WEEK 9 lecture: Reasoning with FOL WEEK 10 lecture: Description logics: Introduction WEEK 11 lecture: Description logics, OWL WEEK 12 lecture: Recap

  7. Recap – XML / XMLS • XML is a convention for packaging up data with its meta-data. Data is stored within tags and with a pointer to its data language parser via DTDs. • Idea of URI – unique identifier for all ‘resources’. Namespaces are a shorthand for giving and using URIs to things. Without them all the terms we use in an internet document would have to use the full URI ! • XML schema documents are used to VALIDATE XML documents. • XMLS is a more expressive, ambitious form of documenting the syntax of your XML data than using DTDs. Further, an XML Schema is an XML document itself.

  8. Recap – RDF / RDFS • Introduce a convention that we will (at the basic level) describe data as ‘resource – property – value’ triples. • Fixed set of tags for this purpose • RDFS – new tags such as Class, property, label, subclass Basic ontologies can therefore Be written in RDFS http://scom.hud.ac.uk/scomtlm/Artform/planning.html Author Lee McCluskey

  9. Recap - Ontologies • A formal, shared, specification of a conceptualization, where a conceptualization is “an abstract, simplified view of the world” • Encode more structured information than RDBs – can use them to do simple reasoning with instances and classes Interpretation Y X C subset of X U Y D&Y => Z Reality Conceptualisation Ontology “an abstract, simplified view of the world”

  10. Recap – FOL • A way of specifying a conceptualisation using Wffs Wff W is true in an interpretation I if W evaluates to true under I. w logically follows from W if and only if every interpretation that makes W true also makes w true

  11. Recap – logic interpretations These 2 Interpretations SATISFY this WFF Ax Ey R(y,x) Greater_than Mother_of persons numbers “Given any person there is Someone who is their mother” “Given any number there Is some number greater than it” WFF = WFF =

  12. Recap – reasoning with FOL Resolution Refutation: To PROVE Wff2 FROM Wff1 1. Translate Wff1 to CLAUSAL FORM 2. Translate ~ Wff2 to CLAUSAL FORM 3. Get contradiction from 1 + 2 using Resolution …. If follows that Wff1 |- Wff2 But use of FOL controversial as: • Reasoning not tractable in general • FOL language ‘flat’ – not designed for the SW!

  13. Recap – Description Logic • DL was designed for use in formalising diagrammtic notations used in OO Modelling, Semantics Nets, Ontology description etc • It is more compact than FOL • It is built around the notion of concepts/classes - a concept or class is the set of individuals x that satisfy some Wff(x) • Its basic reasoning mechanism is subsumption – does one class subsume another? Eg E_Fatherof.Male (the set of fathers who have sons) Eg Person with > 2 degrees subsumes Person with > 3 degrees • OWL-DL is a notation for a DL. Reasoning with OWL is based on the “Open World Assumption”.

  14. New Draft Schedule for next term • Week 13 lecture: Building Ontologies with Protégé/Owl • Week 14 lecture: Building Ontologies with Protégé/Owl • Week 15 lecture: Intelligent internet agents – basics. types of agent - multi agents, mobile agents, information agents • Week 16 lecture: Intelligent internet agents – reasoning+planning, • Week 17 lecture: Intelligent internet agents – adaptation+ learning • Week 18 lecture: Semantic web services: automated reasoning with web pages; • Week 19 lecture: Semantic mark-up for web services: service description languages eg DAML-S and OWL-S • Week 20 lecture: Automated service composition and service discovery; • Week 21 – 23: applications, domain modelling example?

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