The Semantic Web Week 12 Term 1 Recap Lee McCluskey, room 2/07 Department of Computing And Mathematical Sciences Module Website:

SW - Fundamental Idea - 1 n 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. n So ‘data files’ only make sense to the methods we write to manipulate them n 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. n Current data on the internet is largely unstructured and not amenable to processing. The data is by definition very rich and inherently structured.

SW - Fundamental Idea - 2 n 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. n 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. n The meaning of the data / processes will therefore have to be encoded u.. To be program-independent (declarative) u.. To be accessible to the client program n 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.

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

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

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

Recap – XML / XMLS n 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. n 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 ! n XML schema documents are used to VALIDATE XML documents. n 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.

Recap – RDF / RDFS n Introduce a convention that we will (at the basic level) describe data as ‘resource – property – value’ triples. n Fixed set of tags for this purpose n RDFS – new tags such as Class, property, label, subclass Basic ontologies can therefore Be written in RDFS Lee McCluskey Author

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

Recap – FOL n 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

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

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 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!

Recap – Description Logic n DL was designed for use in formalising diagrammtic notations used in OO Modelling, Semantics Nets, Ontology description etc n It is more compact than FOL n It is built around the notion of concepts/classes - a concept or class is the set of individuals x that satisfy some Wff(x) n 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 n OWL-DL is a notation for a DL. Reasoning with OWL is based on the “Open World Assumption”.

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