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An Introduction to Semantic Web Portal Ching-Long Yeh 葉慶隆 Department of Computer Science and Engineering Tatung University

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Presentation on theme: "An Introduction to Semantic Web Portal Ching-Long Yeh 葉慶隆 Department of Computer Science and Engineering Tatung University"— Presentation transcript:

1 An Introduction to Semantic Web Portal Ching-Long Yeh 葉慶隆 Department of Computer Science and Engineering Tatung University

2 Semantic Web Portal2 Outline A brief description to the Semantic Web Portal Architectural basis of the Semantic Web KA2: an ontology-based web portal An architecture of RDF triple data store Conclusions

3 Semantic Web Portal3 Introduction to Semantic Web Facilities to put machine-understandable data on the Web are becoming a high priority for many communities. The Web can reach its full potential only if it becomes a place where data can be shared and processed by automated tools as well as by people. For the Web to scale, tomorrow's programs must be able to share and process data even when these programs have been designed totally independently.

4 Semantic Web Portal4 Introduction to Semantic Web The Semantic Web is a vision: See “W3C Semantic Web Activity,” by Marja-Riitta Koivunen, for more descriptions.W3C Semantic Web Activity the idea of having data on the web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications

5 Semantic Web Portal5 The Semantic Web Layered Architecture (http://www.w3.org/2001/T alks/0228-tbl/slide5-0.html) Tim Berners-Lee: “Axioms, Architecture and Aspirations” W3C all-working group plenary Meeting 28 February 2001 URIUnicode XMLNamespaces XML Schema Sig RDF M&S RDF Schema Ontology Rules Logic Proof

6 Semantic Web Portal6 AI’s Chance Increasing demand for formalized knowledge on the Web: AI’s chance! XML- & RDF-based markup languages provide a 'universal' storage/interchange format for such Web- distributed knowledge representation. DTDs XML RDF[S] Namespaces Stylesheets CSS XSLT XQL Queries XML-QL Transformations Acquisition Protégé Agents Frames Rules SHOE HornML RuleML DAML XQuery TopicMaps Ontobroker

7 The Big Picture of SW

8 Semantic Web Portal8 Web Portals A web portal is a web site that provides information content on a common topic. –General portals, e.g., Yahoo, Excite, Netscape, Lycos, CNET, MSN, and AOL.com –Specialized portal e.g., gardeners.com, semanticweb.org Making valuable information to be found –directory service, –search facility –news, , –community forum

9 Semantic Web Portal9 Ontology-Based Web Portals Ontology represents –common knowledge and interests sharing within their community Tasks that ontology can be used to support a portal –Accessing a portal Conceptual search and navigation Inference capabilities –Providing information Methods and tools accounting for the diversity of information sources

10 Semantic Web Portal10 Introduction to XML-Based Ontology URIUnicode XMLNamespaces XML Schema Sig RDF M&S RDF Schema Ontology Rules Logic Proof

11 Semantic Web Portal11 What is XML? Extensible Markup Language A Syntax for Documents A Meta-Markup Language A Structural and Semantic Language, not a Formatting Language Not just for Web pages

12 Semantic Web Portal12 Namespace Bindings Prefixes are bound to namespace URIs by attaching an xmlns:prefix attribute to the prefixed element or one of its ancestors, prefix:name 1,..., prefix:name n The value of the xmlns:prefix attribute is a URI, which may or (unlike for DTDs!) may not point to a description of the namespace’s syntax An element can use bindings for multiple name-spaces via attributes xmlns:prefix 1,..., xmlns:prefix m

13 Semantic Web Portal13 XML Document Instance and DTD Xaver M. Linde Wikingerufer Berlin / / /

14 Semantic Web Portal14 XML Schema An XML syntax that's an alternative and/or supplement to DTDs Data typing of element and attribute content

15 RDF M&S RDF (Resource Description Framework) –Beyond Machine readable to Machine understandable RDF consists of two parts –RDF Model (a set of triples) –RDF Syntax (different XML serialization syntaxes) RDF Schema for definition of Vocabularies (simple Ontologies) for RDF (and in RDF)

16 Semantic Web Portal16 RDF Data Model Resources –A resource is a thing you talk about (can reference) –Resources have URI’s –RDF definitions are themselves Resources (linkage, see requirement 1) Properties –slots, define relationships to other resources or atomic values Statements –“ Resource has Property with Value ” –(Values can be resources or atomic XML data) Similar to Frame Systems

17 Semantic Web Portal17 A Simple Example Statement –“Ora Lassila is the creator of the resource ” Structure –Resource(subject) –Property(predicate) –Value(object) "Ora Lassila” Directed graph s:Creator Ora Lassila

18 Semantic Web Portal18 Name s:Creator Another Example To add properties to Creator, point through an intermediate Resource. Person://fi/ Ora Lassila

19 Semantic Web Portal19 Example: Bag The students in course are Amy, Tim, John, Mary, and Sue Rdf:Bag /Students/Amy /Students/Tim /Students/John /Students/Mary /Students/Sue bagid1 /courses/6.001 students rdf:type rdf:_1 rdf:_2 rdf:_3 rdf:_4 rdf:_5

20 Semantic Web Portal20 rdf:_1 rdf:_2 rdf:_3 rdf:type source ftp.eu.net ftp.cs.purdue.edu ftp.x.org Example: Alternative The source code for X11 may be found at ftp.x.org, ftp.cs.purdue.edu, or ftp.eu.net altid rdf:Alt

21 Semantic Web Portal21 RDF Syntax I Data model does not enforce particular syntax Specification suggests many different syntaxes based on XML General form: Ora Lassila Starts an RDF-Description Properties Subject (OID) Literal Resource (possibly another RDF-description)

22 Semantic Web Portal22 Resulting Graph Ora Lassila Ora Lassila s:createdWith s:Creator

23 RDF Syntax II: Syntactic Varieties

24 Semantic Web Portal24 RDF Schema (RDFS) RDF just defines the data model Need for definition of vocabularies for the data model - an Ontology Language! The RDF Schema mechanism provides a basic type system for use in RDF models. The RDF schema specification language is less expressive, but much simpler to implement, than full predicate calculus languages such as CycL and KIF.

25 Semantic Web Portal25 Most Important Modeling Primitives Core Classes –Root-Class rdfs:Resource –MetaClass rdfs:Class –Literals rdfs:Literal rdfs:subclassOf -property Inherited from RDF: properties (slots) rdfs:domain & rdfs:range rdfs:label, rdfs:comment, etc. Inherited from RDF: InstanceOf ( rdf:type )

26 Semantic Web Portal26 DAML+OIL: an Ontology Language Extension of RDF Schema Ontology Language DAML+OIL: Result of a Joint (European + US-American) Committee Extension of RDF Schema –Class Expressions (Intersection, Union, Complement) –XML Schema Datatypes –Enumerations –Property Restrictions Cardinality Constraints Value Restrictions

27 Semantic Web Portal27 Example: Intersection & Synonyms

28 Semantic Web Portal28 Example: Disjoint & Complement no car is a person Disjoint not strictly necessary, since expressible via pairwise subClassOf of complementOf, as for Car and Person :

29 Semantic Web Portal29 Example: Properties (Transitive, Inverse, subProperty, UniqueProperty, range, Datatypes)

30 Semantic Web Portal30 Using User-defined Datatypes (based on XML Schema) =18-->

31 Semantic Web Portal31 Instances (Individuals) Adam Adam is a person....

32 Semantic Web Portal32 Web Services

33 Semantic Web Portal33 DAML-S Users and software agents should be able to discover, invoke, compose, and monitor Web resources offering particular services and having particular properties. As part of the DARPA Agent Markup Language program, we have begun to develop an ontology of services, called DAML-S.

34 Semantic Web Portal34 Top Level of the Service Ontology Service Resource Service Grounding ServiceProfile ServiceModel provides presents supportsdescribed by (what it does) (how it works) (how to access it)

35 Semantic Web Portal35 Process Modeling Ontology

36 Semantic Web Portal36 Concept of ebXML Business Process Specification Schema

37 Semantic Web Portal37 Business Process Specification in XML

38 KA2 An Ontology-Based Community Web Portal

39 Semantic Web Portal39 KA2 Knowledge Annotation Initiative of the Knowledge Acquisition Community The basic scenario –WWW documents of the KS community were annotated according to the schema of an ontology. –The annotations enable intelligent access to these documents and infer implicit knowledge from explicitly stated facts and rules from the ontology.

40 The KA2 Ontology Class hierarchy Person Employee Academic-Staff Lecturer Researcher Administrative-Staff Secretary Technical-Staff Student Phd-Student Relations Address, Affiliation, Cooperates-With, Editor-Of, , First-Name, Has- Publication, Head-Of-Group, Head-Of- Project, Last-Name, Member-Of- Organization, Member-Of-Program- Committee, Member-Of-Research-Group, Middle-Initial, Organizer-Of-Chair-Of, Person-Name, Photo, Research-Interest, Secretary-Of, Studies-At, Supervises, Supervisor, Works-At-Project Person-ontology Class hierarchy On-Line-Publication Publication Article Article-In-Book Conference-Paper Journal-Article Technical-Report Workshop-Paper Book Journal IEEE-Expert IJHCS Special-Issue Relations Abstract, Book-Editor, Conference- Proceedings-Title, Contains-Article-In- Book, Contains-Article-In-Journal, Describes-Project, First-Page, Has- Author, Has-Publisher, In-Book, In- Conference, In-Journal, In-Organization, In-Workshop, Journal-Editor, Journal- Number, Journal-Publisher, Journal-Year, Last-Page, On-Line-Version, … Publication-ontology

41 Semantic Web Portal41 Accessing the Community Web Portal Query capability –In F-Logic mechanism Navigating capability –As the easy-to-use front-end of the query mechanism

42 Semantic Web Portal42 Query Capabilities For all publications of the researcher “Steffen Staab”. FORALL Pub <- EXISTS ResID ResID:Researcher[NAME->> Steffen "Staab"; PUBLICATION ->> Pub]. Two researchers cooperate, if a Researcher X works at a Project Proj and if a Researcher Y works at the same Project Proj and X is another person than Y FORALL X; Y; Proj X:Researcher[COOPERATESWITH ->> Y:Researcher] <- X:Researcher[WORKSATPROJECT->>Proj:Project] AND Y:Researcher[WORKSATPROJECT->>Proj:Project] AND NOT equal(X; Y ): Which researchers are cooperating with other r? FORALL ResID1, ResID2 <- ResID1:Researcher[COOPERATESWITH ->> ResID2].

43 Semantic Web Portal43 Navigating and Querying the Portal Query the portal using F-Logic is too inconvenient. Navigating and querying the web –A hypertext link may contain a query dynamically evaluated when clicking on the link (See P. 45) –Query generated by using the hyperbolic view interface (See P. 46) –Queries may be personalized and for the different users and available for the user in a selection list. –An expert mode: Querying the portal by typing an F-Logic statement

44

45

46 Semantic Web Portal46 Providing Information Integrating various syntactic and semantic formats based on the common ontology Three different modes of information provision are supported –Metadata-based information –Wrapper-based information –Fact-based information

47 Semantic Web Portal47 Metadata Metadata-based Information Information source Annotation tool In RDF, XML (OntoPad Annotea, …)

48 Semantic Web Portal48 Wrapper-based Information Annotating information sources by hand is time- consuming. Semi-structured Information sources (e.g., HTML) Structured Information sources (e.g., RDB) Wrapper program Metadata (Onto Wrapper)

49 Semantic Web Portal49 Fact-Based Information Fact Editor New facts create add, modify, delete Knowledge warehouse (Ontoedit, OilED, Protégé 2000)

50 Semantic Web Portal50 Development of Web Portals

51 Semantic Web Portal51 The System Architecture

52 An Architecture of RDF Triple Data Store

53 Semantic Web Portal53 RDF Parser and Generator Using DCG in Prolog as the development tool Formal grammar in RDF M&S Spec Prolog’s inference engine Formal grammar rules in DCG Prolog’s working storage User interface

54 [6.1] RDF ::= [' '] obj* [' '] [6.2] obj ::= description | container [6.3] description ::= ' ' | ' ' propertyElt* ' ' | typedNode [6.4] container ::= sequence | bag | alternative rdf(Objs) --> ([''],{wl('XML heading')} ;[]), (fullSTG('RDF',NS) ; halfSTG('RDF',NS), ['>'] ; [ ]), objStar(Objs), (fullETG('RDF',NS);[ ]). objStar(Out) --> obj(O), objStar(R),{Out=[O|R]} ; [],{Out=[]}. obj(Obj) --> container(Obj) ; description(_),{getAllTriples(Obj)}. getAllTriples(Obj):- findall(statement(A,B,C),statement(A,B,C),Obj). description(_) --> halfSTG('Description',NS), (idAboutAttr(IdAboutAttr);[]), (bagIdAttr(BagIdAttr);[]), propAttrStar(IdAboutAttr), (['/>'] ; ['>'], propertyEltStar(IdAboutAttr), fullETG('Description',NS)), {reificationOfStatements(IdAboutAttr,B agIdAttr)} ; typedNode.

55 [statement(about/http://www.foo.com/cool.html, Title, alt(_87882,[string/The Coolest Web Page, string/Il Pagio di Web Fuba])), statement(about/http://www.foo.com/cool.html, Identifier, bag(id/MirroredSites,[resource/http://www.foo.com.au/cool.html, resource/http://www.foo.com.it/cool.html])), statement(about/http://www.foo.com/cool.html, Creator, seq(id/CreatorsAlphabeticalBySurname,[string/Mary Andrew, string/Jacky Crystal]))] Mary Andrew Jacky Crystal The Coolest Web Page Il Pagio di Web Fuba RDF input Prolog output

56 RDF Statements in RDB Tables IdNsName 1http://www.w3.org/2000/01/rdf# 2http://purl.org/metadata/dublin_core# …… IdNSPredicateName 12Creator 22Language ……… IdResourceName …… IdLiteralName 1 Jacky Crystal 2English …… IdResourcePredicateLiteral ………… RDF_NameSpace RDF_Predicate RDF_Literal RDF_Statement RDF_Resource

57 Semantic Web Portal57 User Interface Conceptual Search Natural language interface is the best choice, but is very difficult to obtain a good result. Form-based interface is easy to implement, but is too restricted. Hierarchical directory browsing is perhaps a good idea, if the domain in question is well organized. We also propose a frame-based query interface. target_concept[(attribute 1 [:value 1 ], …)] teacher(office:6th_floor)

58 Semantic Web Portal58 User Interface Natural Language Generation Knowledge Warehouse (RDF) Content extraction Text planning Content planning Multi-sentential text NLG

59 Semantic Web Portal59 Future Work Building an ontology for the Digital Archive Services –Consisting of resource and process parts Declarative approach to semantic web service –Using an workflow engine to interpret the process descriptions Intelligent Q&A for digital archive

60 Semantic Web Portal60 Summary Semantic Web portals –Machine-understandable information –RDF store –Accessing information Navigation and query –Providing information Annotation, wrapper, fact editing –Enabling automatic processing by software agents


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