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

2. 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
Semantic Web Portal

3. 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.
Semantic Web Portal

4. Introduction to Semantic Web
The Semantic Web is a vision:
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
See “W3C Semantic Web Activity,” by Marja-Riitta Koivunen, for more descriptions.
Semantic Web Portal

5. The Semantic Web Layered Architecture
URI
Unicode
XML
Namespaces
XML Schema
Sig
RDF M&S
RDF Schema
Ontology
Rules
Logic
Proof
Tim Berners-Lee:
“Axioms, Architecture and Aspirations”
W3C all-working group plenary Meeting
28 February 2001 (
Semantic Web Portal

6. AI’s Chance
Namespaces
CSS
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
XSLT
DAML
Stylesheets
Agents
Ontobroker
Transformations
HornML
XML
XQL
Rules
Queries
RuleML
XQuery
XML-QL
SHOE
Frames
RDF[S]
Acquisition
TopicMaps
Protégé
Semantic Web Portal

7. The Big Picture of SW

8. 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
Semantic Web Portal

9. 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
Semantic Web Portal

10. Introduction to XML-Based Ontology
URI
Unicode
XML
Namespaces
XML Schema
Sig
RDF M&S
RDF Schema
Ontology
Rules
Logic
Proof
Semantic Web Portal

11. 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
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12. Namespace Bindings
Prefixes are bound to namespace URIs by attaching an xmlns:prefix attribute to the prefixed element or one of its ancestors, prefix:name1 ,..., prefix:namen
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:prefix1 ,..., xmlns:prefixm
Semantic Web Portal

13. XML Document Instance and DTD
<mail:address xmlns:mail="
xmlns:tele="
<mail:name>Xaver M. Linde</mail:name>
<mail:street>Wikingerufer 7</mail:street>
<mail:town>10555 Berlin</mail:town>
<mail:bill>12.50</mail:bill>
<tele:phone>030/ </tele:phone>
<tele:phone>030/ </tele:phone>
<tele:fax>030/ </tele:fax>
<tele:bill>76.20</tele:bill>
</ mail:address>
<!ELEMENT address (name, street, town,
bill, phone+, fax+, bill)>
<!ELEMENT name (#PCDATA)>
<!ELEMENT street (#PCDATA)>
<!ELEMENT town (#PCDATA)>
<!ELEMENT bill (#PCDATA)>
<!ELEMENT phone (#PCDATA)>
<!ELEMENT fax (#PCDATA)>
<!ELEMENT ARTIST (#PCDATA)>
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14. XML Schema
An XML syntax that's an alternative and/or supplement to DTDs
Data typing of element and attribute content
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15. RDF M&S RDF (Resource Description Framework) RDF consists of two parts
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. RDF Data Model Resources Properties Statements
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
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17. A Simple Example Statement Structure Directed graph
“Ora Lassila is the creator of the resource
Structure
Resource (subject)
Property (predicate)
Value (object) "Ora Lassila”
Directed graph
s:Creator
Ora Lassila
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18. Another Example
To add properties to Creator, point through an intermediate Resource.
s:Creator
Person://fi/
Name
Ora Lassila
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19. Example: Bag
The students in course are Amy, Tim, John, Mary, and Sue
/courses/6.001
Rdf:Bag
rdf:type
/Students/Amy
students
rdf:_1
rdf:_2
/Students/Tim
bagid1
rdf:_3
/Students/John
rdf:_4
/Students/Mary
rdf:_5
/Students/Sue
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20. Example: Alternative
The source code for X11 may be found at ftp.x.org, ftp.cs.purdue.edu, or ftp.eu.net
rdf:Alt
rdf:type
source
altid
rdf:_1
ftp.x.org
rdf:_2
ftp.cs.purdue.edu
rdf:_3
ftp.eu.net
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21. RDF Syntax I Data model does not enforce particular syntax
Specification suggests many different syntaxes based on XML
General form:
Starts an RDF-Description
Subject (OID)
<rdf:RDF>
<rdf:Description about="
<s:Creator>Ora Lassila</s:Creator>
<s:createdWith rdf:resource=“
</rdf:Description>
</rdf:RDF>
Literal
Resource (possibly another RDF-description)
Properties
Semantic Web Portal

22. Resulting Graph <rdf:RDF>
s:Creator
s:createdWith
Ora Lassila
<rdf:RDF>
<rdf:Description about="
<s:Creator>Ora Lassila</s:Creator>
<s:createdWith rdf:resource=“
</rdf:Description>
</rdf:RDF>
Semantic Web Portal

23. RDF Syntax II: Syntactic Varieties
Typing Information
Subject (OID)
In-Element Property
<s:Homepage rdf:about="
s:Creator=“Ora Lassila”/>
<s:createdWith>
<s:HTMLEditor rdf:about=“
</s:createdWith>
</s:Homepage>
rdf:type
s:Homepage
Property
s:createdWith
s:Creator
rdf:type
HTMLEditor
Ora Lassila

24. 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.
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25. 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)
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26. DAML+OIL: an Ontology Language
Extension of RDF Schema
Ontology Language DAML+OIL: Result of a Joint (European + US-American) Committee
Class Expressions (Intersection, Union, Complement)
XML Schema Datatypes
Enumerations
Property Restrictions
Cardinality Constraints
Value Restrictions
Semantic Web Portal

27. Example: Intersection & Synonyms
<daml:Class rdf:ID="TallMan">
<daml:intersectionOf rdf:parseType="daml:collection">
<daml:Class rdf:about="#TallThing"/>
<daml:Class rdf:about="#Man"/>
</daml:intersectionOf>
</daml:Class>
<daml:Class rdf:ID="HumanBeing">
<daml:sameClassAs rdf:resource="#Person"/>
</daml:Class>
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28. Example: Disjoint & Complement
<daml:Disjoint rdf:parseType="daml:collection">
<daml:Class rdf:about="#Car"/>
<daml:Class rdf:about="#Person"/>
<daml:Class rdf:about="#Plant"/>
</daml:Disjoint>
Disjoint not strictly necessary, since expressible via pairwise subClassOf
of complementOf, as for Car and Person:
<daml:Class rdf:ID="Car">
<rdfs:comment>no car is a person</rdfs:comment>
<rdfs:subClassOf>
<daml:Class>
<daml:complementOf rdf:resource="#Person"/>
</daml:Class>
</rdfs:subClassOf>
Semantic Web Portal

29. Example: Properties (Transitive, Inverse, subProperty, UniqueProperty, range, Datatypes)
<daml:TransitiveProperty rdf:ID="hasAncestor"/>
<daml:ObjectProperty rdf:ID="hasChild">
<daml:inverseOf rdf:resource="#hasParent"/>
</daml:ObjectProperty>
<daml:UniqueProperty rdf:ID="hasMother">
<rdfs:subPropertyOf rdf:resource="#hasParent"/>
<rdfs:range rdf:resource="#Female"/>
</daml:UniqueProperty>
<daml:DatatypeProperty rdf:ID="age">
<rdf:type rdf:resource="
<rdfs:range rdf:resource="
</daml:DatatypeProperty>
Semantic Web Portal

30. Using User-defined Datatypes (based on XML Schema)
<xsd:simpleType name="over17">
<!--over17 is an XMLS datatype based on decimal-->
<!--with the added restriction that values must be >=18-->
<xsd:restriction base="xsd:decimal">
<xsd:minInclusive value="18"/>
</xsd:restriction>
</xsd:simpleType>
<daml:Class rdf:ID="Adult">
<daml:intersectionOf rdf:parseType="daml:collection">
<daml:Class rdf:about="#Person"/>
<daml:Restriction>
<daml:onProperty rdf:resource="#age"/>
<daml:hasClass rdf:resource="somefile#over17"/>
</daml:Restriction>
</daml:intersectionOf>
</daml:Class>
Semantic Web Portal

31. Instances (Individuals)
<daml:Class rdf:ID="Person">
. . .
</daml:Class>
<Person rdf:ID="Adam">
<rdfs:label>Adam</rdfs:label>
<rdfs:comment>Adam is a person.</rdfs:comment>
<age><xsd:integer rdf:value="13"/></age>
<shoesize>
<xsd:decimal rdf:value="9.5"/>
</shoesize>
</Person>
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32. Web Services
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33. 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.
Semantic Web Portal

34. Top Level of the Service Ontology
Resource
provides
ServiceProfile
presents
(what it does)
Service
(how it works)
(how to access it)
supports
described by
Service Grounding
ServiceModel
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35. Process Modeling Ontology
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36. Concept of ebXML Business Process Specification Schema
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37. Business Process
Specification
in XML
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38. KA2 An Ontology-Based Community Web Portal

39. 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.
Semantic Web Portal

40. The KA2 Ontology Person-ontology Publication-ontology Class hierarchy
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
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, …

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

42. 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].
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43. 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
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46. 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
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47. Metadata-based Information
In RDF, XML
Metadata
Information
source
Annotation tool
(OntoPad Annotea, …)
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48. Wrapper-based Information
Annotating information sources by hand is time-consuming.
Semi-structured
Information sources
(e.g., HTML)
Wrapper
program
Metadata
Structured
Information sources
(e.g., RDB)
(Onto Wrapper)
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49. Fact-Based Information
create
New facts
add,
modify,
delete
Knowledge
warehouse
Fact Editor
(Ontoedit, OilED,
Protégé 2000)
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50. Development of Web Portals
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51. The System Architecture
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52. An Architecture of RDF Triple Data Store

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

54. [6.1] RDF ::= ['<rdf:RDF>'] obj* ['</rdf:RDF>']
[6.2] obj ::= description | container
[6.3] description ::= '<rdf:Description' idAboutAttr? bagIdAttr? propAttr* '/>'
| '<rdf:Description' idAboutAttr? bagIdAttr? propAttr* '>'
propertyElt* '</rdf:Description>'
| typedNode
[6.4] container ::= sequence | bag | alternative
rdf(Objs) -->
(['<?'],
([nm/'xml'];[nm/'XML'];
[nm/'xmls'];[nm/'XMLS']),
([nm/'version','=',qs/_];[]),
([nm/'encoding','=',qs/_];[]),
['?>'],{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,BagIdAttr)}
typedNode.

55. RDF input Prolog output [statement(about/http://www.foo.com/cool.html,
<rdf:RDF
xmlns:rdf="
xmlns:dc="
<rdf:Description about="
<dc:Creator>
<rdf:Seq ID="CreatorsAlphabeticalBySurname">
<rdf:li>Mary Andrew</rdf:li>
<rdf:li>Jacky Crystal</rdf:li>
</rdf:Seq>
</dc:Creator>
<dc:Identifier>
<rdf:Bag ID="MirroredSites">
<rdf:li rdf:resource="
<rdf:li rdf:resource="
</rdf:Bag>
</dc:Identifier>
<dc:Title>
<rdf:Alt>
<rdf:li xml:lang="en">The Coolest Web Page</rdf:li>
<rdf:li xml:lang="it">Il Pagio di Web Fuba</rdf:li>
</rdf:Alt>
</dc:Title></rdf:Description></rdf:RDF>
RDF input
[statement(about/
Title,
alt(_87882,[string/The Coolest Web Page,
string/Il Pagio di Web Fuba])),
statement(about/
Identifier,
bag(id/MirroredSites,[resource/
resource/
Creator,
seq(id/CreatorsAlphabeticalBySurname,[string/Mary Andrew,
string/Jacky Crystal]))]
Prolog
output

56. RDF Statements in RDB Tables
RDF_NameSpace Id
NsName 1 2 …
RDF_Resource Id
ResourceName 1 2 …
RDF_Statement Id
Resource
Predicate
Literal 1 2 …
RDF_Predicate Id NS
PredicateName 1 2
Creator
Language …
RDF_Literal Id
LiteralName 1
Jacky Crystal 2
English …

57. 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[(attribute1[:value1], …)]
teacher(office:6th_floor)
Semantic Web Portal

58. User Interface Natural Language Generation
Knowledge
Warehouse
(RDF)
Content
extraction
Text
planning
Multi-sentential
text
Content
planning
NLG
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59. 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
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60. 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
Semantic Web Portal