1 ICS-FORTH London 25/01/02 Christophides Vassilis On Community Web Portals and the Semantic Web: A Database Perspective Vassilis Christophides Computer.

Christophides Vassilis

1

ICS-FORTH London 25/01/02

On Community Web Portals and the Semantic Web:

A Database Perspective

Vassilis Christophides Computer Science Department, University of Crete

Institute for Computer Science - FORTHHeraklion, Crete


2


Portalmania!


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Elements of Comparison

Gateways to WWW resources with the aim of making information/service research simpler and more effective

Horizontal Portals Vertical or Thematic Portals

E-marketplaces

Scope Internet-oriented Subject-oriented Industry-oriented

Mission reference points for the general user

promote access to information

promote economic activity

Methods voluntary registration; human or robot-driven resource collection

expert selection of resources

voluntary participation by companies


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Common Objectives/Goals Community Knowledge Management

Ranging from simple vocabularies to formal ontologies Aggregation/Integration of Community Content

Ranging from unstructured (documents) to semi-structured (web sites) and structured information (data)

Collaboration & MessagingRanging from simple to advanced task management (synchronous/

asynchronous) System Integration & Security

Front end to application servers/ workflow systems User Personalization (“pull”) & Syndicated Content Subscription (“push”)

role-based access controlinformation filtering (contexts/viewpoints)customizable information rendering location/time specific information


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Advanced Knowledge Schemas

(ontologies, thesauri)

<tag1> <tag2> <tag3></tag1>


Complexity and diversity

of information resources

Heterogeneous

resource descriptions

Community Web Portals: Knowledge Management


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Community Web Portals: A Broader Functional View

Presentation ServicesPresentation Services

Access and Integration ServicesAccess and Integration Services

Information ServicesInformation Services Personalization ServicesPersonalization Services Collaboration ServicesCollaboration Services

ClassificationMetadata

Content Syndication

SecurityNetwork

TaskManagement

Application Integration

SystemManagement

Description, SearchDocs Repositories

Messaging Workflow

Annotations, Recommendations

Multiple Style SheetsVirtual Documents


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On the Semantic Web

Main infrastructure for supporting Community Webs

groups of people sharing a domain of discourse and a set of information resources (e.g., data, documents, services) and having some common interests/objectives

Higher Quality Web Information Services

having data and programs described in a way that facilitates their reuse and integration by machines across applications

Semantic Web

Education

HealthCommerce

Workplace


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Metadata exists for Almost Anything/Everywhere

Physical Objects, Places,

People,

Devices, Networks,

Infrastructure,

Digital Documents, Data,

Programs,

User Profiles, Preferences,




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RDF Objectives

Enables communities to define their own semantics of resource descriptions

we can disagree about semantics, but share the same infrastructure (syntax, editors, query languages, databases, etc.)

Imposes structural constraints on the expression of metadata in various application contexts

for consistent encoding, exchange and processing of metadata on the Web

Facilitates development of metadata vocabularies without central coordination

mechanisms for reusing descriptions of resources, concepts, etc.

Focus on DBMS technology for RDF metadataRelated W3C efforts on XML data management


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Looking at existing RDF Applications

Publishing/News: BiblinkScholarly Link Specification (Slinks)Rich Site Summary (RSS)

Education/ Academic:Common European Research

Information Format (CERIF)Mathematics InternationalUniversal IMS Global Learning Consortium

Cultural Heritage/ Archives/ Libraries:Inter. Committee for Documentation

Reference Schema (CIDOC)Research Support Libraries – Colle

ction Level Description (RSLP-CLD) EUropean Libraries & Electronic

Resources in Mathematical Sciences (Euler)

Audio-visual: Internet Movie DataBase (IMDB)

Ubiquitous/Mobile/Grid ComputingComposite Capability/Preference

Profile (CC/PP)RDF Calendar Task ForceScheduler Allocation Ontology(SAO)

E-commerceBasic Semantic Registry (BSR)Real Estate Data ConsortiumUniversal Standard Products and

Services Classification (UNSPSC) Geospatial/ Environmental:

Geography Markup Language(GML) Costal Zone Management Ontology

Biology/MedecineGene Ontology

Cross-domain


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Semantic Depth of Resource Descriptions

Dictionaries and Vocabularies: the schemas developed at this level define simple lists of concepts

and their definitions Taxonomies:

their characteristic is that the main relation they define between concepts is that of specialization

Thesauri: besides defining relations among broader/narrower terms through

the definition of hierarchies, a thesaurus also declares relations of equivalence, association and synonymy

Reference Models:comprise a representation vocabulary for referring to the concepts

in the subject area and the logical statements that describe the nature of the terms, the relations among the terms and the way the terms can or cannot be related to each other


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A First Classification of RDF Schemas

Application Domain Dictionary/ Vocabulary

Taxonomy Thesaurus Reference Model

Cultural Heritage/Archives/Libraries

EulerRSLP-CLD

CIDOC

Educational/

Academic

IMSUniversal

Mathematics International

CERIF

Publishing/ News BibLinkSLinkSRSS

Audio-Visual IMDB

Geospatial/ Environmental CZM GML

Biology/ Medicine Gene

E-Commerce BSRUNSPSC

RED

Ubiquitous/ Mobile/Grid Computing

CC/PP RDF CalendarSAO

Cross-Domain CERES/NBIIDublin CoreWordNet

Metanet Limber ThesaurusTop Level Ontology


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Outline

Database issues for RDF metadata managementThe Data Independence IssueThe Query Language IssueThe Model Issue

RDF Query Language: RQLQuerying Large RDF SchemasFiltering/Navigating Complex RDF

descriptions Storing Voluminous RDF descriptions

Alternative DB representationsPerformance Figures

The ICS-FORTH RDFSuite Conclusions and remaining issues


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The Data Independence Issue

Conceptual Level: Describing resources

using one or several RDF schemas

Logical Level: How RDF descriptions

and schemas are physically stored

Logical-schema: Data organization

using tables, objects, etc.

Physical-schema: Data organization

using files, records, indices, etc.

RDF data independence is crucial for

ensuring scalability of real-scale

Semantic Web applications


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The Query Language Issue

Querying the

Structure(Squish)

Querying the

Semantics(RQL)

Querying the

Syntax(XQuery)XML

Repository

Find description elements whose attribute value contains ….

Triple Database

Find statements whose subject is … and object is …

Description Graphs

Find resources classified under … whose property value is ….


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Why a Data Model for RDF ?

As support for physical/logical independenceRDF can be stored in files, a native repository, a relational databaseRDF can be virtual, as a view of a repository, integrated sourcesRDF can be in memory, using data structures in C, C++, Java, etcRDF can be streamed between processes

To describe information content of RDF Statementsto agree and reason about information content, preservation

To define semantics of a data manipulation language: A query language describes in a declarative fashion, the mapping

between an input instance of the data model to an output instance of the data model


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<rdf:Description rdf:ID=“picasso132" fname=Pablo lname=Picasso> <paints rdf:resource="http://museoreinasofia.mcu.es/guernica.gif"/> <paints rdf:resource="http://www.artchive.com/woman.jpg”/> <rdf:type>Painter</rdf:type></rdf:Description> <rdf:Description rdf:about ="http://museoreinasofia.mcu.es/guernica.gif"> <rdf:type>Painting</rdf:type> <created>1937</created> </rdf:Description> <rdf:Description rdf:about =" http://www.artchive.com/woman.jpg"> <rdf:type>Painting</rdf:type> <created>1904</created> </rdf:Description>

<Painter rdf:ID=“picasso132"> <fname>Pablo</fname> <lname>Picasso</lname> <paints> <Painting rdf:about="http://www.artchive.com/woman.jpg”/> <created>1904</created> </paints> <paints> <Painting rdf:about="http://museoreinasofia.mcu.es/guernica.gif"> <created>1937</created> </Painting> </paints></Painter>

But RDF has specifics: Serialization syntax

&r3

&r2paints

&r6

fname

lnamepaints

“Pablo”

“Picasso” 1904created

1937created

r2: museoreinasofia.mcu.es/guernica.jpgr3:www.artchive.com/woman.jpg

r6: picasso132

PaintingPainter

rdf:type rdf:type

XML attributes vs elements for RDF properties fname, lname

XML flat vs nested structures of RDF statements Description vs. Painter elements

RDF properties are unordered, optional, and multivalued 2 paints and 0 creates

One more motivation for a data model :isolate the user from syntactic aspects of RDF/XML


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<rdfs:Class rdf:ID="Artist"/><rdfs:Class rdf:ID="Artifact"/> <rdfs:subClassOf rdf:resource="#Artist"/> </rdfs:Class><rdfs:Class rdf:ID="Painter"> <rdfs:subClassOf rdf:resource="#Artist"/> </rdfs:Class><rdfs:Class rdf:ID="Painting"> <rdfs:subClassOf rdf:resource="#Artifact"/> </rdfs:Class><rdf:Property rdf:ID="fname"> <rdfs:domain rdf:resource="#Painting"/> <rdfs:range rdf:resource=“ http://www.w3.org/rdf- datatypes.xsd#String"/></rdf:Property>

<rdf:Property rdf:ID="creates"> <rdfs:domain rdf:resource="#Artist"/> <rdfs:range rdf:resource="#Artifact"/> </rdf:Property><rdf:Property rdf:ID="paints"> <rdfs:domain rdf:resource="#Painter"/> <rdfs:range rdf:resource="#Painting"/> <rdfs:subPropertyOf rdf:resource="#creates"/> </rdf:Property><rdf:Property rdf:ID="created"> <rdfs:domain rdf:resource="#Painting"/> <rdfs:range rdf:resource=“ http://www.w3.org/rdf- datatypes.xsd#Date"/></rdf:Property>

Distinguish between labels of nodes and edges Painter vs. paints

Class and properties are organized in subsumption hierarchiesPainter <= Artist

Properties are inherited&r6 may also have a creates property

References are typed&r2 should be of class <= Painting

Literal values are typed1937 is not a string but a date value !

But RDF has specifics: Schema Semantics

ArtistString

Artifact

Painting

createsfname

lname

paints

String

createdDatePainter


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But RDF has specifics: Superimposed Descriptions

Resources may belong to multiple (unrelated though isa) classes &r2 is both a Painting and an ExtResource

Heterogeneous descriptions reminiscent of SGML exceptions What is the structure of Painting resources?

&r3

&r2paints

&r6

fname

lnamepaints

“Pablo”

“Picasso”

1904created

1937created

rdf:type rdf:type

ExtResourcefile_size

title String

Int

ArtistString

Artifact

Painting

createsfname

lname

paints

String

createdDatePainter

rdf:type

“Guernica”

4

title

file_size


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RDF/S vs. Well-Known Formalisms

Relational or Object Database Models (ODMG, SQL) Classes don’t define table or object types Instances may have associated quite different properties Collections with heterogeneous members

Semistructured or XML Data Models (OEM, UnQL, YAT, XML Schema) Labels only on nodes or edges Class and property subsumption is not captured Heterogeneous structures reminiscent to SGML exceptions

Knowledge Representation Languages (Telos, DL, F-Logic) Absence of complex values and n-ary relationships (bags, sequences)


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A Semistructured Data Model for RDF

Graph based, unordered, edge/node-labeled (in the style of OEM) But what about sequences (ordered)?

&r2

paints

&r6

fname lname paints

“Pablo” “Picasso”

1904

created

1937

created

“Guernica”4

titlefile_size&r3

Painter

PaintingExtresource

PaintingExtresourceString String

Date DateInt String

friends

&seq1

&r10

1 2fname lname

“XXXX” “YYYY”String String

Painter

Seq


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Towards a Formal Data Model for RDF

An RDF schema is a 5-tuple: RS = (VS, ES, H, , )VS a set of nodesES a set of edgesΗ = (Ν,<) a well-formed hierarchy of names an incidence function: Es VsVs

a labeling function: VS ES Ν Τ An RDF description base, instance of a schema RS, is a 5-tuple: RD =

(VD, ED, , , )VD a set of nodesED a set of edges an incidence function: ED VDVD a valuation function: VD V a labeling function: VD ED 2ΝΤ :

u VD, n CT: (u) [[n]] e ED [u,u’], p


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Why a Type System for RDF ?

For error detection & safety: to verify that statements comply to what the application expectsto make sure that the application accesses valid statements to enforce safe operations (e.g., don’t do float arithmetic on classes!)to check that compositions of operations make sense

For performance:to design storage (saving space, improving clustering, etc.)to process queries (algebraic laws, rewriting path expressions, etc.)

We need a full-fledged Data Definition Language for RDF !RDF Schema is viewed more as an ontology & modeling tool


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Towards a Type System for RDF

Type System:

= L | U | {} | [] | (1: + 2: + … + n:)

Interpretation Function:Literal types, [[ L ]] = dom(L)

Bag types, [[ {} ]] = {1, 2,…, n}, 1, 2,…, n V are values of type Seq types, [[ [] ]] = {1, 2,…, n}, 1, 2,…, n V are values of type Alt types, [[ (1:1 + 2:2 +…+ n:n ) ]] = I, i V, 1<i<n is a value of type i

c C, [[c]] = { | (c)}{(c’) | c’ < c}

p P, [[p]] = {[1, 2] | 1 [[domain(p)]], 2 [[range(p)]]}{(p’) | p’ < p}


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Querying RDF Descriptions: An Introduction to RQL


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The RDF Query Language (RQL)

Declarative query language for RDF description basesrelies on a typed data model (literal & container types + union types)follows a functional approach (basic queries and filters)adapts the functionality of XML query languages to RDF, but also:

treats properties as self-existent individualsexploits taxonomies of node and edge labels allows querying of schemas as semistructured data

Relational interpretation of schemas & resource descriptionsClasses (unary relations)Properties (binary relations)Containers (n-ary relations)


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A Cultural Community Resource Description Example

r2: museoreinasofia.mcu.es/guernica.jpg

r1:www.rodin.fr/thinker.gif

PortalSchema

PortalResourceDescriptions

ExtResource

last_modified title

StringDate

“oil on canvas”technique

exhibited

“Reina Sofia Museum”

title2000/06/09

last_modified

&r3

&r1

&r2

&r4

Artist

Sculptor

StringArtifact

Sculpture

Painting

sculpts

createsfname

lname

paints

StringMuseum

exhibited

techniqueStringPainter

paints

creates

&r5

&r6

fname

lname

lname

paints

“Pablo”

“Picasso”

“Rodin”

2000/01/02last_modified

r4:museoreinasofia.mcu.esr3:www.artchive.com/woman.jpg

Web Resources


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Querying Large RDF Schemas with RQL

Basic Class Queriestopclasssubclassof(Artist)subclassof^(Artist)superclassof(Painter)superclassof^(Painter)

Basic Property Queriestoppropertysubpropertyof(creates)subpropertyof^(creates)superpropertyof(paints)superpropertyof^(paints)domain(creates)range(creates)

Querying the RDF/S meta-schemaClassPropertyLiteral


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Class & Property Querying

Which classes can appear as domain and range of property creates select $X, $Y from {:$X}creates{:$Y} or

select X, Y from Class{X}, Class{Y}, {:X}creates{:Y}

Find all properties defined on class Painting and its superclasses

select @P, range(@P) from {:Painting}@P orselect P, range(P) from Property{P} where domain(P)>=Painting

Find the domain and range of the property creates

seq ( domain(creates), range(creates) ) while thanks to functional composition we can express

subclassof ( seq ( domain(creates), range(creates) ) [0] ) or select X from subclassof(seq(domain(creates), range(creates))[0]) {X}


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Schema Navigation using RQL

Iterate over the subclasses of class Artist

select $X from Artist{:$X} or select X from subclassof(Artist){X}

Find the ranges of the property exhibited which can be reached from a class in the range of property creates

select $Y, $Z from creates{:$Y}.exhibited{:$Z}

Find the properties that can be reached from a range class of property creates, as well as, their respective ranges

select * from creates{:$Y}.@P{:$$Z} orfrom Class{Y}, (Class union Literal){Z}, creates{:Y}.@P{:Z}


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Exporting Schemas using RQL Queries

Find Leaf Classes (i.e., classes without subclasses)

select C1 from Class{C1} where not ( C1 in (select C1 from Class{C2} where C2 < C1) )

Find all schema information (i.e., group related superclasses and properties for each class)

select C, superclassof^(C), (select P, range(P) from Property{P} where domain(P) = C) from Class{C}


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Querying Complex RDF Descriptions with RQL

Find all resources Resource

Find the resources in the extent of the property creates creates or

select * from {X}creates{Y}

Find the resources of type ExtResource and Sculpture ExtResource intersect Sculpture

ExtResource minus SculptureExtResource union Sculpture


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Navigating in Description Graphs using RQL

Find the Museum resources that have been modified after year 2000 (i.e., data path with node and edge labels)

select X from Museum{X}.last_modified{Y} where Y >= 2000-01-01

Find the resources that have been created and their respective titles (i.e., data path using only edge labels)

select X, Z from creates{Y}.title{Z}

Find the titles of exhibited resources that have been created by a Sculptor (i.e., multiple data paths)

select Z, W from Sculptor.creates{Y}.exhibited{Z}, {Z}title{W}


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Using Schema to Filter Resource Descriptions

Find the Painting resources that have been exhibited as well as the related target resources of type ExtResource (i.e., restrict multiply classified property target values using node labels)

select X, Y from {X:Painting}exhibited{Y}.ExtResource

Note the difference with the following path exression

select X, Y from {X:Painting}exhibited{Y:ExtResource}

Find modified resources which can be reached by a property applied to the class Painting and its subclasses (i.e., restrict property source values using edge labels)

select @P, Y, Z

from {:$X}@P.{Y}last_modified{Z}

where $X <=Painting


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Discover the Schema of RDF Descriptions

Find the description of a resource with URI “http://www.museum.es”select $X, (select @P, Y from {Z : $Z} @P {Y} where X = Z and $X = $Z)from $X {X} where X = &http://www.museum.es Find the descriptions of resources whose URI match “www.museum.es”select X, (select $W, (select @P, Y from {Z : $Z} @P {Y} where W = Z and $W = $Z) from $W {W} where W = X) from Resource {X} where X like "*www.museum.es*"


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And if you still like triples …

Find the description of resources which are not of type ExtResource

( (select X, @P, Y from {X} @P {Y}) union (select X, type, $X from $X {X}))minus( (select X, @P, Y from {X:ExtResource}@P{Y}) union (select X, type, ExtResource from ExtResource {X}))


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Storing RDF Descriptions: RSSDB Preliminary Performance Results


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Modeling the ODP Catalog with RDF/S

Class related

ns1: http://www.dmoz.org/topic.rdf

rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#rdfs: http://www.w3.org/2000/01/rdf-schema# typeOf(instance)

subClassOf(isA)attribution

Regional Recreation

Lodging

Vacation-Rentals

related

ns2: www.oclc.org/dublincore.rdfs

Ext.Resource

stringtitle

description

string

date

file_size

last_modifiedIle-de-France

Paris

Travel

Hotel Directories

Hotel

&r1 &r3&r2 &r4

title title title

Notre-Dame

HotelSiteofficielde DisneylandParis

Disneyland

Officialsiteof DisneylandParis

title

description description

Danube OrsaySunScale

&r1: http://www.sunscale.com/france/paris/index.htm


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ODP Statistics

ODP Version: 16-01-2001

170 Mbytes of class hierarchies

700 Mbytes of resource descriptions

337,085 topics

16 hierarchies with

max depth: 13 ( 6.86 on average)

max # subclasses: 314 ( 4.02 on average)

2,342,978 URIs


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Generic Representation

id: int1

uri: texthttp://www.dmoz.org/topics.rdfs#Hotel

Resources

3 http://www.oclc.org/dublincore.rdfs#title2 http://www.dmoz.org/topics.rdfs#Hotel Directories

9 r1

4 http://www.dmoz.org/schema.rdf#Ext.Resource

predid: int6

Triplessubid: int

2objid: int

15 3 75 1 8

objvalue: text

5 http://www.w3.org/1999/02/22-rdf-syntax-ns#type6 http://www.w3.org/2000/01/rdf-schema#subClassOf

7 http://www.w3.org/1999/02/22-rdf-syntax-ns#Property

5 9 2

8 http://www.w3.org/2000/01/rdf-schema#Class

3 9 SunScale


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Specific Representation

subid: int11

13

SubClass superid: int

1

12

subid: int16

SubPropertysuperid: int

1412 1

Namespace

Type

id: int11

rangeid: int4412

13

id:int1

uri: texthttp://www.w3.org/2000/01/rdf-schema#

3 http://www.oclc.org/dublincore.rdfs#4 http://www.dmoz.org/topics.rdfs#

id: int1

nsid: int1

lpart: textResource

2 2 Bag2 http://www.w3.org/1999/02/22-rdf-syntax-ns#3 2 Seq4 String

Classnsid: int

5lpart: text

Ext.Resource 1415

Propertynsid: int

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lpart: texttitledescription

domainid: int114 Hotel

4 Hotel Directories

id: int

16 5 title 11 4

subtable

t12

URI: textt1

source: textt15

target: text

URI: textr1

t11URI: text

r2

URI: textr1

t13r2

source: text target: text

source: textr1

t14target: text

SunScaler2 Pulitzer Opera

t16

classid: int11

1311

uri: textr1

r1

Instances

r2

r2 12


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DBMS Size vs. Schema Triples

DBMS size scales linearly with the number of schema triples

SpecRepr GenRepr

Aver. triple size (with indexes)

0.086 KB (0.1734 KB)

0.1582 KB (0.3062 KB )

Aver. triple storage time (with indexes)

0.0021 sec (0.0025) sec

0.0025 sec (0.0032 sec)


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DBMS Size vs. Data Triples

DBMS size scales linearly with the number of data triples

SpecRepr GenRepr

Aver. triple size (with indexes)

0.123 KB (0.2566 KB)

0.123 KB (0.2706 KB )

Aver. triple storage time (with indexes)

0.0033 sec (0.0043) sec

0.0039 sec (0.00457 sec)


63


Query Templates for RDF description bases

Pure schema queries

Q1 Find the range (or domain) of a property

Q2 Find the direct subclasses of a class

Q3 Find the transitive subclasses of a class

Q4 Check if a class is a subclass of another class

Queries on resource descriptions using available schema knowledge

Q5 Find the direct extent of a class (or property)

Q6 Find the transitive extent of a class (or property)

Q7 Find if a resource is an instance of a class

Q8 Find the resources having a property with a specific (or range of) value(s)

Q9 Find the instances of a class having a given property

Schema queries for specific resource descriptions

Q10 Find the properties of a resource and their values

Q11 Find the classes under which a resource is classified


64


Execution Time of RDF Benchmark Queries


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Comparison

Specific Representation permits the customization of the database representation of RDF metadata

Specific Representation outperforms the Generic Representation for all types of queries

Q1, Q2, Q5, Q7, Q10, Q11: by a factor up to 3.73Q3, Q4, Q6: by a factor up to 2.8Q8, Q9: by a factor up to 95,538

Generic representation pays severe penalty for maintaining large tables (Triples, Resources)

e.g., queries Q8, Q9 require (self-) joins of Triples, Resources


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Other Issues

RDF Metadata Generation from Legacy Repositories:need to capture schemas from heterogeneous resources

RDF Schema Evolution and Metadata Revision: to support the dynamics of resource descriptions

RDF Repositories Distribution:for integration with WebDAV or LDAP-like architectures

RDF Query Languages Optimization:for real-scale Semantic Web applications


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The ICS-FORTH R&D Activities on the Semantic Web


68


The C-Web Project

EC IST Project (13479) 1999-2000 Overall Aim: Set-up methodologies and

infrastructure for fast deployment and easy management of Web Portals for communities requiringeffective knowledge

assimilation,elicitationefficient query answering

Partners: INRIA(FR), FORTH(GR), EDW(IT)

Running Application Scenario: Learning

Portals for intranets or the InternetCorporate Knowledge Servers (e.g.,

automobile, telecommunications)Memory Organizations (e.g., museums,

libraries, archives)


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Project “MESMUSES”Programme:(IST) KAIII.1.4. Multimedia

Content and Tools (Access to digital collections of cultural and scientific content)

Contract: IST-2000-26074 (02/2001 – 07/2003)

Partners: INRIA (France),

FINSIEL - Multimedia Services (Italy),

ICS-FORTH (Hellas),

ENSTB - Ecole Nationale Supérieure des Télécommunications - Bretagne (France), VALORIS - Group, Paris (France)

IMSS - Istituto e Museo di Storia della Scienza, Firenze (Italy)

CSI - Cité des Sciences et de l'Industrie, Paris (France)

EDW International, Milano (Italy) DET-UNIFI - University of Florence (Italy)


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89


University Portals

Most of the Corporate Portal features apply to higher educationuPortal is bridging the gap between corporate portals and the

needs of Higher Education Institutions One of the most complex portal applications is instruction. Several

information channels have to be synchronized together to:present learning materials and assessmentsmonitor the learner’s progress and adapt the presentation to the

learner’s knowledgeaudit the progression through contentand perhaps even simulate a process


90


The Evolving Campus


91


The 21Century Campus in the .com World


92


The Higher Education Web World


93


uPortal Hierarchy


94


uPortal Interfaces

AuthenticationProving your identity

AuthorizationDeciding what you can access

Directory servicesSuch as populating

EduPerson User preferences

Profiles, structure, themes, skins

Channel informationAvailability and configuration

1 ICS-FORTH London 25/01/02 Christophides Vassilis On Community Web Portals and the Semantic Web: A Database Perspective Vassilis Christophides Computer.

Documents

knowledge management

crete slide

corporate communities

editor web portal slide

knowledge processes

new knowledge

portals market facts

semistructured web sites