Realizing Interoperability of E-Learning Repositories Daniel Olmedilla L3S Research Center / Hannover University Universidad Autónoma de Madrid - PhD Defense

Realizing Interoperabilityof E-Learning Repositories

Daniel OlmedillaL3S Research Center / Hannover University

Universidad Autónoma de Madrid - PhD Defense24th May 2007

May 24th, 2007UAM PhD Defense 2Daniel Olmedilla

Outline

Introduction and Motivation Interoperability: what is it and why is it

needed? Common Query Interface Common Metadata Schema Ranking Successful Interoperability

Demonstrations Conclusions & Open Issues


Outline

Introduction and Motivation Interoperability: what is it and why is it Interoperability: what is it and why is it

needed?needed? Common Query InterfaceCommon Query Interface Common Metadata SchemaCommon Metadata Schema RankingRanking Successful Interoperability Successful Interoperability

DemonstrationsDemonstrations Conclusions & Open IssuesConclusions & Open Issues


IntroductionSimple Motivation Scenario (I)

Simple Scenario:

Alice is interested in learning about Windows and would like to attend a lecture about it this year


IntroductionSimple Motivation Scenario (& II)


IntroductionSearch Engine Limitations

Unstructured information and lack of semantics

Size and coverage of the Web Hidden Web (also Deep Web) Personalized Ranking


IntroductionOther Approaches: Coalitions

Repositories interconnected Lack of standards, ad-hoc solutions Individual agreement required to join

Approaches Replication

Loose control over data sometimes undesirable

Federated Search Lack of standards costly


IntroductionOther Approaches: P2P Networks

Advantages Scalability No single point of failure Control remains with owners Dynamicity

Disadvantages Decrease on performance Ad-hoc interfaces lack of

interoperability


IntroductionA bit More Complex Motivation Scenario

Alice is a consultant and she has been asked to lead a project starting in two months. Now she needs to retrieve courses in order to refresh and improve her previous

knowledge on project management get some basic knowledge about

accounting and auditing practice her advanced level of English


IntroductionProblem Statement

Lack of standards and appropriate integration solutions prevent users from easily and effectively finding relevant resources to their needs


Outline

Introduction and MotivationIntroduction and Motivation Interoperability: what is it and why is it

needed? Definition Why Interoperability? Challenges to achieve it

Common Query InterfaceCommon Query Interface Common Metadata SchemaCommon Metadata Schema RankingRanking Successful Interoperability DemonstrationsSuccessful Interoperability Demonstrations Conclusions & Open IssuesConclusions & Open Issues


Interoperability: What and Why? What is it?

Summary from existing definitions:

Ability of working together to accomplish a common task

Work in conjunction Exchange of information and USE it Provided at different levels Without increasing the effort of the user

[Concise Oxford Dictionary, NISO, IEEE: Standard Computer Dictionary, DMReview, Whatis.com]


Interoperability: What and Why? Interoperability encompasses …

Technical Interoperability Semantic Interoperability Political Interoperability Inter-community Interoperability Legal Interoperability International Interoperability


Interoperability: What and Why? Investment in Technology

ICT Gobally $1,45 trillion

annually

Technology in Europe €6,4 billion in 2004 Increasing (10%

more than previous year)

[Money for Growth, The European Technology Investment Report 2005. PricewaterhouseCoopers Report, Jun. 2005]


Interoperability: What and Why? Key Technological Issues (I)

38 industry associations in 27 different countries

The most significant technology issues … included Integration (21%) Standards (20%)

[International Survey of E-Commerce. World Information Technology and Services Alliance (WITSA), 2000]


Interoperability: What and Why? Key Technological Issues (& II)

[International Survey of E-Commerce. World Information Technology and Services Alliance (WITSA), 2000]


Interoperability: What and Why? Interoperability Inhibited by Cost

“Although interoperability is a significant strategic direction, it is often inhibited by

cost”

[Survey: Integration costs still hamper agility. Computerworld Today, February 2006]


Interoperability: What and Why? User Effectiveness: Some Facts

User Effectiveness Knowledge workers spend from 15% to 35%

of their time searching for information Searchers are successful in finding what

they seek 50% of the time or less

Total Lost not finding the right information:

estimated among $2.5 to $3.5 million per year for an enterprise with 1000 knowledge workers

opportunity cost: potential additional revenue of $15 million annually

[Feldman. The high cost of not finding information. IDC White Paper & KMWorld Magazine, 2004]


Interoperability: What and Why? Challenges to achieve it

CommonCommunication

Interface

CommonQuery

Language

CommonMetadataSchema

Ranking


Interoperability: What and Why? E-Learning Study Analysis: Technical Requirements

Training-life-cycle in companies across Europe Retrieving learning services from a wide

variety of providers Search heuristics Metadata queries Matching skill gaps with learning service

selections Matching personal development gaps

with learning services

[Gunnarsdottir. User Trials – Evaluation Report. EU IST ELENA Deliverable, May 2005]


Outline

Introduction and MotivationIntroduction and Motivation Interoperability: what is it and why is it Interoperability: what is it and why is it

needed?needed? Common Query Interface

Simple Query Interface Opening P2P to the rest of the World

Common Metadata SchemaCommon Metadata Schema RankingRanking Successful Interoperability DemonstrationsSuccessful Interoperability Demonstrations Conclusions & Open IssuesConclusions & Open Issues


Common Communication Interface Simple Query Interface (SQI)

Simple but Highly flexible: targets different interoperability scenarios

Official CEN/ISSS Workshop Agreement since October 2006

Listed by IMS on Query Services

Widely adopted in E-Learning community


Common Communication Interface Simple Query Interface: Design Issues

Independent of query language, result format and vocabularies

Complex information sources may be queried (e.g., P2P networks) Synchronous and asynchronous

Support for Lightweight implementations Stateful and stateless

Access-control and search separation Easy extensibility


Common Communication Interface Simple Query Interface: Session Management

Authentication/authorization are requirements

Independent of the search interface

Separation is managed via sessions session createAnonymousSession () session createSession (user, passwd) destroySession (sessionId)

Other different methods are allowed (e.g., based on credentials or trust negotiations)


Common Communication Interface Traditional Access Control in Decentralized Systems

Assumption: I already know you---you have a local account!

Not a member?


Common Communication Interface Trust Negotiation: Features

Trust is based on parties’ properties

Every party can define access control policies to control outsiders’ access to their sensitive resources

Establish trust iteratively and bilaterally by the disclosure of certificates and by requests for certificates


Common Communication Interface Trust Negotiation: Example

Step 1: Alice requests a service from Bob

Step 5: Alice discloses her VISA card credential

Step 4: Bob discloses his BBB credential

Step 6: Bob grants access to the serviceService

BobAlice

Step 2: Bob discloses his policy for the service

Step 3: Alice discloses her policy for VISA


Common Communication Interface Simple Query Interface: Query (I)


Common Communication Interface Simple Query Interface: Query (& II)


Common Communication Interface P2P Proxying Architecture

User

Provider

SQI ConsumerProxy

SQI ProviderProxy

Provider

Provider

Provider

User

External Provider

SQI ProviderProxy

External Provider

Web Service SQI

Web Service SQI

Web Service SQI

Web Service SQI

EDUTELLA NETWORK

[Brunkhorst, Olmedilla. Interoperability for peer-to-peer networks: Opening P2P to the rest of the World. EC-TEL, Oct 2006]


Outline


needed?needed? Common Query InterfaceCommon Query Interface Common Metadata Schema

Learning Resource Schema Competence Modeling

RankingRanking Successful Interoperability DemonstrationsSuccessful Interoperability Demonstrations Conclusions & Open IssuesConclusions & Open Issues


Common Metadata SchemaSimple Learning Resource Schema


Common Metadata SchemaComplex Learning Resource Schema


Common Metadata SchemaCompetence Requirements

Excerpt extracted from a newspaper Complete Master’s Degree (any faculty) Expert knowledge in Java J2EE, Servlets,

JSP) Very good IT English and / or Spanish

Drawbacks Does not indicate what is mandatory or

optional It is not machine-understandable


Common Metadata SchemaCompetence Definition

“an effective performance within a domain / context at different levels of proficiency”

Example: Competency “English Language”, Level “Advanced”, Context ”Computer Science”

Competence

ProficiencyLevel

Context

Competency


Common Metadata SchemaCompetency

We use IEEE RCD to represent a Competency

Uniquely identify an isolated competency

Enriched with human-readable titles and descriptions

Metadata

-RCD Schema Version-Additional Metadata

-RCD Schema

Statement

-Token

-Name-Text

-IdDefinition

-Model Source

RCD

-Description-Title

-Statements

1..*

0..1

0..1

Competence

ProficiencyLevel

Context

Competency


Common Metadata SchemaProficiency Level

Reusable scales of totally ordered proficiency levels

Each level is identified by an ID, a human-readable label and an optional mapping to a numerical domain

Proficiency Level

-Universal Scale Mapping [0..1]-LabelProficiency Scale

Ordered list

-levels

1..*

Competence

ProficiencyLevel

Context

Competency


Common Metadata SchemaContext

“... the interlaced conditions in which something exists or occurs”

Competences might be interpreted differently in a different context

Context are defined in tree-like hierarchies Easier to model and to handle Simpler algorithms, no cycle detection necessary May optionally link to additional ontologies

Context

-Label -subClassOf

0..1

Competence

ProficiencyLevel

Context

Competency


Aggregate Competence

-Sequenced : boolean = false

SimpleCompetence

Competence

-NameRCD

-RCD Ref-parts

2..*

-Prof Level Ref

Proficiency Level

Alternative Competence

-minNumber : Integer = 1-maxNumber : Integer

Composite Competence

Global Identifier

-Catalogue-Entry

Context

-alternatives

2..*

-Context Ref

-identifier

1

Common Metadata SchemaCompetence

Links to the dimensions objects High degree of

reusability Better support for gap

analysis

Competences can be simple or composed of other (arbitrary nested) competences Aggregation Set Selection

Competence

ProficiencyLevel

Context

Competency


Common Metadata SchemaA bit More Complex Motivation Scenario (Revisited)

Alice is a consultant and she has been asked to lead a project starting in two months. Now she needs to retrieve courses in order to refresh and improve her previous

knowledge on project management get some basic knowledge about

accounting and auditing practice her advanced level of English


Outline


needed?needed? Common Query InterfaceCommon Query Interface Common Metadata SchemaCommon Metadata Schema Ranking

Link-based Personalized Ranking Platform

Successful Interoperability Successful Interoperability DemonstrationsDemonstrations

Conclusions & Open IssuesConclusions & Open Issues


RankingPageRank

Page score based on the link structure of the web

It measures page popularity page i pointing to page j means vote from i to j The more backlinks a page has, the more important it is Sum of the ranks of the backlinks

It has a personalization vector

Computationally expensive: not possible to make the whole computation for each user


RankingPersonalized PageRank

Hubs: pages pointing to many important pages

Compute one Personalized PageRank Vector for each user (PPV)

Challenges:- Reduce storage required- Reduce time for computation

Each PPV corresponding to a Preference Set P can be expressed as a linear combination of Basis Hub Vector

Decomposes each Basis Hub Vector in two parts: Hub skeleton vector (common interrelationships and precomputed) Partial vector (unique values and computed at construction-time)


RankingPersonalized PageRank Limitations

Personalization relies on user’s ability to choose a good Preference Set High quality hubs which match his

preferences

This process can be automated: Information collected from the user can

be used to derive his Preference Set

User does not even need to know what is a hub


RankingA Personalized Ranking Platform (I)

Personalization relies on user’s ability to choose a good Preference Set High quality hubs which match his

preferences

This process can be automated: Information collected from the user can

be used to derive his Preference Set

User does not even need to know what is a hub


RankingA Personalized Ranking Platform (II)

User’s interests are determined by Most surfed pages User’s bookmarks

We get a set of pages from the user but They are not highly ranked hubs

HubFinder is an algorithm to find related web pages It allows pluggable filtering mechanisms

We use HubRank to find highly rated hubs related to a given initial set of pages

User web pages set of related highly rated hubs


SearchEngine

Crawler

Proxy

Crawl the WebComputescores

Extractbookmarks

User surfsin Internet

Tracksurfed pages

Search EngineIndex

User's BrowserUser's Browser

Hubrank scores

User’s bookmarks

Most surfedpages

Bookmarksrelated Hubs

Preferenceset

Surfed pagesrelated Hubs

User’sHub Set

Hubfinde

rH

ubfinder

UserUser queries

the search engine

RankingA Personalized Ranking Platform (& III)


RankingSelected Example (I)

Crawl with 3,000,000 web pages

30 bookmarks 15 on architecture 7 on traveling 6 on software 2 on sports

78 selected surfed pages

Computed 1300 pages as hub set


RankingSelected Example (II)

Query Keywords

PageRank PPR PROS

Rel.

P.Rel.

Irrel.

Rel.

P.Rel. Irrel.

Rel. P.Rel. Irrel.

architecture

5 3 2 3 7 0 8 2 0

building 3 2 5 2 3 5 4 1 5

Paris 6 0 4 2 3 5 6 2 2

park 6 0 4 8 0 2 10 0 0

surf 3 0 7 4 2 4 7 2 1

Total 23 5 22 19 15 16 35 7 8


RankingSelected Example (& III)


Outline


needed?needed? Common Query InterfaceCommon Query Interface Common Metadata SchemaCommon Metadata Schema RankingRanking Successful Interoperability Demonstrations

HCD-Online: Advanced Network Search Bringing Learning Repositories to a Global Network Knowledge Resource Sharing for a Life Long

Learning Infrastructure Conclusions & Open IssuesConclusions & Open Issues


Successful Interoperability DemonstrationsHCD-Online: Advanced Network Search


Successful Interoperability DemonstrationsPROLEARN & GLOBE


Successful Interoperability DemonstrationsTENCompetence, MACE, MELT, …

... Lobster Flickr YouTubeAriadneLionshare

Wrapper Wrapper WrapperWrapper

FederatedSearch Engine

Search Publishing

InformationSource Registry

Information Source Mgmt.

UserDatabase

User Mgmt.Rating

ClientClient

INFORMATION SOURCE LAYER

SERVICE LAYER

CLIENT LAYER

LionsharePeer at DesktopGUI

Taste


Outline


needed?needed? Common Query InterfaceCommon Query Interface Common Metadata SchemaCommon Metadata Schema RankingRanking Successful Interoperability Successful Interoperability

DemonstrationsDemonstrations Conclusions & Open Issues


Conclusions & Further WorkConclusions

Interoperability is a key technological issue

Lack of standards and integration solutions reusability prevent users from finding the information they need


Conclusions & Further WorkMain contributions (I)

1. Identification of Requirements for system interoperability

2. Specification and Standardization of Simple Query Interface

3. SQI-based open-source components for easy adoption by information providers

4. Proxying architecture for distributed environments such as P2P networks

5. Data models and ontologies for semantic representation of learning objects and competences

6. Semantic integration based on query rewriting mechanisms

7. New personalized ranking algorithms for linked and unlinked corpus

8. Proof of concept integrated prototypes

9. Demonstration of interoperability achievement through several networks and projects world wide


Conclusions & Further WorkMain Contributions (& II)

The contributions of this presentation (and more in the

written thesis) provides small steps towards achieving interoperability


Conclusions & Further WorkFurther Work

Interfaces for other services than search (e.g., publishing)

More research on flexible query languages (e.g., PLQL)

Development and Evolution of schemas

Adaptation, optimization and improvement of ranking algorithms


Questions?

[email protected] - http://www.L3S.de/~olmedilla/

Thanks!

Documents

Realizing Interoperability of E-Learning Repositories Daniel Olmedilla L3S Research Center / Hannover University Universidad Autónoma de Madrid - PhD Defense