Realizing Interoperability of E-Learning Repositories

1. Realizing Interoperabilityof E-Learning Repositories Daniel Olmedilla L3S Research Center / Hannover University Universidad Autónoma de Madrid - PhD Defense 24th May 2007

2. 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 UAM PhD Defense

3. 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 UAM PhD Defense

4. IntroductionSimple Motivation Scenario (I) • Simple Scenario: • Alice is interested in learning about Windows and would like to attend a lecture about it this year UAM PhD Defense

5. IntroductionSimple Motivation Scenario (& II) UAM PhD Defense

6. IntroductionSearch Engine Limitations • Unstructured information and lack of semantics • Size and coverage of the Web • Hidden Web (also Deep Web) • Personalized Ranking UAM PhD Defense

7. 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 UAM PhD Defense

8. 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 UAM PhD Defense

9. 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 UAM PhD Defense

10. IntroductionProblem Statement • Lack of standards and appropriate integration solutions prevent users from easily and effectively finding relevant resources to their needs UAM PhD Defense

11. Outline • Introduction and Motivation • Interoperability: what is it and why is it needed? • Definition • Why Interoperability? • Challenges to achieve it • Common Query Interface • Common Metadata Schema • Ranking • Successful Interoperability Demonstrations • Conclusions & Open Issues UAM PhD Defense

12. 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] UAM PhD Defense

13. Interoperability: What and Why? Interoperability encompasses … • Technical Interoperability • Semantic Interoperability • Political Interoperability • Inter-community Interoperability • Legal Interoperability • International Interoperability UAM PhD Defense

14. 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] UAM PhD Defense

15. 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] UAM PhD Defense

16. Interoperability: What and Why? Key Technological Issues (& II) • [International Survey of E-Commerce. World Information Technology and Services Alliance (WITSA), 2000] UAM PhD Defense

17. 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] UAM PhD Defense

18. 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] UAM PhD Defense

19. Interoperability: What and Why? Challenges to achieve it UAM PhD Defense

20. 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] UAM PhD Defense

21. Outline • Introduction and Motivation • Interoperability: what is it and why is it needed? • Common Query Interface • Simple Query Interface • Opening P2P to the rest of the World • Common Metadata Schema • Ranking • Successful Interoperability Demonstrations • Conclusions & Open Issues UAM PhD Defense

22. 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 UAM PhD Defense

23. 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 UAM PhD Defense

24. 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) UAM PhD Defense

25. Not a member? Common Communication Interface Traditional Access Control in Decentralized Systems • Assumption: I already know you---you have a local account! UAM PhD Defense

26. 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 UAM PhD Defense

27. Step 1: Alice requests a service from Bob Step 2: Bob discloses his policy for the service Step 3: Alice discloses her policy for VISA Step 4: Bob discloses his BBB credential Step 5: Alice discloses her VISA card credential Step 6: Bob grants access to the service Service Common Communication Interface Trust Negotiation: Example Alice Bob UAM PhD Defense

28. Common Communication Interface Simple Query Interface: Query (I) UAM PhD Defense

29. Common Communication Interface Simple Query Interface: Query (& II) UAM PhD Defense

30. Common Communication Interface P2P Proxying Architecture • [Brunkhorst, Olmedilla. Interoperability for peer-to-peer networks: Opening P2P to the rest of the World. EC-TEL, Oct 2006] UAM PhD Defense

31. Outline • Introduction and Motivation • Interoperability: what is it and why is it needed? • Common Query Interface • Common Metadata Schema • Learning Resource Schema • Competence Modeling • Ranking • Successful Interoperability Demonstrations • Conclusions & Open Issues UAM PhD Defense

32. Common Metadata SchemaSimple Learning Resource Schema UAM PhD Defense

33. Common Metadata SchemaComplex Learning Resource Schema UAM PhD Defense

34. 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 UAM PhD Defense

35. 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” UAM PhD Defense

36. We use IEEE RCD to represent a Competency Uniquely identify an isolated competency Enriched with human-readable titles and descriptions Common Metadata SchemaCompetency UAM PhD Defense

37. 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 Common Metadata SchemaProficiency Level UAM PhD Defense

38. “... 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 Common Metadata SchemaContext UAM PhD Defense

39. 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 UAM PhD Defense

40. 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 UAM PhD Defense

41. Outline • Introduction and Motivation • Interoperability: what is it and why is it needed? • Common Query Interface • Common Metadata Schema • Ranking • Link-based Personalized Ranking Platform • Successful Interoperability Demonstrations • Conclusions & Open Issues UAM PhD Defense

42. 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 UAM PhD Defense

43. 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) UAM PhD Defense

44. 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 UAM PhD Defense

45. 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 UAM PhD Defense

46. 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 UAM PhD Defense

47. RankingA Personalized Ranking Platform (& III) UAM PhD Defense

48. 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 UAM PhD Defense

49. RankingSelected Example (II) UAM PhD Defense

50. RankingSelected Example (& III) UAM PhD Defense