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Open Knowledge Initiative Phillip D. Long Senior Strategist for the Academic Computing Enterprise Massachusetts Institute of Technology eLearning Standards Business Stakeholder’s Group Feb. 3, 2003
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The Problem
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Universities and other institutions are building: Boutique customized learning tools
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The Problem Universities and other institutions are building: Boutique customized learning tools Trying to implement commercial learning systems (VLE/LMS) across heterogeneous learning domains
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The Problem Universities and other institutions are building: Boutique customized learning tools Trying to implement commercial learning systems (VLE/LMS) across heterogeneous learning domains On top of divergent underlying enterprise infrastructures
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It’s not working
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1 st Generation Technology Course Mgmt Content Mgmt Assessment Etc... Software for Teaching and For Learning AuthN AuthZ DBMSFileGUID Log Etc... Digital Libraries Browser Environments Simulations Remote Devices
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2 nd Generation Technology Course Mgmt Content Mgmt Assessment Etc... Software for Teaching and For Learning AuthNAuthZDBMSFileGUIDLogEtc... Digital Libraries Browser Environments Simulations Remote Devices Enterprise Services
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Assumptions Things Change –New Services & Functions –Method of Accessing Services –More Central Software Services Authorization, Calendaring, etc. –Evolving Systems Definitions – Protocols and transport layers will evolve
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More Assumptions Enterprises have different technologies Enterprise systems will use different technologies Need for sharing will grow Agreement beyond APIs needed for interoperability (vocabularies, metadata, etc)
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Goals of Interoperability What do we mean by Interoperability? First -
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Goals of Interoperability Data Synchronization Enterprise Integration Tool/UI Integration Application Portability Programming Language Integration Inter-Enterprise Resource Sharing
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OKI Addressing Data Synchronization Enterprise Integration Tool/UI Integration Application Portability Language Integration Inter-Enterprise Resource Sharing Etc…
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Dimensions of Interoperability Data Definitions Technology Choices UI/Application Frameworks Service Definitions
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Dimensions of Interoperability Service Data UI Tech Gov.CorpHESchool
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Open Knowledge Initiative Service Data UI Tech Gov.Corp.H.E.School J
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Data Specifications IMS/1.X Enterprise Application A Enterprise Application B Data
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OKI in a Nutshell An Application Before O.K.I. An Application After O.K.I.
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Tool and Implementation Portability
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The API Approach API are interfaces only, not implementations Code reuse Could achieve real-time integration Clean separation or boundaries Facilitates changes by minimizing impact
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Common Service Level APIs Allows integration with enterprise services Adapts to multiple standards Allows several sites to share services Independence from changing technology
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Service Based Architecture public class Factory implements org.okip.service.Example.api.Factory { private static final blah blah bhal private static final yada yada yada } … Example API … org.okip.service.shared.api.Thing things = myFactory.getSomething(); if (null != thingss) { for (int i = 0; things.length != i; i++) { out.println(things[i]); System.err.println(types[i]); } } … User Application Implementation Infrastructure Service
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OKI Services Course MgmtContent MgmtAssessment AuthN Etc… LocalIdFileDBCAuthZHierarchy User Messaging LoggingEtc… Shared Objects Educational Service APIs Common Service APIs Educational Service Implementations Common Service Implementations Educational Software “MLE” Institutional Infrastructure
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Core Institutional Partners Cambridge University Dartmouth College MIT North Carolina State University Stanford University University of Michigan University of Pennsylvania University of Wisconsin
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Core OKI Deliverables Service specifications/APIs –13 “Common Services” –3 “Educational Services” Reference implementations Exemplar applications (including “MLE/LMS”) Sustainability strategy
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O.K.I. Service Definition Process 0.2 0.9 1.0 draft
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Common Service API Status Authentication Authorization DBC Logging LocalID Shared Filing Hierarchy Localization Group User Messaging Scheduling Workflow 0.9 – Public 0.9 0.5
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Educational Service API Activity Class Admin –Student Information Systems Integration –Approaching 0.9 Digital Repository –Digital Library Community Engagement –Approaching 0.9 Assessment
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OKI Application Activity LMS’s –Stellar – MIT –CourseWork – Stanford University –CHEF – University of Michigan –OnCourse II – Indiana University (with CHEF) Client Demo Apps –Filing Demo – MIT –Hierarchy Demo – MIT –User Messaging Demo – MIT –Digital Repository and Class Admin Management Apps – MIT Digital Library Systems –DSpace – MIT –Fedora –University of Virginia/Tufts University Educational Tool Development –VUE Concept Mapping Tool – Tufts University –Assessment Components – Stanford University –SCORM Player – University of Cambridge
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The Service Definition Sweet Spot Too ConcreteToo Abstract Protocol and Data Model Choices Defined “Java” “Perl”
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O.K.I. Abstraction and Bindings Abstract Service Definition Emitters Java Interfaces Documentation Other…
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Phase 2Phase 1 OKI General TimeLine Jan 01Jan 02Jan 03Jan 04Jan 05Jan 06 Initial Core Service DevelopmentFurther Spec. Dev. – “Institute” Ref. Implementations Applications Developer Community Coordination/Support Core Service Maintenance/Evolution Adopter Engagement Vendor Engagement Grant Funded OKI App Activity
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Data and Functional Specifications Data standards serve two goals –Data exchange inter/intra enterprise Functional specifications define behavior Both are needed Agreed upon standards allows parallel development –Above the line - in learning apps –Below the line - in enterprise technologies
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An Example
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OKI Content Repository API What functions do “Learning Systems” need from content repositories? How can we complement existing data specifications? Allow for a single “System of record” for an asset
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Many Repositories IDC iMac I BM Remote Local IDC Institutional
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Content Repository Goals Allow for reuse of assets Allow the definition of assets to be preserved & extended. Easy & flexible search & access Allow for organization & classification of assets Maintain authorship & IP information Allow for inheritance
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Learning Use Assumptions A learning system might use more than one content repository A Learning System needs to store many types of assets for local use User software tools shouldn’t care if assets are local or remote User software tools shouldn’t care about protocols or transport
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Many Protocols IDC iMac I BM IDC SOAP Z39.50 V2 HTML Z39.50 File System OAI Remote Local Institutional
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Asset Assumptions Assets can contain other assets There are many types of assets Assets may be references There will be different metadata structures required for different asset types Assets types might share sets of attributes definitions Assets might share sets of attributes
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Content Repositories Assumptions Content repositories store and retrieve assets and information about those assets (metadata structure and values). A content repository may store permanent or temporary assets Determines asset types managed Determines metadata required for particular asset types Determines the search functionality supported Content repositories have other functions not addressed
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What is the work ahead? Decomposition
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What is the work ahead? Finding the right boundaries
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What is the work ahead? Engaging in a process, not selecting an end state
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What is the work ahead? Learning as a science –Apply formalism to describe behavior
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The End & The Beginning longpd@mit.edu
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