8th Sakai Conference

4-7 December 2007Newport Beach

OPEN-CLE: Sakai Integration OPEN-CLE: Sakai Integration with federated repositorieswith federated repositories

Angela Rabuck

Mustansar Mehmood, Carlos Solis

Rice University

OutlineOutline

• Introduction• IBM SUR Grant• Federated searching

– Connexions

– DSpace• Building “Collections”• Next Steps • Summary

Project OverviewProject Overview• Objectives:

– Develop a model for the integration of federated open source repositories

– Central instructional workspace– Use existing Rice repositories and instructional

collaboration systems– Base development on existing IBM technologies

and infrastructures

SUR GrantSUR Grant• IBM Shared University Research (SUR)

Grant– Open-standards-based– Service oriented architecture – IBM Enterprise Bus Product Suite– Loosely coupled

Project GoalsProject Goals• Help education institutions loosely tie

together open source applications• Explore development of Open

Standards using Bus Architecture• Allow flexibility when choosing

applications• Better utilization of current shared

resources

Federated RepositoriesFederated Repositories

• Sakai projects– Sakaibrary– Twin Peaks– O.K.I. Repository interfaces (OSIDs)

• Want to do more than search and select– Build learning collections

• Course specific• Ad-hoc

– Instructor added comments

Currently at RiceCurrently at Rice

• Sakai - production ~1.5 years• MDID - “pilot”; production Fall 2008• DSpace - “pilot”• Connexions - since 1998 • ExTemplate - since 1999• Etc . . .

ExTemplate ExTemplate • Developed by Rice University• Specifically designed for language

instruction• Create a variety of interactive multimedia

exercises and tests• Multiple choice, true/false, fill in the blank,

short answer, essay questions, and speaking• Use Wimba voice recording or Flash Media Server Plug-in to

assess speaking• Languages: Arabic, Chinese, French, German, Hebrew, Hindi,

Italian, Japanese, Korean, Polish, Portuguese, Russian, Tibetan, and Spanish

• http://lang.rice.edu/extemplate/index.htm

Current Rice Workspaces and RepositoriesCurrent Rice Workspaces and Repositories

DSpaceSakai

Connexions

MDID

ExTemplateEtc . . .

GoalGoal

DSpaceConnexion

sMDID

ExTemplate Etc . . .

Sakai

Use CaseUse Case

(Hub)

“Repository”“Repository”

“Repository”“Repository”

Why?Why?

• Lessons and more already built in Connexions• Other departments on campus’ work

– Ex. Art History scanned in 50,000+ images– DSpace archives

• Known, trusted sources• Easily find relevant course related materials • Broad base of available materials• Find things that you didn’t know existed

SearchSearch

Search ResultsSearch Results

Search ResultsSearch Results

Why separate?Why separate?

• No priority received from search results• Extremely diverse results in each area• Allows instructors to choose which types of

materials they are looking for

Have searches, now what?Have searches, now what?

• Search multiple repositories • Integrated into Sakai • What do we do with the results now?

– Tell the students to run the search using specific keywords?

– Save information – Tell the students why they should read it

DiagramDiagram

Use “Insert Chart…” from the Insert menu to create a chart in PowerPoint (it can import data from Excel). Otherwise, you can use a dedicated graphing or charting application, save the chart as a TIFF or PDF file, and insert the resulting image file as a Picture (Insert>Picture>From File…).

CachingIntegrationNotificationSecurity

Process Management

Logging Scheduler Workflow

IBM WebSphere Application Server

Provider for Connexions

Provider forD-Space

Provider For MDID

D-Space MDID

IBM WebSphere Application Server

Repository ‘X’

Provider for Repository ‘X’

Internet

Connexions

Rice Open CLE

Sakai Presence API

Sakai Mail API

Sakai Course API

Sakai User API

Sakai Authentication API

Sakai Authorization API

Sakai Site API

Sakai Learning and Collaboration System

IBM Enterprise Service Bus

Mediator

Process Choreographer Service

Registry

Database

ArchitectureArchitecture

DemoDemo

Demo

Initial ScreenInitial Screen

Create CollectionCreate Collection

SearchSearch

Adding ContentAdding Content

Adding ContentAdding Content

AnnotateAnnotate

Student View - Initial ScreenStudent View - Initial Screen

Title Release Date End DateAutomata 10/11/2006 07/21/2007 Java ME 12/12/2007 04/12/2007Search Theory 02/05/2007 03/01/2007

Student ViewStudent View

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Automata

Automata are abstract mathematical models of machines that perform computations on an input by moving through a series of states or configurations. If the computation of an automaton reaches an accepting configuration it accepts that input. At each stage of the computation, a transition function determines the next configuration on the basis of a finite portion of the present configuration. Turing machines are the most general automata. They consist of a finite set of states. Since Turing machines can leave symbols on their tape at the end of the computation, they can be viewed as computing functions: the partial recursive functions. Despite the simplicity of these automata, any algorithm that can be implemented on a computer can be modeled by some Turing machine.

Description

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What is a Broadband Network? This module explains about broadband networks, an entity to be considered in future Telecommunication Networks..

Network Information Theory: Multi-Access and Broadcast ChannelsThis is a brief summary of what has been known about network information theory. It covers multi access and broadcast channels, in an attempt to summarize about two dozen scattered papers in both subjects.

What is the role of teletraffic engineering in broadband networks?

In communications, a technique for transmitting a large amount of information, including voice, data, and video, over long distances.

Network information theory is the study of reliable communication in a network setting, where there are many sources and users who wish to communicate with one another.

Teletraffic engineers use their basic knowledge of statistics, the nature of traffic, their practical models, their measurements and simulations to make predictions and to plan telecommunication networks at minimum total cost

Next

Automata

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In a previous work we have analyzed a family of antibody and B-cell network models (basic AB models) of the immune system. This analysis focused principally on the physiological interpretation of their parameters. Our approach consisted in building a detailed and general mathematical model (referred to as the GIB model) and then simplifying it formally to a version (named the RIB model) that belongs to the family of AB models, but which is more general than the basic AB models. From that study it was clear that some of the assumptions necessary to simplify the GIB model into the RIB one, as well as to recover the basic AB models from the RIB one,

are quite unrealistic from physiological point of view All this raised the issue of the reliability, or even the heuristic value, of theoretical studies based on current network models for experimental immunologists. One approach to clarify this issue is to ask whether the unrealism of the assumptions implicit in the RIB and AB models entails qualitatively different behaviors between them compared to the GIB one. We initiate here such a work by performing a comparative study of a two-clone system of the AB and RIB models, and a variant of the GIB model in which the different molecular compartments were merged into a single one (labeled IGB model). Because all those models rely critically on certain B-cell activation functions, which constitute the core of an implicit model of individual B-cell reactivity or "local rules", we focused the present numerical study, to a great extent, on two parameters determining those activation functions (Hill coefficient and thresholds). Our results indicate that: (1) the RIB and IGB models display in general a much larger diversity of steady states than the AB models; (2) only under a very restricted parameter regime did all studied models behave similarly; (3) the parameter regime under which the AB and IGB models, but not the RIB one, behave similarly is still rather restricted through not as much as in (2); and (4) even relatively small quantitative changes (within reasonable values) in the postulated "local rules" can induce very large quantitative changes in the behavior of the AB and RIB models but not the IGB model. In the light of the present results, we discuss the need of postulating a set of "local rules" solidly based on experimental evidence as a necessary condition for the reliability of current network models.

Next Steps

Automata

Examples of UseExamples of Use

• Instructor chosen materials for student use• Resource finder for student projects• Combined content/bibliography for

collaborators• Assemble “collections”

””Possible” future featuresPossible” future features• User definable repository priority weighting• Favorites

– keywords– results

• Personal resource repository searching in MyWorkspace• Packaging (Import/Export)• Ability to add/replace repositories easily• Link directly to known repository item• “Freeze” resources• Printable pdf• Drag and drop functionality• Cross system publishing

What’s next?What’s next?

• More databases in federated search– MDID

• Library resources– eReserves– JSTOR– Shibboleth

• Instructional Design Component– User friendly way to create content

SummarySummary

• Loosely coupling open source products• Exploring Open Standards using Bus

Architecture• Sakai (CMS) - Hub• Other systems as repositories

– DSpace– Connexions– Etc

• Create learning “collections” with instructor annotations

ThanksThanks

• IBM Shared University Research (SUR) Program

• IBM WebSphere Teams in Dallas and Houston, TX

Contact InformationContact Information

• Want more information, have ideas, comments, etc:

• Angela Rabuck

adehart@rice.edu• Mustansar Mehmood

mm3@rice.edu• Carlos Solis

solis@rice.edu