WP1: Content Federation and Content Maintenance Infrastructure

Main Objectives

The main objective of WP1 is to enable the re-use, enrichment and internationalization of management related content from open content repositories. Based on the OpenScout application profile, the customized technical infrastructure will be set up as a web service oriented architecture that strongly uses internationally accepted standards like WSDL, SOAP, SQI, OAI-PMH, OSIDs, XML, XQuery, SQL, etc.

Analysis of Federation Infrastructures and Development of Integrated Application Profiles

In working group WP1 we analyzed the state-of-the-art technologies, infrastructures and data modeling options to build OpenScout upon. Our choices are based on the study of general background and the lessons learned from past projects. Additionally we describe the actual OpenScout infrastructure and the OpenScout application profile. Following is a brief summary of the main results of the analysis and implementation outcomes of this task.

Architectural Design for Searching Repositories

Harvest Pattern

OpenScout uses harvest patterns for searching repositories. The harvesting approach can give clients search access to OpenScout repositories that only support harvesting and don't offer search interfaces. Another argument for using the harvest pattern is that the system architects are free to decide which query languages the metadata store will provide to the source applications and what technology to use to implement searching.

Learning Object Data Models

LOM, the Learning Object Metadata (IEEE 1484.12.1 – 2002 Standard), describes resources using a set of more than 70 attributes, divided into these nine categories:

• General
• Lifecycle
• Meta-Metadata
• Technical
• Educational
• Rights
• Relation
• Annotation
• Classification

The descriptors are organized in a tree-like structure under these categories. This tree makes it possible to organize the information in a consistent way, grouping information into related pieces. The LOM schema is thus based on a recursive container model. Additionally, LOM is gradually becoming the reference standard for educational systems managing learning objects of many kinds, besides that it is one of most important standard for Interoperability [10]. Also, LOM is part of SCORM which is the standard to package learning resources; it is used by most LMS and consequently it is a de facto standard. OpenScout therefore has to support LOM.

OpenScout infrastructure and services

The different layers of the architecture in the OpenScout approach are exposed in the Figure below. Based on a shared technical infrastructure for federated access to the repositories, metadata harvesting and content enrichment, web services for metadata manipulation and retrieval and metadata-based content access will be provided. The approach aims to make the learning objects in all repositories jointly searchable and retrievable.

Services in OpenScout connect the presentation layer with data sources. They process user queries and return results, handle user management and provide means for gathering and manipulating metadata. Some services provide simple functions while others are more complex and can even aggregate functionality. Besides metadata and content retrieval, OpenScout services will allow users to annotate contents with own metadata, track activities and generate metadata from user actions. To ensure full interoperability, all services will be based on open standards, such as OAI-PMH for metadata harvesting and SOAP for remote web service connectivity. The search service is enabled through the Simple Query Interface (SQI) in order to be able for OpenScout to join Learning Object Repositories (LOR) federations like Globe and Ariadne.

Content Metadata Harvester

The harvesting component is the foundation of the OpenScout effort. Harvesting means to crawl and to analyze content metadata of Learning Objects (LO) from different Learning Object Repositories (LOR) and store it in a centralized repository (based on the Open Archive Initiative Protocol for Managing Harvesting OAI-PMH). This is not a one-time import action, it is an event repeatedly in a regular basis or triggered by updates. Once harvested, the LO is described through an application profile described by LOM standard. The result of the harvesting processes provides a centralized repository for all repositories and means to uniformly query and retrieve the learning objects.

Federated Infrastructure Services

Through the Web Portal component in WP1, OpenScout provides content access services for end-users, for example basic key-word search, to access the contents. The search operation is conducted on top of the centralized metadata repositories. In addition to keyword-based search, end-users may also able to access the contents via navigation. In addition to providing services to end-users, OpenScout also enables developers inside (e.g. the connector component described in D5.1) or outside the OpenScout consortium to access the federated infrastructure. This is necessary for different reasons. For example, this service helps existing LCMSs access the federated contents, enlarge their repositories and thus benefit their users. Also, this service increases the impact of OpenScout and makes OpenScout open contents visible to boarder audiences.

Conclusion

OpenScout uses harvest patterns for searching repositories. Also we use OAI-PMH to gather distributed content metadata and build our content federation. After demonstrating the OpenScout federated infrastructure and metadata harvesting process, we described centralized content access services to both end-users and developers. Currently these results can be seen and tested through through the OpenScout portal.

All public WP 1 deliverables are available here.