A NEW APPROACH TO STORE LEARNING OBJECT METADATA!

A semantic learning object repository is a software system which stores educational resources and their metadata (or only the metadata), and provides some type of searching interface, to human or to others software systems. Repositories provide access to collections of educational resources, usually in an electronic format, al-though most of them don’t store educational resources themselves, just only their metadata. Therefore it is possible to find the same resource from different reposito-ries. The main functionality of a learning object repository is searching educational resources. It’s observed two wide kind of repositories:

1. Interactive searching interfaces, to be used by humans
2. Querying interfaces which can be used by software agents, for example, through web services.

Sometimes, one same way of searching can be used to both usages. Nevertheless, it must be noted than most usual general propose information retrieval mechanisms (Baeza-Yates & Ribeiro-Neto, 1999) (like Internet searching) must be complemented with a browsing metadata searching. The simplest way to do it is allowing metadata field searching. However, those interfaces sometimes are not satisfactory therefore the research is focused in currently advantages techniques that enable the knowledge use about a metadata domain, as the ontologies uses (described in the next sections).

Recent studies try unifying different learning object definitions (McGreal, 2004). These studies show that learning-oriented entities in a repository have a high variability on its characterizations. The non-existence of a common vocabulary, as well as the coexistence of different learning object definitions, point out the need of flexible repositories whose can fit all existent conceptualizations.

Formal ontology as a discipline (Welty & Guarino, 2001) is aimed at studying possibilia, so that it can be used to compare learning element representations according to the flexibility of their coverage, and term subsumption properties. In fact, ontological representations can play an important role as support for sound semantic models that fulfill a number of new requirements related to automation, such as search, retrieval or composition of new learning materials from others that already exist. The existence of ontology-based schemas becomes essential when some of the functions are to be delegated to automated or semi-automated systems, following the Semantic Web vision (Berners-Lee, Hendler & Lassila, 2001).

This documentation shows the progress of a research on course, which main goal is the design of the ontology schema in order to provide more flexibility into entities description of a learning object semantic repository, besides to be able to allow automated functions or tasks delegation to agents. The research project result on several contributions, and the most significant are:

- Semantic description of standard IEEE LOM metadata
- Resource description with several ontologies.
- Design of the SLOR core basic functions that enable a variety of ontological char-acterizations about learning object concept.
- Upgrade searching and browsing functions.
- Generalization of semantic repository concept.

Those contributions are the start point to others applications whose use the proposal technique.