Internal Area

Learning Objects, Metadata and Standard

In this work package, we focus on some of the key factors that impede more flexible, advanced and powerful uses of reusable learning objects. (We intentionally focus on some key factors, not all!)

One part of the work package is concerned with the actual development and roll-out of a global, trans-European infrastructure for federated search of learning objects and their introduction into repositories, documented in deliverable D4.2. In the context of this infrastructure, we developed the Simple Query Interface (SQI, documented in D4.1) to enable simple search in a federation of learning resource repositories. Furthermore, we developed the ALOCOM ontology for learning objects to simplify the reuse of learning resources, as demonstrated within the ALOCOM toolset.

Furthermore, we developed the abstract query language (named PROLEARN Query Language, PLQL) for learning repositories, documented in D4.6: The formalism is "abstract" so as to enable the "binding" to several query languages already developed within the Professional Learning community and PROLEARN. Such bindings are experimented in several PROLEARN prototypes, thus yielding experience for the consolidation of the PROLEARN query language proposal.

We also focus on aspects related to the insertion of new objects in the infrastructure that led to the development of the Simple Publishing Interface (SPI), documented in D4.8, now part of the CEN/ISSS workplan on standardization in this area. The automatic generation of metadata is a key aspect here. The automation of metadata has led to the development of the AMG (and now SamgI) framework for Automatic Metadata Generation. We therefore are able to integrate new sources of metadata, e.g. flashmeeting descriptions.

Our work on empirical evaluation of the usage of learning resources has led to the development of the Contextualized Attention Metadata (CAM) schema. Using CAM, metadata about learning resources can be enriched with specific usage metadata. Furthermore, the ideas of CAM are generalized into the "Snowflake" discussion.

In order to increase interoperability with repositories that have not been developed specifically for learning, we also investigate “semantic interoperability”, starting from work we did on the harmonization of the underlying abstract models for metadata standards like Dublin Core (DC) and Learning Object Metadata (LOM). See D4.7 and the Harmony discussions on harmonizing of metadata. Harmony involves a number of the key researchers in this domain and participants from standardization bodies like CEN/ISSS, in a cross-collaborative DC-LOM approach. All specifications are available online.

Another part of the WP is concerned with restructuring European (and global) research in this area, through the organization of a series of research seminars (LOMI seminars, documented in D4.5) that feed into the work on a research manifesto (Learning Object Manifesto, partly documented in D4.2 and the aforementioned "Snowflake" discussion.

All Learning Objects, Medatata and Standards deliverables can be downloaded here

Search for learning objects