A model for the creation of human-generated metadata within communities

This paper considers situations for which detailed metadata descriptions of learning resources are necessary, and focuses on human generation of such metadata. It describes a model which facilitates human production of good quality metadata by the development and use of structured vocabularies. Using examples, this model is applied to single and multiple communities of metadata creators. The approach for transferring vocabularies across communities is related to similar work on the use of ontologies to support the development of the semantic web. Notable conclusions from this work are the need to encourage collaboration between the metadata specialists, content authors and system designers, and the scope for using accurate and consistent metadata created for one context in another context by producing descriptions of the relationships between those contexts

Human-Generated Learning Object Metadata

The paper examines how to address the need for a production process for e-learning resources to include human generated metadata, and considers how users will exploit this metadata. It identifies situations in which human production of metadata is unavoidable, and examines fundamental problems concerned with human metadata generation such as motivation and shared understanding. It proposes and discusses some methods to exploit endemic motivational factors within communities in an attempt to ensure good quality human generated metadata, and identifies how ontological constructs can support the exploitation of such metadata. The relevance of these methods to the semantic web in general is discussed