Global vs. Community Metadata Standards: Empowering Users for Knowledge Exchange

Abstract

The idea of knowledge sharing has strong roots in the education process. With the current development of the technology and moving learning material into the web environment it acquired a new dimension. Learning objects are the chunks of knowledge shared by e-learning community. Organizations and individuals are building repositories of learning objects and annotate them with metadata to describe their educational values and standardization efforts are on the way to provide a franca lingua for the educators. In this paper we describe the peer-to-peer infrastructure for sharing learning object we are building in Canada. The POOL projects builds on the three types of nodes: SPLASH is an freely downloadable application which allows individuals to create metadata and maintain their collection of learning objects, PONDs are bigger repositories of learning objects connected to the peer-to-peer network and POOL centrals increase the speed and breadth of the searches in the peer-to-peer network. The POOL project uses CanCore - a subset of the IMS metadata protocol - to describe learning objects. In the second part of the paper we discuss the future direction of this initiative based on the maturing learning objects community and lessons learned in the deployment of POOL network. We argue that the standardization effort, although very important, currently provides solutions that are too complex. We see the communities where the knowledge is shared to be the main force in the creation of the metadata standards which would support the growth of semantic web. The implications of moving the responsibility for schemas and metadata creation on communities poses new requirements on interoperability and tools. We describe those requirements and we outline approach we are developing to address them.KeywordsLearning ObjectActive ElementMetadata StandardMetadata SchemaMetadata RecordThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.