Learning Object Repositories with Dynamically Reconfigurable Metadata Schemata
[ES] In this paper we describe a model of learning object repository in which users have full control on the metadata schemata. Thus, they can define new schemata and they can reconfigure existing ones in a collaborative fashion. As consequence, the repository must react to changes in schemata in a...
| Autores: | , , |
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| Formato: | capítulo de livro |
| Fecha de publicación: | 2016 |
| País: | España |
| Recursos: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/131558 |
| Acesso em linha: | http://hdl.handle.net/10366/131558 |
| Access Level: | acceso abierto |
| Palavra-chave: | Learning object repository Metadata schemata Dynamic reconfigurability Learning object indexing Browsing |
| Resumo: | [ES] In this paper we describe a model of learning object repository in which users have full control on the metadata schemata. Thus, they can define new schemata and they can reconfigure existing ones in a collaborative fashion. As consequence, the repository must react to changes in schemata in a dynamic and responsive way. Since schemata enable operations like navigation and search, dynamic reconfigurability requires clever indexing strategies, resilient to changes in these schemata. For this purpose, we have used conventional inverted indexing approaches and we have also devised a hierarchical clusteringbased indexing model. By using Clavy, a system for managing learning object repositories in the field of the Humanities, we provide some experimental results that show how the hierarchical clustering-based model can outperform the more conventional inverted indexes-based solutions. |
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