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Formal description and automatic generation of learning spaces based on ontologies

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Resumo:A good Learning Space (LS) should convey pertinent information to the visitors at the most adequate time and location to favor their knowledge acquisition. This statement justifies the relevance of virtual Learning Spaces. Considering the consolidation of the Internet and the improvement of the interaction, searching, and learning mechanisms, this work proposes a generic architecture, called CaVa, to create Virtual Learning Spaces building upon cultural institution documents. More precisely, the proposal is to automatically generate ontology-based virtual learning environments from document repositories. Thus, to impart relevant learning materials to the virtual LS, this proposal is based on using ontologies to represent the fundamental concepts and semantic relations in a user- and machine-understandable format. These concepts together with the data (extracted from the real documents) stored in a digital repository are displayed in a web-based LS that enables the visitors to use the available features and tools to learn about a specific domain. According to the approach here discussed, each desired virtual LS must be specified rigorously through a Domain-Specific Language (DSL), called CaVaDSL, designed and implemented in this work. Furthermore, a set of processors (generators) was developed. These generators have the duty, receiving a CaVaDSL specification as input, of transforming it into several web scripts to be recognized and rendered by a web browser, producing the final virtual LS. Aiming at validating the proposed architecture, three real case studies – (1) Emigration Documents belonging to Fafe’s Archive; (2) The prosopographical repository of the Fasti Ecclesiae Portugaliae project; and (3) Collection of life stories of the Museum of the Person – were used. These real scenarios are actually relevant as they promote the digital preservation and dissemination of Cultural Heritage, contributing to human welfare.
Autores principais:Martini, Ricardo Giuliani
Assunto:Ciências Naturais::Ciências da Computação e da Informação
Ano:2018
País:Portugal
Tipo de documento:tese de doutoramento
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

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