The Role of E-Vocabularies in the Description and Retrieval of Digital Educational Resources

Vocabularies are linguistic resources that make it possible to access knowledge through words. They can constitute a mechanism to identify, describe, explore, and access all the digital resources with informational content pertaining to a specific knowledge domain. In this regard, they play a key role as systems for the representation and organization of knowledge in environments in which content is created and used in a collaborative and free manner, as is the case of social wikis and blogs on the Internet or educational content in e-learning environments. In e-learning environments, electronic vocabularies (e-vocabularies) constitute a mechanism for conceptual representation of digital educational resources. They enable human and software agents either to locate and interpret resource content in large digital repositories, including the web, or to use them (vocabularies) as an educational resource by itself to learn a discipline terminology. This review article describes what e-vocabularies are, what they are like, how they are used, how they work, and what they contribute to the retrieval of digital educational resources. The goal is to contribute to a clearer view of the concepts which we regard as crucial to understand e-vocabularies and their use in the field of e-learning to describe and retrieve digital educational resources

Automatic domain-specific learning: towards a methodology for ontology enrichment

[EN] At the current rate of technological development, in a world where enormous amount of data are constantly created and in which the Internet is used as the primary means for information exchange, there exists a need for tools that help processing, analyzing and using that information. However, while the growth of information poses many opportunities for social and scientific advance, it has also highlighted the difficulties of extracting meaningful patterns from massive data. Ontologies have been claimed to play a major role in the processing of large-scale data, as they serve as universal models of knowledge representation, and are being studied as possible solutions to this. This paper presents a method for the automatic expansion of ontologies based on corpus and terminological data exploitation. The proposed ¿ontology enrichment method¿ (OEM) consists of a sequence of tasks aimed at classifying an input keyword automatically under its corresponding node within a target ontology. Results prove that the method can be successfully applied for the automatic classification of specialized units into a reference ontology.Financial support for this research has been provided by the DGI, Spanish Ministry of Education and Science, grant FFI2011-29798-C0201.Ureña Gómez-Moreno, P.; Mestre-Mestre, EM. (2017). Automatic domain-specific learning: towards a methodology for ontology enrichment. LFE. Revista de Lenguas para Fines Específicos. 23(2):63-85. http://hdl.handle.net/10251/148357S638523

Localizing Ontologies in OWL

This paper presents a model for linguistic/terminological information, which can be used in tandem with an ontological model, in order to link lexicalizations and concepts. The main aim of the proposed model is to provide multilingual information to ontologies. Interoperability with existing standard models of terminological description as well as access to authoritative linguistic resources are crucial aspects that have been considered in the design of the proposed model

Reuse of terminological resources for efficient ontological engineering in Life Sciences

This paper is intended to explore how to use terminological resources for ontology engineering. Nowadays there are several biomedical ontologies describing overlapping domains, but there is not a clear correspondence between the concepts that are supposed to be equivalent or just similar. These resources are quite precious but their integration and further development are expensive. Terminologies may support the ontological development in several stages of the lifecycle of the ontology; e.g. ontology integration. In this paper we investigate the use of terminological resources during the ontology lifecycle. We claim that the proper creation and use of a shared thesaurus is a cornerstone for the successful application of the Semantic Web technology within life sciences. Moreover, we have applied our approach to a real scenario, the Health-e-Child (HeC) project, and we have evaluated the impact of filtering and re-organizing several resources. As a result, we have created a reference thesaurus for this project, named HeCTh