Abstract
In this paper, we present a review on the use of ontologies in learning object repositories systems for searching and suggestion purposes, considering its adoption for the seaThings project that aims to promote the ocean literacy. We also describe the use case of the Cognix system and Agent-based Learning Objects - OBAA metadata standard for learning objects which is being implemented on a new learning objects repository. This system includes concepts from artificial intelligence such as agents and ontologies that aim to improve the search and so making the system more responsive. This paper also sugests how an ontology can be implemented, using metadata in learning object repositories to provide relevant aspects, such as interoperability, reuse, and searching.
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Acknowledgements
This work is financed by the FEDER in 85% and by regional funds in 15%, through the Operational Program Azores 2020, within the scope of the SEA-THINGS Learning Objects to Promote Ocean Literacy project ACORES-01-0145-FEDER-000110. This study was also financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
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Behr, A. et al. (2021). Enhancing Learning Object Repositories with Ontologies. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies. WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1368. Springer, Cham. https://doi.org/10.1007/978-3-030-72654-6_44
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