Article: Semantic interoperability model for learning object repositories Journal: International Journal of Metadata, Semantics and Ontologies (IJMSO) 2023 Vol.16 No.2 pp.172 - 186 Abstract: Interoperability among repositories requires syntactic and semantic compatibility, achieved through the adoption of metadata standards. However, different learning object repositories currently use diverse metadata standards to describe their resources, so multiple metadata standards describe the same term, and vice versa. This paper proposes an ontology-based interoperability model, featuring a shared vocabulary (SV) and a set of matching rules. The SV establishes a common terminology for learning objects, while the matching rules enable translation between the SV and any metadata standard. As a result, both deposit and search for learning objects can be conducted using any metadata standard, thanks to the rules that ensure seamless translations where needed. To evaluate the proposed model, a prototype has been developed, which implements the SV and matching rules. This experience has shown that using ontologies and matching rules to provide an interoperability model for learning objects repositories is a valid, flexible and user-friendly solution. Inderscience Publishers - linking academia, business and industry through research

Title: Semantic interoperability model for learning object repositories

Authors: Valeria Celeste Sandobal Verón; Mariel Alejandra Ale; María de los Milagros Gutiérrez

Addresses: Engineering Education Research Group, Resistencia Regional Faculty, National Technological University, Resistencia, Chaco, Argentina ' Centre for Research and Development in Information Systems Engineering, Santa Fe Regional Faculty, National Technological University, Santa Fe, Argentina ' Centre for Research and Development in Information Systems Engineering, Santa Fe Regional Faculty, National Technological University, Santa Fe, Argentina

Abstract: Interoperability among repositories requires syntactic and semantic compatibility, achieved through the adoption of metadata standards. However, different learning object repositories currently use diverse metadata standards to describe their resources, so multiple metadata standards describe the same term, and vice versa. This paper proposes an ontology-based interoperability model, featuring a shared vocabulary (SV) and a set of matching rules. The SV establishes a common terminology for learning objects, while the matching rules enable translation between the SV and any metadata standard. As a result, both deposit and search for learning objects can be conducted using any metadata standard, thanks to the rules that ensure seamless translations where needed. To evaluate the proposed model, a prototype has been developed, which implements the SV and matching rules. This experience has shown that using ontologies and matching rules to provide an interoperability model for learning objects repositories is a valid, flexible and user-friendly solution.

Keywords: semantic interoperability; learning object repositories; metadata standards; open.

DOI: 10.1504/IJMSO.2023.135334

International Journal of Metadata, Semantics and Ontologies, 2023 Vol.16 No.2, pp.172 - 186

Accepted: 12 Mar 2023
Published online: 05 Dec 2023 *

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Title: Semantic interoperability model for learning object repositories

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