Proposta metodológica para avaliar o enriquecimento semântico de objetos publicados no linked data

Abstract

Linked Data is a set of principles proposed by Tim Berners Lee, whose purpose is to facilitate the publication and connection of data from different sources in the Semantic Web. Currently, several data models are developed with the purpose of semantic enrichment of this data for publication in Linked Data, thus ensuring the interoperability and integration of information from different providers. The present article aims to present a methodology proposal to evaluate the semantic enrichment of objects published on the web through Linked Data, using a Matrix of Techniques and Resources for the Semantic Enrichment of Objects - Matrix TRESO developed during the master 's research in Science of Information. The developed matrix was applied in the BIBFRAME and EDM data models to verify how these models performed the semantic enrichment of objects during the publication in Linked Data. A comparative analysis was carried out through which it was possible to identify the model most closely adhering to the criteria of the TRESO Matrix, as well as to propose recommendations for semantic enrichment.