Linked Data for Visualizing and Retrieving RDA Relationships
DOI:
https://doi.org/10.15517/9dgwyf14Keywords:
RDA relationships, linked data, grafo de conocimientosAbstract
This study proposes a theoretical-practical methodology for applying linked data to the visualization and retrieval of relationships defined by RDA (Resource Description and Access), using Pedro Páramo by Juan Rulfo as a case study. It is based on the premise that, although RDA and the IFLA Library Reference Model (LRM) provide a solid conceptual framework for representing bibliographic entities and relationships, their potential remains limited in traditional systems based on linear formats such as MARC21.The methodology is structured in five phases: selection of a corpus of MARC21 records, including editions, translations, and adaptations of the work; transformation of data into RDF using OpenRefine and vocabularies such as the RDA Registry, SKOS, and schema.org; construction of a knowledge graph in Neo4j with typed nodes and relationships; execution of Cypher queries to explore translations, manifestations, thematic links, and adaptations; and evaluation of navigability and semantic retrieval in comparison with traditional catalogs. The results show that the knowledge graph enhances the visualization and analysis of complex relationships, enabling the identification of connections not easily detectable in conventional systems. The explicit semantic representation improves both the precision and completeness of information retrieval. Additionally, the model proves to be replicable across other bibliographic corpora and aligns with Semantic Web principles, supporting interoperability and data reuse. Key challenges include data normalization, technical training, and scalability when handling large volumes of information.
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