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Abstract
mythLOD dataset is the result of the reengineering process of Mythologiae collection (https://mythologiae.unibo.it/), transforming it from a conventional tabular format (CSV format) into a knowledge graph (RDF format). The mythLOD knowledge graph served online along with its technical documentation, catalogue visualisation and a storytelling experiment to encourage exploration and reuse. Specifically, mythLOD preserves the artwork’s descriptive metadata and a set of interpretations performed by the scholars. Each interpretation identifies a mythological theme or scene depicted in an artwork of the collection and associates a curated set of literary references that convey the same theme. The dataset, in RDF format, contains 4260 heterogeneous artefacts, their descriptive metadata and the scholars’ interpretations using Nanopublications and Named Graphs.
Abstract
mythLOD dataset is the result of the reengineering process of Mythologiae collection (https://mythologiae.unibo.it/), transforming it from a conventional tabular format (CSV format) into a knowledge graph (RDF format). The mythLOD knowledge graph served online along with its technical documentation, catalogue visualisation and a storytelling experiment to encourage exploration and reuse. Specifically, mythLOD preserves the artwork’s descriptive metadata and a set of interpretations performed by the scholars. Each interpretation identifies a mythological theme or scene depicted in an artwork of the collection and associates a curated set of literary references that convey the same theme. The dataset, in RDF format, contains 4260 heterogeneous artefacts, their descriptive metadata and the scholars’ interpretations using Nanopublications and Named Graphs.
Tipologia del documento
Dataset
Autori
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
07 Feb 2024 15:39
Ultima modifica
12 Feb 2024 13:02
Risorse collegate
Nome del Progetto
Programma di finanziamento
MIUR - PON Ricerca e Innovazione 2014-2020 (CCI: 2014IT16M2OP005)
URI
Altri metadati
Tipologia del documento
Dataset
Autori
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
07 Feb 2024 15:39
Ultima modifica
12 Feb 2024 13:02
Risorse collegate
Nome del Progetto
Programma di finanziamento
MIUR - PON Ricerca e Innovazione 2014-2020 (CCI: 2014IT16M2OP005)
URI
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