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Paving the Way for Enriched Metadata of Linguistic Linked Data

Articolo
Data di Pubblicazione:
2022
Abstract:
The need for reusable, interoperable, and interlinked linguistic resources in Natural Language Processing downstream tasks has been proved by the increasing efforts to develop standards and metadata suitable to represent several layers of information. Nevertheless, despite these efforts, the achievement of full compatibility for metadata in linguistic resource production is still far from being reached. Access to resources observing these standards is hindered either by (i) lack of or incomplete information, (ii) inconsistent ways of coding their metadata, and (iii) lack of maintenance. In this paper, we offer a quantitative and qualitative analysis of descriptive metadata and resources availability of two main metadata repositories: LOD Cloud and Annohub. Furthermore, we introduce a metadata enrichment, which aims at improving resource information, and a metadata alignment to META-SHARE ontology, suitable for easing the accessibility and interoperability of such resources.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Linguistic linked open data, metadata enrichment, metashare, Annohub, LOD Cloud
Elenco autori:
di Buono, Maria Pia; Gonçalo Oliveira, Hugo; Barbu Mititelu, Verginica; Spahiu, Blerina; Nolano, Gennaro
Autori di Ateneo:
di Buono Maria Pia
Link alla scheda completa:
https://unora.unior.it/handle/11574/202045
Pubblicato in:
SEMANTIC WEB
Journal
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