Paving the Way for Enriched Metadata of Linguistic Linked Data

Tracking #: 2697-3911

This paper is currently under review
Authors: 
Maria Pia di Buono1
Hugo Gonçalo Oliveira
Verginica Barbu Mititelu
Blerina Spahiu
Gennaro Nolano

Responsible editor: 
Guest Editors Advancements in Linguistics Linked Data 2021

Submission type: 
Full Paper
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 those efforts, the achievement of full compatibility for metadata in linguistic resource production is still far from being reached. On the other hand, 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 a descriptive schema, suitable for easing the accessibility and interoperability of such resources.
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Under Review