Abstract
It is introduced a platform for quality control and monitoring of Cuban scientific publications named Sceiba. To this end, it needs to collect scientific publications comprehensively at the national level. Metadata quality is crucial for Sceiba interoperability and development. This paper exposes how metadata quality is assured and enhanced in Sceiba. The metadata aggregation pipeline is worked out to collect, transform, store and expose metadata on Persons, Organizations, Sources, and Scientific Publications. Raw data transformation into Sceiba’s internal metadata models includes cleaning, disambiguation, deduplication, entity linking, validation, standardization, and enrichment using a semi-automated approach aligned with the findability, accessibility, interoperability, and reusability principles. To meet the requirements of metadata quality in Sceiba, a three-layer structure for metadata is used, including 1) discovery metadata, which allows the discovery of relevant scientific publications by browsing or query, 2) contextual metadata, which allows a) rich information on persons, organizations and other aspects associated with publications, b) interoperation among common metadata formats used in Current Research Information Systems, journals systems or Institutional Repositories; 3) detailed metadata, which is specific to the domain of scientific publication evaluation. The example provided shows how the metadata quality is improved in the Identification System for Cuban Research Organizations, one of Sceiba´s component applications.
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Notes
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Vlaamse Interuniversitaire Raad - Universitaire Ontwikkelingssamenwerking’ (VLIR-UOS), more information about the project can be found in https://www.vliruos.be/en/projects/project/22?pid=4202.
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Sceiba is a word that arises from the combination of the Latin ‘‘sci’’ and Ceiba, a leafy tree considered sacred by several Cuban traditions.
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Acknowledgements
The work of the Sceiba project was supported by the ‘Vlaamse Interuniversitaire Raad - Universitaire Ontwikkelingssamenwerking’ (VLIR-UOS), Belgium. The authors are team members of the Sceiba project. They like to thank Sadia Van Cauwenbergh (Hasselt University) and Raf Guns (Antwerp University) for their suggestions on the article and to the Sceiba team of the University of Pinar del Rio for their contribution to the development of the Sceiba platform.
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Arencibia, E., Martinez, R., Marti-Lahera, Y., Goovaerts, M. (2022). On Metadata Quality in Sceiba, a Platform for Quality Control and Monitoring of Cuban Scientific Publications. In: Garoufallou, E., Ovalle-Perandones, MA., Vlachidis, A. (eds) Metadata and Semantic Research. MTSR 2021. Communications in Computer and Information Science, vol 1537. Springer, Cham. https://doi.org/10.1007/978-3-030-98876-0_9
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