Evaluating the FAIRness of Scientific Data Repositories

Evaluation of FAIRness of scientific data repositories is a growing concern. FAIRness means making data compatible with FAIR data principles (M. D. Wilkinson, “The FAIR Guiding Principles for scientific data management and stewardship,” Sci Data, vol. 3, no. 1, p. 160018, Mar. 2016, https://doi.org/10.1038/sdata.2016.18 ). These principles guide how research data is published to be “findable,” “accessible,” “interoperable,” and “reusable,” not only by humans but also by machines. Although Libras (stands for “Brazilian Sign Language) is considered the second official language in Brazil, storing and teaching technical-scientific terms to deaf students is still challenging, mainly due to the plurality of signs used for the same scientific quantity. Inclusive teaching requires teachers or interpreters to adopt STEM signs. Digital platforms have been created that contribute to the teaching-learning process at different levels of education for deaf people. However, as highlighted by Williams (“‘Chapter 12: Disability, Universal Design, and the Digital Humanities | George H. Williams’ in ‘Debates in the Digital Humanities’ on Debates in the DH Manifold,” Debates in the Digital Humanities, 2012. https://dhdebates.gc.cuny.edu/read/untitled-88c11800-9446-469b-a3be-3fdb36bfbd1e/section/2a59a6fe-3e93-43ae-a42f-1b26d1b4becc#ch12 (accessed Sep. 22, 2021) and Pletsch et al. (“Apresentação—Inclusão Digital e Acessibilidade: Desafios da educação contemporânea,” Revista Docência e Cibercultura, vol. 4, no. 1, Art. no. 1, Apr. 2020, https://doi.org/10.12957/redoc.2020.50573 ), there are still few studies that combine Digital Humanities (DH), Educational Accessibility, and Digital Inclusion. Although DH is interdisciplinary and closely associated with the social sciences and uses software and data corpora to study social problems, there are still gaps in DH when planning to support or assess whether its professionals can meet user needs with hearing loss. The main contribution of this work is to present the repository evaluation process for updating the main functionalities of the RECLibras platform and evaluating the FAIRness of its descriptors and Libras signs according to the FAIR data principles. We developed a semiautomatic method to evaluate the FAIRness of scientific data repositories using three FAIRification tools. Our experiments considered the repository of RECLibras. The findings contribute to their development and provide information on how to evaluate the FAIRness of other scientific data repositories such as (Cruz et al. “OpenSoils: Uma Plataforma de Apoio à Ciência do Solo,” Nov. 2019; Da Cruz et al., “Towards an e-infrastructure for Open Science in Soils Security,” in Anais do Brazilian e-Science Workshop (BreSci), Sociedade Brasileira de Computação—SBC, Jul. 2018. https://doi.org/10.5753/bresci.2018.3273 ), to name a few. By making data and metadata more discoverable and accessible to humans and machines, this study can serve as a model for the development of other digital platforms to support users with hearing acuity challenges.