Vasyl Oleksiuk
https://orcid.org/0000-0003-2206-8447
Oleh Spirin
https://orcid.org/0000-0002-9594-6602
Kateryna Osadcha
https://orcid.org/0000-0003-0653-6423
A STANDARDISATION MODEL OF FAIR DATA FOR EDUCATIONAL SCIENCES
Full text (pdf)
Language: Ukrainian
Abstract. The growing volume of digital information in scientific and pedagogical research underscores the urgent need for its preservation, indexing, and exchange. The aim of this article is to develop and theoretically substantiate a standardisation model for research data in educational sciences, in accordance with the international principles of findability, accessibility, interoperability, and reusability, collectively known as FAIR data. This study briefly examines international experience in implementing Open Science projects and identifies the specific features of research data within the field of educational sciences. Consequently, an original model was designed, comprising goal-oriented, content-related, procedural, and outcomes-based components. Within the content block, a taxonomy of educational data is developed, data presentation formats are described, and the structure of a standard FAIR data package is proposed. Furthermore, the procedural component of the model outlines the ethical standards mandatory for dataset compilation, the procedures for generating these data, and the infrastructural elements required for their storage. Particular attention is given to the outcomes-based component, for which a system of criteria and indicators has been established to evaluate the compliance of educational research data with FAIR principles. A scale is proposed to classify datasets into four levels of maturity: insufficient, basic, sufficient, and high. The conclusion demonstrates that implementing the developed model and indicator system ensures a transition from the declarative application of Open Science principles to a measurable and technologically integrated data management lifecycle. The implementation of the designed model will enhance the transparency, quality, and reproducibility of educational research.
Keywords: FAIR principles, research data, educational sciences, data taxonomy, metadata, standardisation, criteria and indicators.
https://doi.org/10.32987/2617-8532-2026-2-91-103
Keywords: FAIR principles, research data, educational sciences, data taxonomy, metadata, standardisation, criteria and indicators.
https://doi.org/10.32987/2617-8532-2026-2-91-103
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8. Verkhovna Rada of Ukraine. (2010). On the protection of personal data (Act No. 2297-VI, June 1). Retrieved from https://zakon.rada.gov.ua/laws/show/2297-17#Text [in Ukrainian]
9. Brandt, O., Gauza, H., Kaltenbach, J., Müller, M. E., Schneider, G., & Zinn, C. (2024). A Minimal Metadata Schema and Its Tool to Improve the Searchableness of Research Data in Bioinformatics. Journal of Library Metadata, 24(3), 165-188. DOI: https://doi.org/10.1080/19386389.2024.2338314.
10. Devare, M., Aubert, C., Benites Alfaro, O. E., Perez Masias, I. O., & Laporte, M.-A. (2021). AgroFIMS: A Tool to Enable Digital Collection of Standards-Compliant FAIR Data. Frontiers in Sustainable Food Systems, 5, 726646. DOI: https://doi.org/10.3389/fsufs.2021.726646.
11. Provost, L., Bezuidenhout, L., Venkataraman, S., van der Lek, I., van Gelder, C., Kuchma, I., …& Braukmann, R. (2024). Towards FAIRification of learning resources and catalogues – lessons learnt from research communities. Frontiers in Education, 9, 1390444. DOI: https://doi.org/10.3389/feduc.2024.1390444.
12. NAUKA (n. d). FAIR principles for research data. Retrieved from https://nauka.gov.ua/information/pryntsypy-fair-dlia-doslidnytskykh-danykh [in Ukrainian].
13. Oleksiuk, V., Habrusiev, V., & Balyk, A. (2011). Some aspects of integration of web services of a higher educational institution. Scientific notes of the Volodymyr Hnatyuk Ternopil National Pedagogical University. Series: Pedagogy, 1, 228-234 [in Ukrainian].
Received March 10, 2026
Accepted May 14, 2026
Published May 28, 2026
Accepted May 14, 2026
Published May 28, 2026
