Digital architecture of information governance for education and research in Ukraine

Abstract

The article substantiates information governance as an integrated mechanism for enhancing the quality, resilience, and innovation capacity of education and research in the context of digital transformation, war-related risks, and European integration. The target of research is to define the concept and scope of information governance, identify systemic problems in the use of education and research data, and develop a practical model for transforming such data into evidence-based governance decisions. The methodological framework comprises systemic, comparative, analytical-synthetic, and institutional approaches. Based on data from Eurostat, Eurydice, the ITU, the OECD, the Ministry of Education and Science of Ukraine, the State Statistics Service of Ukraine, UNESCO, and the World Bank Group, the study analyses trends in digital accessibility, the development of education information systems, R&D funding, open science, the use of artificial intelligence, and the impact of the war on the development of education and research infrastructure in Ukraine. The findings indicate that Ukraine has a relatively high level of digital coverage and has established key elements of an integrated education and research information ecosystem. However, their effectiveness is constrained by data fragmentation, which contributes to inadequate metadata quality and digital inequality, alongside cybersecurity threats, risks to academic integrity, and weak linkages among R&D statistics, R&D funding, and actual research outcomes. A four-domain information governance model encompassing data, analytics, decisions, and outcomes is proposed. The practical significance of this model lies in its potential application by public authorities, educational and research institutions, local communities, and international partners for evidence-based planning, monitoring, and adjustment of education, research, investment, and innovation policies. Simultaneously, implementing this model requires the creation of a unified education and research data architecture incorporating integrated analytical dashboards, FAIR data and open science policies, data literacy development programmes, results-based financing mechanisms, responsible use of artificial intelligence, and regular audits of data quality and cyber resilience.