Behavioral analytics as FAIR impact proxies: a longitudinal study of Digital Library NAES of Ukraine (2012-2025)

- Kilchenko, Alla V. (orcid.org/0000-0003-2699-1722), Ivanova, Svitlana M. (orcid.org/0000-0002-3613-9202), Novytska, Tetiana L. (orcid.org/0000-0003-2591-5218) and Shynenko, Mykola A. (orcid.org/0000-0001-6697-747X) (2026) Behavioral analytics as FAIR impact proxies: a longitudinal study of Digital Library NAES of Ukraine (2012-2025) CTE Workshop Proceedings, 1 (13). pp. 189-205. ISSN 2833-5473

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Abstract

This longitudinal study analyzes fourteen years (2012-2025) of web analytics data from the Digital Library of the National Academy of Educational Sciences (NAES) of Ukraine to develop proxy indicators for monitoring the behavioral impact of FAIR-aligned repository design. Using Google Analytics metrics across three platform generations (Classic Analytics, Universal Analytics, and Google Analytics 4), we propose a conceptual mapping between behavioral metrics and FAIR principles while acknowledging significant limitations. The dataset encompasses 1.34 million active users in 2025, with traffic source analysis revealing sustained direct access patterns (86.6%) alongside declining organic search visibility (3.7%). Geographic distribution shows substantial international reach with 183 countries accessing resources, though the dominant share from non-Ukrainian sources (particularly China at 57.0%) raises questions about potential automated traffic. Device analysis demonstrates desktop dominance (94.6%) with limited mobile adoption (5.3%). The study identifies distinct phases: establishment (2012-2014), acceleration (2015-2021), and maturation (2022-2025), including crisis periods (COVID-19 pandemic, 2022 invasion). We propose a Key Performance Indicator framework using web analytics as proxy indicators for FAIR impact assessment, explicitly distinguishing between behavioral metrics and intrinsic FAIR compliance. This approach provides repository administrators with practical monitoring tools while recognizing the gap between usage patterns and data quality attributes.

Item Type:	Article
Keywords:	FAIR data, Google Analytics 4, digital library, web analytics, longitudinal study, Open Science, Ukraine, scientific data management
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 001 Science and knowledge in general. Organization of intellectual work > 001.8 Methodology > 001.89 Organization of science and scientific work Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.01/.08 Special auxiliary subdivision for computing Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 Application-oriented computer-based techniques Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 37.01/.09 Special auxiliary table for theory, principles, methods and organization of education
Divisions:	Institute for Digitalisation of Education > Department of Open Education and Scientific Information Systems
Depositing User:	науковий співробітник Алла Віленівна Кільченко
Date Deposited:	27 Apr 2026 20:32
Last Modified:	27 Apr 2026 20:41
URI:	https://lib.iitta.gov.ua/id/eprint/748981

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