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

Alla V. Kilchenko; Svitlana M. Ivanova; Tetiana L. Novytska; Mykola A. Shynenko

doi:10.55056/cte.1211

Автор(и)

Alla V. Kilchenko Institute for Digitalisation of Education of the NAES of Ukraine https://orcid.org/0000-0003-2699-1722
Svitlana M. Ivanova Institute for Digitalisation of Education of the NAES of Ukraine https://orcid.org/0000-0002-3613-9202
Tetiana L. Novytska Institute for Digitalisation of Education of the NAES of Ukraine https://orcid.org/0000-0003-2591-5218
Mykola A. Shynenko Institute for Digitalisation of Education of the NAES of Ukraine https://orcid.org/0000-0001-6697-747X

DOI:

https://doi.org/10.55056/cte.1211

Ключові слова:

FAIR data, Google Analytics 4, digital library, web analytics, longitudinal study, Open Science, Ukraine, scientific data management

Анотація

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.

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