Driving National R&D: Methodological Insights into Developing a Classifier for the Ukrainian National CRIS System by the State Scientific and Technical Library of Ukraine

Abstract

Objective. The objective of this study is to develop and characterize a comprehensive classifier for research and development (R&D), which plays a crucial role in the effective implementation of a National Current Research Information System (CRIS). The study aims to address the challenges and methodologies involved in creating a system that categorizes diverse R&D initiatives while ensuring interoperability with existing systems and adaptability to evolving scientific fields. Methods. The development of the classifier involved a multi-step process, including consultation with domain experts and reviewing existing classification systems. The study focused on identifying key research areas, ensuring compatibility with international standards, and developing a flexible taxonomy to cover both established and emerging fields. A diagnostic study on CRIS systems in Latin America and insights from similar systems, such as in Croatia and Portugal, were examined to refine the classifier's design for Ukraine. Results. The study successfully developed a classifier that addresses the specific needs of the Ukrainian research landscape, particularly within the Ukrainian Information System for Current Research (URIS). The classifier's structure aligns with international standards and supports interoperability with global databases. Furthermore, the dynamic nature of the classifier allows for continuous updates, making it adaptable to new research fields. The classification system was also tailored to accommodate Ukraine’s unique research ecosystem and infrastructure. Conclusions. The development of this R&D classifier represents a strategic advancement for Ukraine’s research infrastructure, enhancing data organization, accessibility, and collaboration. By addressing both technical and contextual challenges, the classifier provides a flexible, scalable solution that supports long-term scientific innovation. This study highlights the importance of context-driven approaches in creating effective research management tools, positioning the classifier as a robust framework for future developments in CRIS systems. The State Scientific Technical Library of Ukraine has played a pivotal role in developing this classifier, ensuring it meets the specific needs of the Ukrainian research community.