Browsing by Author "Tsybenko, Iryna O."

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    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
    (Ukrainian State University of Science and Technologies, Dnipro, 2024) Tsybenko, Iryna O.; Zherebchuk, Sofiia V.; Fedchuk, Andrii P.
    ENG: 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.
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    The Necessity of Implementation of RI‘s Module to the Ukrainian Research Information System
    (Ukrainian State University of Science and Technologies, Dnipro, 2023) Tsybenko, Iryna O.; Zherebchuk, Sofiia V.
    ENG: The objective of implementing an RI (Research Information) module to the Ukrainian Research Information System is to enhance the management, visibility, and accessibility of research-related information within the Ukrainian research ecosystem. The module aims to improve the efficiency of research administration, promote collaboration among researchers and institutions, and facilitate the dissemination of research outputs. In this article, the authors attempted to investigate the need for developing a comprehensive classification of national research infrastructures with the aim of implementing a separate module into the national CRIS system. The work is aimed at analyzing the possibilities and advantages of implementing the RI (Research Information) module in the Ukrainian Research Information System. Methods. Developing the national classifier, the experience and methodology of the EU were utilized, taking into account both legislative and technical peculiarities specific to the country. Additionally, the approaches of various Ukrainian research institutions in defining and classifying research infrastructures were studied, and the existing experience in CRIS systems related to this matter was also examined. Results. The research should highlight the existing challenges and limitations in managing research-related information within the Ukrainian research ecosystem. This could include issues related to data fragmentation, lack of standardization, limited accessibility, inefficient research administration processes, and low visibility of research outputs. Based on the research findings, a set of proposed features and functionalities for the RI module should be presented. These features should address the identified challenges, stakeholder needs, and lessons learned from international practices. The proposed module should aim to improve data management, collaboration, visibility, and efficiency in research administration. Besides, the authors are trying to figure out the role of the libraries into CRIS implementation process. The scientific library's expertise in research data management, data curation, user support, collaboration, and promotion makes it an invaluable partner in implementing a Research Information module into the current Research Information System. Conclusion. The research should provide a comprehensive understanding of the necessity and potential benefits of implementing an RI module to the Ukrainian Research Information System, guiding future decision-making and actions in this regard. In general, the need for developing an operational classifier for the national CRIS system is driven by the fact that such a step will provide structured frameworks for managing research activities, efficient allocation of resources, including financial resources, strategic planning, and collaborations.