ANALYSIS AND SELECTION OF DIGITAL SOLUTIONS FOR THE INTEGRATION OF SCIENTIFIC JOURNALS WITH THE RUSSIAN SCIENCE CITATION INDEX (RISC)

Abstract

Objective. The objective of the study is to analyze and select digital solutions for the integration of academic journals with the Russian Science Citation Index on the basis of assessing editorial labor intensity, metadata quality, and the organizational and technological parameters of publication processing. Materials and Methods. The methodological framework of the study is based on systemic, comparative, and process approaches. The research applies methods of editorial workflow analysis, decomposition of publication processing operations, comparative assessment of digital solutions, and expert scoring of selection criteria. The empirical basis includes data on the actual practice of preparing journal publications for subsequent submission to the Russian Science Citation Index, including the average time required to process one article, the duration of issue preparation, the nature of typical metadata errors, and the number of repeated corrections. The study also draws upon academic publications devoted to the digital transformation of scholarly communications, electronic editorial platforms, metadata management, and scientometric infrastructure, as well as official materials on SCIENCE INDEX procedures and Open Journal Systems data import and export tools. Results. The study demonstrates that the manual model of preparing journal publications for integration with the Russian Science Citation Index is characterized by high labor intensity and unstable timelines. The average processing time for one article is 5-6 hours, while the average preparation time for one issue reaches 7-10 working days. A significant factor reducing process efficiency is the presence of recurring metadata errors, particularly incorrect completion of the JEL classification field when Cyrillic letters visually similar to Latin characters are used. As a result, the system fails to recognize the classifier correctly, which leads to repeated verification and correction cycles. The average number of repeated corrections per publication is 1-2 iterations. The research constructs a space of alternative solutions including a fully manual model, a ready-made editorial platform, a hybrid model, and a custom-built system. Comparative assessment shows that, under the conditions of the analyzed editorial office, the hybrid model is the most practically feasible option because it combines the existing digital infrastructure with additional tools for validation, normalization, and structured metadata export. Conclusion. The study concludes that journal integration with the Russian Science Citation Index should be treated as an independent organizational and technological task rather than as a purely technical upload procedure. Its solution requires the selection of a digital tool on the basis of measurable indicators instead of intuitive assumptions. A hybrid model makes it possible to reduce manual workload, decrease the number of formal metadata errors, and create a foundation for the future development of a specialized publication management system. Official SCIENCE INDEX materials emphasize the importance of correct issue registration, author and organization identification, and consistent metadata input, while OJS documentation confirms the availability of built-in import and export tools that may serve as the basis for a platform-based or hybrid integration model.