Н. С. Редькина Evolving open science information infrastructure increases the number of diverse open access resources (OAR) and improves their functionality. This trend also facilitates new ways for scientific information and data search and analysis, scientometrical studies and science forecasting. Tracking science vectors is determined by the high rates of scientific and technological progress and the need to foresee the possible development scenarios in science and to define its priority vectors based on the processing metadata of scientific articles, data sets, patents, and other documents. The open access resources and search systems comprising information on hundred millions of documents in the open sources, provide the widest range of metadata of research results (often wider in typology than well-established license resources) and can make the basis for revealing the trends in science and their further visualization. To develop the approach to defining the trends in science based on the quantitative analysis of OAR data processed with visualization tools, the following problems were solved: 1) the term “trend” was analyzed; 2) patterns of patent and publication activities were specified to define the trends in science (OpenAlex, Lens, BASE, etc.); 3) the methods to identify the trends were selected (thematic mapping on the basis of key concepts and the most often used keywords, treтв extrapolation, etc.); and 4) trend analysis and visualization tools were examined (Google Trends, VOSviewer, Excel, etc.). The author suggests that the information products comprising the findings of trend identification and visualization analysis with the reference to user information queries, make a promising vector for the scientific libraries.
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