- Іванова, С.М. (orcid.org/0000-0002-3613-9202) and Кільченко, А.В. (orcid.org/0000-0003-2699-1722) (2023) Features of the abstract and analytical database Dimensions – an innovative resource for supporting scientists In: Сучасні цифрові технології та інноваційні методики навчання: досвід, тенденції, перспективи. Матеріали ІX Міжнародної науково-практичної інтернет-конференції (м. Тернопіль, 6 квітня, 2023) . Тернопільський національний педагогічний університет імені Володимира Гнатюка, м. Тернопіль, Україна, pp. 236-240.
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Abstract
The paper analyzes the possibilities of the abstract and analytical database Dimensions - an innovative resource for supporting scientists. Dimensions is the world's largest connected research knowledge system, providing a new vision for discovery and access to research. Developed by Digital Science in collaboration with over 100 leading research organizations worldwide, this tool brings together publications, citations, grants, altmetrics, clinical trials, patents, policy documents and datasets to create a platform that allows users to find and retrieve access to the most up-to-date information, faster and more extensive analysis of academic results of scientific research, as well as gathering information for future strategy formation. Through deep indexing of a large number of publications and patents, Dimensions provides rich insights to support scientific research. This database isolates certain data about individual scientists and scientific institutions using artificial intelligence-based categorization and a wide range of different indicators. An innovative resource for supporting researchers, Dimensions is considered more than a database, providing access to information from journals around the world, as well as preprints, datasets, materials and books, and helping to identify future trends through grant funding. Dimensions' core mission is to enrich and link data for users: using keywords and concepts, organizations, researchers, or machine learning-based classifications to combine large amounts of information into a single, connected dataset.
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