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Dataverse UA is a national research data repository designed to support open science and implement the FAIR principles (Findable, Accessible, Interoperable, Reusable) in Ukraine. Its mission is to ensure long-term preservation, publication, and reuse of research outputs in standardized formats. The platform enables researchers, educators, graduate students, and institutions to store datasets, metadata, supporting documents, and code — all with persistent identifiers (DOIs), Creative Commons licenses, and ORCID integration. Dataverse UA supports both Ukrainian and English, allows the creation of thematic collections by discipline or institution, and complies with the standards of the National Academy of Sciences of Ukraine and international best practices. It is a tool for enhancing transparency, reliability, and reproducibility in research, while connecting Ukrainian science to global open data ecosystems.
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Tabular Data - 5.0 KB - 7 Variables, 79 Observations - UNF:6:30ZRIx4FhLaCQBuUPvK7vA==
Дані
Tabular Data - 5.1 KB - 7 Variables, 79 Observations - UNF:6:c9QXwxRNIjh8xcGaUW+ZSw==
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Tabular Data - 4.9 KB - 6 Variables, 79 Observations - UNF:6:S6xV3UQGM36SO6EASYq3rw==
Дані
Tabular Data - 4.9 KB - 6 Variables, 79 Observations - UNF:6:MX4ZzOzot4KIQLkRcYf5Qg==
Дані
Tabular Data - 4.9 KB - 6 Variables, 79 Observations - UNF:6:eRzeVnhr2gSO9lvIC/7n/A==
Дані
Tabular Data - 5.0 KB - 6 Variables, 79 Observations - UNF:6:2tuyZ3gLWCefBwxJRg1Zlg==
Дані
Jul 21, 2026 - V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine
Anisa, Kasim; Alexandr, Palagin; Petro, Stetsyuk; Olha, Khomiak, 2025, "Solutions to the symmetric traveling salesman problem for 1354 locations in the Kyiv region: Concorde solver", https://doi.org/10.48788/DVUA/7P2OE6, DataverseUA, V2, UNF:6:LkepojHDzM92QCMow9MEvg== [fileUNF]
The dataset includes geographic and Euclidean coordinates of 1354 locations in Kyiv region (including Kyiv city) and contains both input and output data for solving the symmetric traveling salesman problem (STSP) using Euclidean (L2) and Manhattan (L1) metrics. The dataset is int...
Jul 20, 2026 - V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine
Denkov, Ivan, 2026, "Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department", https://doi.org/10.48788/DVUA/VHVDAJ, DataverseUA, V1
The dataset includes data from 9544 patients of the cardiology department, obtained from a depersonalized fragment of the Aesculap patient visit database. Each patient's data is represented as a sparse binary 1436-dimensional vector. 1 more dimension is added to each vector - the...
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