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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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231 to 240 of 1,260 Results
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...
Jul 15, 2026 - Sumy State University
Yevhen Kuzenko; Skydanenko Maksym; Ponomarova Liudmyla; Roman Pshenychnyi, 2026, "SEM-EDAX analysis of 8 hydroxyapatite samples: data obtained using the SEO-SEM Inspect S50-B instrument", https://doi.org/10.48788/DVUA/VBTHKX, DataverseUA, V1
The dataset comprises data acquired via scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX). These study materials clearly capture the differences in morphology, nanostructure dimensions, surface topography, and local elemental distribution among th...
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