DataverseUA: Research Data Repositories and Practical Dataset Publication
This course introduces research data repositories and the practical workflow for preparing and publishing research datasets in DataverseUA — the Open Research Data Repository of the National Academy of Sciences of Ukraine. The course explains the main types and functions of repositories, the structure and support model of DataverseUA, the roles of dataset authors and data curators, and the sequence of actions from preparing files and metadata to dataset review and publication.
The initial version of the course was compiled from presentations delivered during the webinar programme held on 8–9 October 2026. The original slides provided by the authors were divided into four thematic sections without changing their content or design.
Course Profile
Access: Open
| Format: Self-paced online learning | Language: Ukrainian |
| Scope: 4 thematic modules | Learning materials: 4 presentations |
| Level: Basic | Version: 1.0, 2026 |
Target Audience
The course is intended for researchers, PhD candidates, dataset authors, institutional data curators and data stewards, repository administrators, and research support staff involved in preparing, reviewing or publishing research datasets.
No prior experience with DataverseUA is required. Basic familiarity with FAIR principles and research data management is helpful but not mandatory.
Learning Outcomes
After completing the course, participants will be able to:
- explain the purpose and principal functions of research data repositories;
- distinguish between institutional, disciplinary, national and general-purpose repositories;
- identify the main criteria for selecting a reliable repository;
- describe the structure, support infrastructure and institutional collections of DataverseUA;
- distinguish the responsibilities of a dataset author, institutional data curator and repository curator;
- prepare dataset files, metadata, supporting documentation and access conditions;
- select an appropriate licence for a research dataset;
- outline the DataverseUA registration, submission, review and publication process;
- create and manage a draft dataset in DataverseUA;
- explain dataset citation, DOI assignment, versioning and the dataset lifecycle.
Course Content
Topic 1. Research Data Repositories: Purpose, Types and Selection
This topic explains the role of research data repositories in the Open Science and EOSC infrastructure. It presents the main functions of repositories and distinguishes between institutional, disciplinary, national and general-purpose services. Particular attention is paid to repository reliability, long-term preservation, DOI assignment, metadata support, licensing, certification and the criteria that should be considered when selecting a repository for research data.
Presentation length: 21 slides
Topic materials:
Topic 2. DataverseUA: Structure, Support and Data Curators
This topic introduces the Dataverse software platform and the DataverseUA repository. It describes the repository’s organisational structure, institutional collections, support infrastructure and integration with international research data discovery services. The presentation also explains the functions of repository and institutional data curators, the process of registering institutions and obtaining access rights, and the available routes for researchers whose institution does not yet have its own data curator.
Presentation length: 14 slides
Topic materials:
Topic 3. Preparing and Publishing a Research Dataset
This topic presents the complete workflow for submitting a research dataset to DataverseUA. It covers obtaining institutional approval, creating an account, requesting the necessary access rights, submitting a dataset placement request, preparing and uploading files, completing metadata, selecting a licence and defining access conditions. It also explains the curator’s review, correction and approval stages and the final publication of the dataset.
Presentation length: 23 slides
Topic materials:
Topic 4. Practical Work with DataverseUA
This topic provides practical guidance on working with the DataverseUA interface. Participants learn how to sign in, select an institutional collection, create a draft dataset, complete the required metadata fields, upload and organise files, apply licences and access restrictions, and submit a dataset for review. The presentation also covers metadata schemas, dataset citations, DOI identifiers, versions, metadata templates, guestbooks, links between datasets and collections, and the principal stages of the dataset lifecycle.
Presentation length: 24 slides
Topic materials:
Recommended Learning Sequence
The topics should preferably be studied in the proposed order. Topic 1 establishes the general context of research data repositories. Topic 2 introduces the DataverseUA infrastructure and the responsibilities of its participants. Topic 3 describes the regulated dataset preparation and publication workflow. Topic 4 translates this workflow into practical actions in the DataverseUA interface.
Participants who already have experience with research data repositories may use Topics 3 and 4 as a practical reference for preparing and publishing datasets.
Authorship and Course Development
Authors of the original learning materials: Serhii Svistunov, Pavlo Svirin, Nataliia Denysiuk and Svitlana Smoliak.
Course structuring and compilation: Research Data Management Competence Center of the National Academy of Sciences of Ukraine.
The course is based on presentations delivered during the webinar programme on research data management and practical work with DataverseUA. For the first version of the course, the original presentation slides were divided into four thematic sections while preserving their source content and visual design.