Copilot-generated summary based on the video recording of the event. Prepared by Irena Vipavc Brvar.
Data citation is a cornerstone of open science, ensuring that research data receive proper recognition and remain transparent, reproducible, and reusable. At a recent OPERAS 2026 conference, Irena Vipavc Brvar, Research Data Management Specialist at the Slovenian Social Science Data Archives (ADP), highlighted the growing importance of data citation as a cornerstone of open science. Drawing on her experience within the Consortium of European Social Science Data Archives (CESSDA), she demonstrated how proper data citation improves research transparency, reproducibility, and recognition of the substantial effort involved in collecting and managing research data.
Why Data Citation Matters
Research data are increasingly recognized as legitimate scholarly outputs that deserve the same level of acknowledgment as journal articles. Yet despite being essential to scientific discovery, datasets often remain invisible in traditional academic reward systems.
Proper citation helps close this recognition gap by:
- Giving credit to data creators.
- Supporting verification and reproducibility of research findings.
- Encouraging data sharing and reuse.
- Enabling tracking of data impact and usage.
- Strengthening the FAIR principles (Findable, Accessible, Interoperable, Reusable).
Core principles of data citation include the use of persistent identifiers, rich metadata, accessibility, versioning, and both human- and machine-readable citation formats.
The CESSDA Data Citation Guide
To address inconsistent citation practices across repositories and disciplines, CESSDA developed a comprehensive Data Citation Guide, published in 2024 after several years of collaborative work. Building upon initiatives such as FORCE11, the Research Data Alliance (RDA), and metadata standards like Dublin Core, the guide provides practical recommendations for researchers, repositories, publishers, institutions, and policymakers.
The guide recommends six essential citation elements:
- Author
- Title
- Publication year
- Version
- Data publisher/repository
- Persistent identifier (such as a DOI)
Additional elements, such as dataset number, resource type, and place of publication, may also be included where appropriate.
A Shared Responsibility Across Stakeholders
One of the guide’s key messages is that effective data citation requires coordinated action across the entire research ecosystem. CESSDA identified six stakeholder groups whose actions collectively enable robust citation practices.
Policymakers and Funders
National governments and research funders must establish clear policies requiring data citation and data availability. Slovenia provides a strong example through recent legislation and open science policies that mandate data management and sharing practices. Importantly, these policies are supported by dedicated funding, recognizing that open science infrastructure requires sustained investment.
Research Institutions
Universities and research organizations play a critical role in implementing policies through local procedures, data management support, and researcher training. In Slovenia, a large national project SPOZNAJ involving nearly all research-performing organizations has focused on developing institutional policies, workflows, and guidance for research data management.
Publishers and Journals
Journal policies are essential for integrating data citation into scholarly communication. Slovenian journals receiving 50 % or more public funding are now required to establish research data policies and ensure dataset citations appear in article reference lists.
To support publishers, guidelines have been developed by Slovenian RDA Node covering:
- Definitions of research data.
- Mandatory data citation requirements.
- Exceptions to open access.
- Trusted repository recommendations.
- Data availability statements.
- Roles and responsibilities of authors, editors, and reviewers.
These guidelines help journals standardize expectations and improve transparency.
Data Repositories
Repositories play a crucial quality-assurance role. Beyond assigning persistent identifiers and generating citations, trusted repositories provide curation, metadata enhancement, documentation support, and long-term preservation.
Examples from CESSDA repositories demonstrate how well-structured metadata expose methodological details, survey questions, and contextual information that significantly enhance dataset discoverability and reuse.
Challenges in Data Quality and Review
An important discussion during the session focused on data quality assessment. Editors noted that while journals increasingly require data availability statements, evaluating the quality of deposited datasets remains difficult.
Vipavc Brvar argued that trusted repositories can help address this challenge by conducting curation and quality reviews before publication. This reduces the burden on journal editors and reviewers while improving confidence in the data underlying published research.
The discussion also highlighted a common issue: researchers who have not planned for data sharing from the beginning of a project may face legal, ethical, or consent-related obstacles that prevent data publication later. This reinforces the need for data management planning and ethical review processes from the earliest stages of research.
Beyond FAIR: The Importance of Research Data Documentation
Another recurring theme was the critical role of data documentation. While repositories increasingly support rich metadata standards such as DDI (Data Documentation Initiative), supplementary documentation remains essential.
Participants discussed the value of structured README templates that describes datasets, variables, methodologies, and processing steps. Such documentation improves reproducibility, especially in disciplines where dedicated repositories are not yet available.
The distinction between raw data, processed data, and visualization data was also addressed. According to Vipavc Brvar, FAIR data should generally include the core microdata needed to reproduce analyses, rather than only aggregated tables or figures presented in publications.
Building a Culture of Data Citation
The presentation concluded with a broader reflection: implementing data citation is not simply a technical challenge. Success depends on fostering a culture that values data as a first-class research output.
Achieving this requires:
- Supportive policies and funding.
- Institutional implementation.
- Journal requirements.
- Trusted repositories.
- Robust metadata standards.
- Researcher training and awareness.
The CESSDA Data Citation Guide provides a practical framework for advancing these goals and helping the research community move toward greater openness, transparency, and recognition of valuable data contributions. As open science continues to evolve, proper data citation will be essential not only for preserving research integrity but also for ensuring that the creators of high-quality datasets receive the scholarly credit they deserve.
The presentation at the OPERAS 2026 & SCIROS Conference reinforced the importance of collaboration across the research ecosystem in promoting good data citation practices. By bringing together researchers, repositories, publishers, institutions, and policymakers, initiatives such as the CESSDA Data Citation Guide contribute to a more transparent, reproducible, and FAIR research environment.
Karim, F., Bornatici, C., Alaterä, T. J., & Vipavc Brvar, I. (2026, May 21). Fostering a Culture of Data Citation through Practical, Multi-Stakeholder Recommendations across the Research Ecosystem. OPERAS 2026 & SCIROS Conference. One Network, Many Possibilities: Strengthening the OPERAS Community, Warsaw, Poland. Zenodo. https://doi.org/10.5281/zenodo.21227995
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