Description
As Open Science and the FAIR data principles continue to reshape the research landscape, the roles of data stewards and data curators are gaining increasing importance. These professionals are essential for implementing sustainable data practices, ensuring long-term accessibility, and improving the quality of research data throughout their lifecycle. Within this context, Research Data Centers (RDCs) play a central role by curating, safeguarding, and providing access to high-quality data for secondary use, particularly in social sciences. However, in contrast to researchers who have various training opportunities, the education of data curators and other Research Data Management (RDM) professionals remains underdeveloped and scattered across institutions and disciplines. To address this gap, RDM Compas (Research Data Management Competence Base) was developed as an open accessible online platform aimed at strengthening the competencies of professionals working in RDM and research data curation, particularly in social, behavioural, educational, and economic sciences. RDM Compas is a project of KonsortSWD - a consortium of the German National Research Data Infrastructure (NFDI).
RDM Compas provides structured and flexible learning paths tailored to the specific needs of data stewards, data curators, and other RDM staff, aligning these with the Data Curation Lifecycle (Higgins, 2008). While the more widely known research data lifecycle focuses on researcher’s perspective and various stages data undergoes during a research project, the Data Curation Lifecycle (Higgins, 2008) emphasizes the process-oriented activities required to manage, curate, and preserve data for future reuse. This perspective underpins the platform’s approach to offered training and information materials.
RDM Compas offers a comprehensive knowledge base – RDM Knowledge Base - designed to support day-to-day work of RDC staff. It covers a wide range of RDM topics including metadata standards, persistent identifiers, legal and ethical aspects, data documentation etc. The articles are useful for both emerging and experienced professionals, and they are aimed at facilitating knowledge exchange between RDM professionals and researchers. To complement the Knowledge Base, RDM Compas includes an interactive, self-paced Trainingcenter. It offers internally developed courses and links to external training opportunities, emphasizing practical workflows in areas such as data quality assurance, anonymization, legal compliance etc. The training materials adhere to Open Educational Resources (OER) principles, ensuring that content is freely available and adaptable to individual learning needs and schedules.
In addition to the generic content, the platform also addresses specific challenges associated with different types of research data generated in social, behavioural, educational, and economic sciences. For instance, curating qualitative data often requires particular attention to ethical concerns, anonymization, and detailed documentation to ensure contextual integrity. This is especially important when dealing with sensitive topics or vulnerable populations. In contrast to qualitative data, corporate data, which is frequently collected for non-research purposes, presents unique challenges related to contractual agreements, data restructuring, and legal compliance.
RDM Compas is a community driven platform that aims to foster collaborations, share best practices and develop a foundation for professional standards in RDM. It encourages contributions from RDCs and other institutions to expand its informational and training resources. In doing so, it serves as a training tool and as a community for RDM professionals and thus represents a significant step towards the standardisation of research data curation in social, behavioural, educational, and economic sciences.
By presenting specific challenges encountered in some phases of the Data Curation Lifecycle, we will illustrate the most relevant and demanding competences required in practice. Drawing on insights from selected RDCs, the poster highlights how these competencies are applied in everyday data curation scenarios.
| Abstract | Poster |
|---|
