Research data management training covers the courses, workshops and certifications that prepare staff to plan, organise, preserve and share research data throughout its lifecycle. For someone moving into a data-steward or research-data-manager role, the realistic routes fall into four groups: institutional workshops, free self-paced courses such as MANTRA, the international CODATA-RDA Schools of Research Data Science, and formal professional certifications.
Research data management (RDM) is the set of practices that govern how research data is created, documented, stored, preserved and shared so that it remains accurate, findable and reusable. There is no single mandatory qualification for the role; instead, institutions and funders recognise a mix of short courses, free online training and professional certifications as evidence of competence.
- What is research data management training?
- Institutional workshops and short courses
- MANTRA and free self-paced courses
- CODATA-RDA Schools of Research Data Science
- Professional certifications for data stewards
- Comparing the four training routes
- Common questions about RDM training
- Choosing a pathway
What is research data management training?
Research data management training teaches the practical skills behind the data curation lifecycle: planning, documentation, storage, preservation and sharing. It is aimed at researchers, librarians, IT staff and administrators who take on data-support responsibilities, not only at specialists with “data steward” already in their job title.
Training providers range from single-day institutional workshops to multi-week international schools and multi-year professional certification pathways. The right choice depends on career stage, whether the goal is a specific role, and whether an employer or funder requires a recognised credential.
Institutional workshops and short courses
University-run workshops are the most common entry point. The Digital Curation Centre (DCC) runs a full-day Principles of Research Data Management workshop covering the data curation lifecycle, licensing, data sharing and secure storage; DCC prices the in-person session at £200 including VAT and includes materials, lunch and coffee breaks. Comparable sessions run through library and research-support teams at institutions including Queen’s University Belfast, the University of Liverpool and the University of Southampton, typically as half-day or full-day introductory sessions for research staff and postgraduate researchers.
- Short, structured, and usually free or low-cost for staff at the host institution
- Best suited to researchers and support staff who need a working overview rather than a credential
- Often the first step before pursuing a certification or specialist school
MANTRA and free self-paced courses
MANTRA, developed by the University of Edinburgh’s Data Library, is a free online course for researchers and anyone managing digital data as part of a research project. It works through data management planning, organising and documenting data, storage and security, ethics and copyright, and data sharing, using a self-paced format that fits around existing work commitments.
The UK Data Service published new introductory research data management course materials in January 2025, developed from workshops aimed at improving skills in managing, documenting, curating and sharing longitudinal research data. Other free options include the University of Edinburgh’s Research Data Management and Sharing MOOC and FOSTER Open Science’s introductory modules — all suited to self-directed learners building foundational RDM literacy before taking on formal steward duties.
CODATA-RDA Schools of Research Data Science
For a deeper, internationally recognised grounding, the CODATA-RDA Schools of Research Data Science are an intensive route. Since 2016, CODATA and the Research Data Alliance (RDA) have jointly run these schools, most commonly hosted at the Abdus Salam International Centre for Theoretical Physics (ICTP) in Trieste, alongside regional editions elsewhere. The programme typically runs as a two-week residential course covering data management, statistics, programming and reproducibility skills for researchers at early-career stage, with a strong focus on participants from low- and middle-income countries.
This route suits candidates who want a rigorous, research-council-recognised training block rather than a single workshop, and who can commit the time to an intensive residential format.
Professional certifications for data stewards
Where a role specifically requires a credential, two established professional certifications dominate. DAMA International’s Certified Data Management Professional (CDMP) is offered across four tiers, from Associate to Fellow, and covers the full range of data management disciplines including governance, quality, architecture and metadata — it is widely used as a baseline qualification for data managers moving from adjacent fields such as library science or IT.
The EDM Council’s Certified Data Steward (CDS) programme formalises data stewardship as a distinct professional designation, testing the ability to apply data quality, governance and metadata-management concepts in practice. The ICCP’s Data Governance and Stewardship Professional (DGSP) credential offers a similar path through foundation-to-executive levels, evaluated through a combination of education, experience and examination.
Comparing the four training routes
| Route | Format | Typical duration | Cost | Best for |
|---|---|---|---|---|
| Institutional workshop (e.g. DCC) | In-person, single session | Half-day to full-day | Free–£200 | First exposure to RDM concepts |
| MANTRA / UK Data Service / MOOCs | Self-paced online | A few hours to a few weeks | Free | Self-directed foundational learning |
| CODATA-RDA Schools | Residential, intensive | Around two weeks | Application-based, often funded | Early-career researchers seeking depth |
| CDMP / CDS / DGSP | Examination-based certification | Weeks to months of study | Paid, tiered | Formalising a data-steward job title |
Common questions about RDM training
What is research data management?
Research data management is the set of practices covering the entire data lifecycle — planning, collecting, storing, documenting, analysing, archiving and sharing data — designed to keep research data accurate, secure and reusable. It applies across disciplines and is increasingly required by funders and institutional policy, not just recommended good practice.
What is the best certification for data management?
There is no single “best” option; the right certification depends on career stage. DAMA International’s CDMP is the most widely recognised general credential, while the EDM Council’s Certified Data Steward designation is more targeted at staff whose job title is specifically data steward. Both are examination-based and tiered by experience level.
What are the 5 pillars of data management?
Most data governance frameworks, including those underpinning the CDMP and CDS syllabuses, group data management around data quality, data stewardship, data protection and compliance, data architecture, and data governance itself. Training routes vary in how much weight they give each pillar, so checking a course’s syllabus against these five areas is a useful sense-check.
Choosing a pathway
For institutions building RDM capacity, a blended approach works best: use free courses such as MANTRA to build baseline literacy across research and library staff, reserve CODATA-RDA School places for early-career researchers who need depth, and require a formal certification such as the CDMP or CDS only where a post is explicitly titled data steward or research data manager. This mirrors how the role sits within the broader research administration function, alongside compliance, funder liaison and governance duties.
As funder data-sharing requirements tighten, expect more institutions to treat a recognised RDM credential as a minimum bar for steward-titled posts rather than a discretionary extra. Staff who combine a foundational course with a certification, and who understand the wider vocabulary of the field via resources such as CASRAI’s research-data glossary, will be best placed for that shift.