CASRAI Dictionary

Tag: research data management course

  • Research Data Management Training: 4 Routes

    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?

    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.

  • Research Data Manager Job Description, Skills and Career Path

    A research data manager plans, organises and safeguards the data a research project produces — from collection through documentation, storage, sharing and long-term archiving — and is distinct from a data steward (governance-focused) or a research administrator (grants and compliance-focused). The role sits at the intersection of research support, information management and IT, typically inside a university’s library, research office or a funded project team.

    This guide sets out the research data manager job description, the skills and qualifications employers ask for, how the role differs from adjacent titles, and the realistic career path from entry-level data support through to strategic data leadership.

    What is a research data manager?

    A research data manager is the named individual responsible for a project’s or department’s data management plan, metadata standards and repository deposits. The role exists because funders increasingly require a documented, reusable dataset alongside every publication, not just the paper itself.

    The task is not new — it maps closely to the Data Curation contributor role in the CRediT taxonomy, defined as “management activity to annotate, scrub data and maintain research data for initial use and later re-use.” CASRAI originated the CRediT contributor role taxonomy in 2014; the standard is now stewarded by NISO as ANSI/NISO Z39.104-2022, and Data Curation remains one of its 14 defined roles — evidence that the function research data managers perform has been formally recognised in scholarly attribution for over a decade.

    What does a research data manager do day to day?

    Day-to-day work centres on making a project’s data findable, well-documented and safely stored, then repeatable for the next study. Typical duties, drawn from published UK university and NHS job descriptions, include:

    • Drafting and reviewing data management plans (DMPs) for grant applications
    • Setting up and maintaining databases, spreadsheets and case report forms for a study
    • Applying metadata standards so datasets are discoverable in institutional or subject repositories
    • Coordinating deposit of datasets with DataCite-registered DOIs for citation and reuse
    • Running data quality checks, version control and access permissions across a research team
    • Training researchers and doctoral students in good data management practice
    • Advising on compliance with funder data policies and data protection legislation

    Research data manager vs data steward vs research administrator

    These three titles are frequently confused in job adverts because responsibilities overlap, but their primary focus and reporting line differ. The table below distinguishes the three roles as they typically appear in UK higher education and research institutions.

    Dimension Research Data Manager Data Steward Research Administrator
    Primary focus Lifecycle management of a specific project’s or department’s datasets Institution-wide data governance, quality rules and ownership policy Grant administration, compliance and researcher support
    Typical base Research office, library or funded project team IT services, information governance or central data office Research office, faculty or funder-facing team
    Core output Data management plans, metadata, repository deposits Data policies, classification schemes, access controls Grant applications, contracts, financial and ethics reporting
    Professional body Often affiliated with library/data-curation networks Information governance and data protection networks ARMA (UK/Ireland), EARMA, INORMS, NCURA
    Typical entry route Data science, library/information studies, life sciences degree IT governance, information management background Any discipline plus research administration training

    What skills, qualifications and training are required?

    Employers combine technical data skills with domain and communication skills, since the role requires translating funder and disciplinary requirements into practical workflows researchers will actually follow.

    • Data handling: spreadsheet and database competence; SQL, Python or R are increasingly listed as desirable
    • Standards knowledge: metadata schemas, DataCite, ORCID identifiers, and repository deposit workflows
    • Policy literacy: UK GDPR, funder data policies, and institutional research governance frameworks
    • Communication: training researchers, writing plain-English guidance, negotiating with study sponsors
    • Project management: running parallel studies to funder deadlines with limited resource

    Formal training routes include postgraduate qualifications in library and information science or data science, plus shorter dedicated courses. The Digital Curation Centre (DCC), funded by Jisc, has provided UK universities with research data management guidance and training resources since 2004 and remains the primary UK reference point for RDM practice. Institutional RDM obligations trace back to funder policy: EPSRC’s research data expectations, effective from 1 May 2015, require UK institutions receiving its funding to publish a research data management policy and a roadmap for compliance. The 2016 Concordat on Open Research Data — jointly published by Research Councils UK, Universities UK, Wellcome Trust and HEFCE — set out ten principles establishing that data management planning should be integral to research design, reinforcing why institutions now hire dedicated staff for this function rather than leaving it to individual researchers.

    What is the typical career path and salary range?

    Entry typically begins in a data assistant or data curator post supporting a research team’s day-to-day data handling, often on a fixed-term contract tied to a specific study. Real UK job postings illustrate the entry tier clearly: an NHS Research Data Manager post advertised in May 2025 by Midlands Partnership NHS Foundation Trust was graded at Agenda for Change Band 4, with a salary of £26,530 to £29,114 a year.

    Progression moves through Research Data Manager (owning DMPs and repository workflows for a department or portfolio of studies) to Senior/Lead Research Data Manager, where the postholder sets institutional RDM policy and may supervise a small team. The most senior tier — Director of Research Data Services or equivalent — sets strategic direction for an institution’s entire research data infrastructure and reports into the research office or library leadership. Unlike research administration, a PhD is not a standard requirement at any tier, though it is common among staff who progress from a research role into data management.

    Common questions about the role

    What are the responsibilities of a data manager?

    A data manager is responsible for the entire data lifecycle: collection, quality control, storage, security, documentation and eventual archiving or disposal. In a research context this extends to writing data management plans, applying metadata standards, and coordinating repository deposit so datasets remain reusable after a project ends.

    What does a research data manager do?

    A research data manager develops and implements the policies, workflows and documentation that keep a project’s or department’s datasets organised, secure and discoverable. Duties include drafting data management plans, training researchers, running quality checks, and depositing data with persistent identifiers such as DataCite DOIs for citation and reuse.

    What is the salary of a data manager?

    Salaries vary widely by sector and seniority. A UK NHS-graded entry-level research data manager post advertised in 2025 sat at Agenda for Change Band 4, paying £26,530–£29,114 a year; senior and director-level research data roles in universities and industry command substantially higher salaries, reflecting added strategic and line-management responsibility.

    What are the 4 types of research data?

    Research data is commonly grouped into primary data (collected directly for the study), secondary data (reused from existing sources), and quantitative versus qualitative data by format. A research data manager must apply appropriate metadata, storage and sharing rules to each type, since funder and ethical requirements differ across them.

    What this means for institutions and job seekers

    For institutions, the job description confusion between research data manager, data steward and research administrator is itself a risk: unclear scoping leads to duplicated effort or gaps in funder compliance. Writing role descriptions that reference recognised frameworks — the CRediT Data Curation role, DCC guidance, and funder RDM policy — gives hiring managers a defensible, standards-aligned specification rather than an ad hoc list of duties.

    For job seekers, the clearest differentiator to lead with on an application is lifecycle ownership of data, not general IT or administrative competence. As funders continue tightening open-data mandates, demand for staff who can demonstrate metadata standards knowledge, repository deposit experience and DMP authorship is likely to keep outpacing supply, making this one of the more durable specialisms within the broader research administration and support ecosystem.

    For related roles and standards context, see CASRAI’s CRediT contributor roles hub, the research administration dictionary, and the research administration pillar.