CASRAI Dictionary

Category: Guides & Explainers

Practical how-to guides, templates, checklists, and career pathways for research administrators, authors, and institutional teams.

  • Genomic Data Repository Guide: ENA vs GEO vs SRA

    Choosing a genomic data repository comes down to three questions: what type of data you have, whether it is identifiable human data, and what your funder or journal mandates. Raw sequencing reads generally go to the European Nucleotide Archive (ENA) or the Sequence Read Archive (SRA) — two mirrored nodes of the same international collaboration — while processed gene-expression data belongs in the Gene Expression Omnibus (GEO). A genomic data repository is a persistent, publicly accessible database that assigns stable identifiers to deposited sequence or expression datasets so they can be cited, retrieved and reused under FAIR data principles.

    ENA, GEO and SRA are the three repositories researchers encounter most often when funder or journal data-sharing policies require deposition of sequencing output. They are not interchangeable: each has a different primary data type, a different metadata standard, and a different position in the international data-sharing infrastructure. This guide compares them on deposit requirements, metadata standards and journal acceptance so research administrators and authors can make a defensible, mandate-compliant choice.

    What is a genomic data repository?

    A genomic data repository is a curated, publicly accessible database that archives DNA or RNA sequence data — raw reads, assembled genomes, or processed expression tables — and assigns each dataset a stable accession number for permanent citation. Repositories exist because journals and funders increasingly require that sequence data underlying a publication be deposited somewhere reviewers, readers and future researchers can retrieve it, rather than held privately by the authors.

    The three most consulted repositories for sequencing output are the European Nucleotide Archive (ENA), the Sequence Read Archive (SRA), and the Gene Expression Omnibus (GEO). ENA and SRA are both members of the International Nucleotide Sequence Database Collaboration (INSDC), alongside Japan’s DNA Data Bank of Japan (DDBJ); records submitted to any one of the three are mirrored across all of them, typically within 24-48 hours.

    ENA vs GEO vs SRA: how do they differ?

    The single biggest distinction is data type: ENA and SRA hold raw sequence reads (FASTQ, BAM, CRAM), while GEO holds processed functional genomics results — expression matrices, normalised counts and the experimental metadata describing them — and links out to SRA for the underlying raw reads. Geography and stewardship differ too: ENA is maintained by EMBL-EBI in the UK/Europe, while SRA and GEO are both maintained by the US National Center for Biotechnology Information (NCBI).

    Feature ENA GEO SRA
    Steward EMBL-EBI (Europe) NCBI (US) NCBI (US)
    Primary data type Raw reads, assemblies, annotated sequences Processed expression data + metadata Raw sequencing reads
    INSDC member Yes No (links to SRA) Yes
    Metadata standard ENA checklists MINSEQE / MIAME INSDC submission schema
    Access model Open (controlled tier via EGA for identifiable human data) Open Open (controlled tier via dbGaP)

    A frequently overlooked distinction is access control. None of ENA, SRA or GEO is designed to hold identifiable human genomic or phenotypic data. That category of data belongs in a controlled-access archive — the European Genome-phenome Archive (EGA), jointly run by EMBL-EBI and the CRG, or NCBI’s database of Genotypes and Phenotypes (dbGaP) — where access is granted through a data access committee rather than opened to the public. Depositing identifiable clinical genomic data in an open repository such as ENA or SRA would breach both the repositories’ own policies and, in most jurisdictions, data protection law.

    What are the deposit requirements for each repository?

    Each repository sets its own submission checklist, but all three require a structured description of the experiment alongside the sequence files themselves.

    • ENA requires a study, sample, experiment and run object for each submission, described against one of ENA’s checklist templates (for example, the pathogen or invertebrate checklists), plus the raw read files.
    • SRA requires equivalent BioProject and BioSample records, submitted through NCBI’s submission portal, with reads in FASTQ or BAM/CRAM format.
    • GEO requires a MINSEQE-compliant description of the experimental design (samples, protocols, processed data matrix) and will route the corresponding raw reads to SRA as part of the same submission, generating a linked SRA accession automatically.

    Because ENA and SRA mirror each other, a dataset submitted to one is not normally resubmitted to the other — submitting twice creates duplicate, unlinked accessions rather than better coverage.

    Which metadata standards apply?

    Metadata quality, not just file deposition, is what makes a dataset FAIR — Findable, Accessible, Interoperable and Reusable, per the FAIR data principles first published by Wilkinson et al. in 2016. GEO submissions are assessed against MIAME (Minimum Information About a Microarray Experiment) for array data and MINSEQE (Minimum Information about a high-throughput Nucleotide Sequencing Experiment) for sequencing-based expression studies. ENA and SRA submissions follow INSDC’s shared sample and experiment metadata schema, supplemented by checklist-specific fields for the sample type in question.

    Consistent metadata is also what allows a dataset to be discovered through cross-repository registries such as re3data and FAIRsharing, both of which index genomic repositories alongside thousands of other subject and generalist repositories.

    Do journals and funders accept all three equally?

    Most journal data-availability policies name an INSDC-compliant repository — ENA, SRA or DDBJ — as the acceptable destination for raw sequence data, and GEO or ArrayExpress for expression data. PLOS, for example, states that authors should select field-appropriate repositories and lists ENA, SRA, GEO and DDBJ among its recommended sequencing repositories, while also pointing authors to re3data and FAIRsharing when no field-specific option exists.

    Funder policy is generally repository-agnostic within the INSDC family: the NIH Genomic Data Sharing Policy and the 2023 NIH Data Management and Sharing Policy both accept SRA, dbGaP or an equivalent controlled-access archive for human data, without mandating SRA specifically over ENA. UK and European funders operating under UKRI or Horizon Europe open-science requirements similarly accept any INSDC-affiliated repository, reflecting the FAIR data principles rather than naming a single preferred database.

    Frequently asked questions

    What is the difference between ENA, GEO and SRA?

    ENA and SRA both archive raw sequencing reads and mirror each other as INSDC members, differing mainly in which institution — EMBL-EBI or NCBI — hosts the submission. GEO instead archives processed gene-expression results and metadata, forwarding the associated raw reads to SRA automatically during submission.

    Do I need to submit data to both GEO and SRA?

    Not separately. When you submit a gene-expression study to GEO, the platform generates a linked SRA accession for the raw reads as part of the same workflow, so a single submission satisfies both repositories without duplicate uploads.

    Is ENA the same as SRA?

    No — they are separate databases run by different organisations that mirror the same underlying INSDC data. A dataset submitted to ENA in Europe becomes visible through SRA in the US within roughly one to two days, and vice versa, so researchers choose one, not both.

    Which repository do funders require for genomic data?

    Most funder policies, including NIH’s Genomic Data Sharing Policy and UKRI’s open research requirements, accept any INSDC-affiliated repository — ENA, SRA or DDBJ — for raw sequence data, plus GEO for expression data, rather than mandating one specific database.

    What this means for research administrators

    For institutions building data-management-plan templates or compliance checklists, the practical rule is to map deposition guidance to data type and access sensitivity rather than to a single named repository: raw non-identifiable reads to ENA or SRA, expression matrices to GEO, and any identifiable human genomic or clinical data to a controlled-access archive such as EGA or dbGaP. Framing repository choice this way keeps research administration guidance aligned with funder and journal policy regardless of which INSDC node an individual researcher prefers to use.

    As funder mandates increasingly cite FAIR data principles explicitly rather than naming individual repositories, the durable compliance strategy is to select any INSDC-affiliated repository appropriate to the data type, document the accession number in the manuscript, and reserve controlled-access archives strictly for identifiable human data. Research offices that build this decision logic into deposit checklists now will need far less rework as funder policy language continues to converge on FAIR terminology rather than named databases.

  • EU-US Data Privacy Framework for Research Data

    The EU-US Data Privacy Framework (DPF) is the adequacy mechanism that lets UK and EU research institutions send personal data to self-certified US collaborators without signing Standard Contractual Clauses, provided the US recipient holds active DPF status covering the right data category. Where a collaboration involves health, genetic or other sensitive research data, extra labelling duties apply before the transfer can rely on the Framework at all.

    The EU-US Data Privacy Framework is a voluntary self-certification scheme, administered by the US Department of Commerce and underpinned by the European Commission’s 10 July 2023 adequacy decision, that recognises participating US organisations as offering GDPR-equivalent protection for personal data received from the EEA. A parallel UK adequacy instrument extends the same recognition to transfers made under UK GDPR. For research offices coordinating cross-border studies, biobanks, consortium agreements or collaborative datasets with US partners post-Brexit, choosing correctly between the DPF, the UK Extension and Standard Contractual Clauses (SCCs) determines whether a transfer is lawful on day one or exposed to later challenge.

    What is the EU-US Data Privacy Framework?

    The EU-US Data Privacy Framework replaced the invalidated EU-US Privacy Shield after the Court of Justice of the European Union’s 2020 Schrems II ruling found US surveillance law did not offer equivalent protection. The European Commission’s adequacy decision of 10 July 2023 concluded that the DPF ensures an adequate level of protection for personal data transferred to certified US organisations, removing the need for Standard Contractual Clauses on covered transfers.

    Eligibility is narrower than it first appears. Only US organisations regulated by the Federal Trade Commission or the Department of Transportation may self-certify, which excludes many non-profits, banks, insurers and telecoms — categories that include some university-affiliated research foundations and repositories. Institutions must verify a partner’s active status on the official DPF list before relying on it, and confirm the certification covers the specific data category (HR or non-HR) being shared.

    How does the UK Extension (Data Bridge) work post-Brexit?

    Since Brexit, UK organisations cannot rely on the EU adequacy decision directly. The Data Protection (Adequacy) (United States of America) Regulations 2023 created a separate UK Extension — commonly called the UK-US Data Bridge — which came into force on 12 October 2023 and lets UK organisations, including universities and Gibraltar-based bodies, make restricted transfers to US businesses that have separately self-certified to the UK Extension.

    Per the Information Commissioner’s Office, a UK institution relying on the Data Bridge must confirm the US recipient has active status on the DPF list, has specifically opted into the UK Extension (not only the EU-US DPF), and that its registration covers the correct data type. Periodic re-checks are required, since a US partner can lose or withdraw certification at any point during a live research project.

    EU-US Data Privacy Framework vs Standard Contractual Clauses for research data

    Where a US collaborator is not DPF-certified — common among smaller labs, non-profits and public bodies outside FTC/DoT jurisdiction — Standard Contractual Clauses remain the fallback transfer mechanism. UK exporters use the International Data Transfer Agreement (IDTA) or the UK Addendum to the EU’s SCCs, and, following Schrems II, must complete a Transfer Risk Assessment (TRA) examining whether US law could undermine the contractual protections.

    Feature DPF / UK Extension (Adequacy) Standard Contractual Clauses (SCCs)
    Legal basis Adequacy decision (EU) / adequacy regulations (UK) Contractual safeguard under UK GDPR Art. 46 / EU GDPR Art. 46
    Recipient eligibility Limited to self-certified, FTC/DoT-regulated US organisations Any US recipient, regardless of sector
    Transfer Risk Assessment required No Yes, mandatory since Schrems II
    Sensitive/special category data Must be explicitly flagged as “sensitive” to the recipient Protections negotiated within the contract and TRA
    Ongoing obligation Periodic verification of active DPF/UK Extension status Periodic review of the TRA and supplementary measures

    Many research offices now adopt a “belt and braces” approach: relying on the Data Bridge where a partner is certified, while keeping SCCs signed as a fallback in case certification lapses mid-project — a real risk, since a US partner can be forcibly removed from the DPF list by the Department of Commerce.

    Data sharing agreement vs data processing agreement: which applies?

    A data sharing agreement (DSA) and a data processing agreement (DPA) serve different roles in a research collaboration, and confusing them is a common compliance gap. A DSA is used when two institutions each act as independent or joint controllers — for example, two universities pooling anonymised survey results for a shared analysis. A DPA (required under UK GDPR Article 28) is used when one party processes data solely on the instructions of another, such as a US cloud vendor hosting a UK institution’s research dataset.

    • Use a DSA when both parties determine the purposes of processing (joint or independent controllers).
    • Use a DPA when one party is a processor acting only on the controller’s documented instructions.
    • Either document sits alongside, not instead of, the transfer mechanism (DPF, UK Extension or SCCs) — the agreement governs the relationship; the mechanism governs the lawfulness of the cross-border movement itself.

    What special rules apply to sensitive research data?

    Research data frequently includes health records, genetic material or biobank samples — categories UK GDPR classifies broadly as special category data. The DPF’s definition of “sensitive data” is narrower: only genetic data, biometric data used for unique identification, information about sexual orientation, and criminal offence data are covered, and only if the UK or EU sender proactively identifies and marks them as sensitive before transfer.

    This is a frequently overlooked gap for research consortia: personal data revealing ethnicity, religion, trade union membership or health status more broadly is special category data under UK GDPR but is not automatically treated as sensitive under the DPF unless explicitly flagged. Institutions transferring such data should apply a persistent classification (metadata tags or labelling) that survives onward sharing by the US recipient, and document this step in the study’s data management plan.

    Frequently asked questions

    What is the EU-U.S. Data Privacy Framework?

    The EU-U.S. Data Privacy Framework is a self-certification scheme allowing US organisations to receive personal data from the EEA under an EU adequacy decision. It replaced the invalidated Privacy Shield and removes the need for Standard Contractual Clauses for covered, certified transfers.

    What happened to the EU-US Privacy Shield?

    The Privacy Shield was invalidated in July 2020 by the Court of Justice of the EU in Schrems II, which found US surveillance access to personal data was not sufficiently limited. The Data Privacy Framework was negotiated as its successor and adopted in 2023.

    What is the status of the EU-U.S. Data Privacy Framework?

    As of mid-2026 the DPF remains in force, with the EU adequacy decision, the UK Extension and the Swiss-US DPF all active, though the mechanism continues to face legal challenges in the European courts, as its predecessors did.

    Implications for research institutions

    For research administrators managing international collaborations, the practical task is procedural discipline: verify DPF or UK Extension status before every transfer, not just at project setup; classify sensitive data explicitly; and keep SCCs and a completed Transfer Risk Assessment on file as a contingency. Given the DPF’s contested legal history, institutions that treat adequacy as a convenience rather than a permanent guarantee will be best placed to keep collaborations lawful if the Framework is narrowed or challenged again.

    These obligations sit within the broader compliance landscape that research administration teams increasingly own alongside funders, ethics committees and legal counsel — making data transfer literacy as core to running an international study as the science itself.

  • Research Data Management Policy: Not Just a DMP

    A research data management policy is an institution-wide governance document that sets ownership, retention, storage and researcher-responsibility rules for all research data an organisation produces — distinct from a data management plan (DMP), which is a project-specific document written for a single grant. Confusing the two leaves institutions with fragmented practice: strong per-grant DMPs but no consistent rule for what happens to data once a project, or a researcher, moves on.

    A research data management policy is the institutional framework; the DMP is one project’s implementation of it. This article sets out the structural difference and gives a template for writing the institutional-level document, covering ownership, retention tiers, storage classes and researcher obligations.

    What is a research data management policy?

    A research data management (RDM) policy is a formally approved institutional document — typically ratified by a university executive, senate or research committee — that defines how all research data created, collected or reused at that institution must be handled across its lifecycle: creation, active use, retention, sharing and disposal.

    Unlike guidance notes or web pages, a policy carries institutional authority: it assigns accountability, sets minimum retention periods, and states what happens by default when a researcher leaves or a grant closes. The UKRI Concordat on Open Research Data (2016, updated 2020), signed by UK Research and Innovation, Universities UK and the Wellcome Trust among others, sets out common principles — including that research data are a public good and that costs of good data management are legitimate, fundable research costs. Most UK institutional RDM policies, including those at Edinburgh, Southampton and Manchester, cite the Concordat directly as their basis.

    Research data management policy vs a data management plan

    The policy and the DMP operate at different scopes and answer different questions. The policy answers “what does this institution require of everyone, always?” The DMP answers “how will this specific project handle its specific data?” A DMP written for a UKRI or Horizon Europe grant should reference and comply with the institutional policy, not substitute for it.

    Dimension Institutional RDM policy Data management plan (DMP)
    Scope Whole institution, all research Single project or grant
    Author Research office, library, IT, governance committee Principal investigator / research team
    Trigger Approved once, reviewed periodically Written at proposal stage, revised through project life
    Contains Ownership defaults, retention minimums, storage tiers, roles Dataset types, volumes, specific repositories, embargo dates
    Enforcement Institutional compliance / disciplinary framework Funder compliance check at reporting/audit
    Review cycle Every 3-5 years (Edinburgh’s policy specifies five) Reviewed and updated within the life of one project

    A well-run institution needs both, in that order: the policy first, so every subsequent DMP inherits a consistent set of defaults — retention minimums, approved repositories, data protection procedures — rather than each research team inventing its own.

    Template structure for an institutional RDM policy

    Reviewing current UK institutional policies (Edinburgh, Southampton, Manchester, Birmingham, Cambridge) shows a consistent structural skeleton. A new or revised policy should include, in order:

    • Purpose and scope — why the policy exists, and which staff, students and data types it covers.
    • Definition of research data — the institution’s own working definition (the UKRI Concordat’s is a common starting point: digital or analogue information collected, observed or created to validate research findings).
    • Roles and responsibilities — who is the data owner by default (usually the institution), who is the data steward (usually the principal investigator), and what the research office, IT services and library each provide.
    • Data management planning requirement — a mandate that a DMP must exist for every funded (and, ideally, every unfunded) research project, and where that requirement sits relative to ethics approval.
    • Storage and security tiers — approved storage classes mapped to data sensitivity.
    • Retention and disposal — minimum retention period, and the trigger for review or deletion.
    • Sharing, access and FAIR compliance — the institution’s default position on open data, exceptions for confidentiality, and adherence to the FAIR principles (Findable, Accessible, Interoperable, Reusable), as defined by Wilkinson et al. in Scientific Data (2016).
    • Legal and ethical compliance — UK GDPR and Data Protection Act 2018 obligations for personal data, plus any sector-specific requirements.
    • Review cycle and ownership of the policy itself — who revises it and how often.

    This ordering matters: policies that lead with storage and IT detail before establishing roles tend to read as IT documents rather than governance ones, which weakens researcher buy-in.

    Retention, ownership and storage tiers

    Retention should be set as a minimum, not a target. A commonly cited UK baseline is three years from project end or publication, with the caveat that funder, sponsor or disciplinary requirements specifying longer periods take precedence — clinical and health-related data, for example, routinely requires 10-15 year retention under separate regulatory regimes.

    Ownership defaults matter because researchers move institutions far more often than data does. Most UK institutional policies assign underlying ownership of research data to the institution as the legal entity that employed the researcher and typically held the grant, while the principal investigator retains stewardship responsibility — the practical duty of care — during and after the project. This split must be stated explicitly, not left implicit, because it is the clause institutions rely on when a departing researcher wants to take data with them.

    Storage tiers should be mapped to data sensitivity rather than treated as one undifferentiated pool. A workable minimum is three tiers:

    • Tier 1 — open/shareable: deposited in a Re3data-listed, CoreTrustSeal-certified repository with a DOI via DataCite.
    • Tier 2 — restricted/sensitive: access-controlled institutional storage under a data sharing agreement.
    • Tier 3 — confidential/personal: encrypted storage meeting UK GDPR requirements, with a Data Protection Impact Assessment on file.

    Researcher obligations and governance roles

    The policy should state researcher obligations as directives, not suggestions. At minimum, researchers are required to: complete a DMP before data collection begins; store active data only in institutionally approved systems; register externally held datasets with the institution; and provide a data access statement or citation in any publication when the underlying data are not directly deposited.

    Governance sits across three functions the policy must name individually: the research office (grant compliance, costing RDM into proposals — UKRI states that RDM costs are eligible under its funding), IT services (approved storage infrastructure and security), and the library or research data service (repository operation, metadata standards, researcher training). ARMA and INORMS provide sector benchmarking for how these research administration roles are typically distributed across institutions.

    Common questions

    What is the difference between a research data management policy and a data management plan?

    A research data management policy is an institution-wide governance document setting defaults for ownership, retention and storage. A data management plan is a project-specific document, usually required by a funder at proposal stage, that details how one project’s data will be collected, stored and shared within those institutional defaults.

    Who is responsible for research data management at an institution?

    Responsibility is shared but must be explicitly assigned. The principal investigator is typically the data steward for a given project; the institution holds underlying ownership; and the research office, IT services and library provide the supporting infrastructure, costing advice and repository services the policy commits to.

    How long should institutions retain research data?

    Most UK institutional policies set a minimum retention period of three years from project end or publication, deferring to longer funder-, sponsor- or discipline-specific requirements where they apply — for example, clinical research data typically requires substantially longer retention under separate regulatory regimes.

    What does FAIR data mean in a research data management policy?

    FAIR stands for Findable, Accessible, Interoperable and Reusable — principles defined by Wilkinson et al. (2016) that a policy should require researchers to apply when depositing data, typically through persistent identifiers, standard metadata and appropriate licensing. See the CASRAI research data dictionary for related term definitions.

    Implications for research administrators

    Institutions that only mandate DMPs at grant stage, without an underlying institutional policy, end up with inconsistent retention practice, ambiguous ownership when staff leave, and duplicated storage costs across departments running incompatible systems. Writing the institutional policy first — using the structure above — gives every subsequent DMP a consistent, auditable baseline, and gives research offices a defensible answer when a funder, ethics committee, or departing researcher asks who owns what and for how long.

    As RDM costs are increasingly built into grants and UK institutions face growing FOI and audit scrutiny of data retention, the institutional policy is the operational backbone that per-project DMPs are supposed to inherit from, not replace.

  • DMPonline vs DMPTool vs Argos: DMP Tool Guide

    DMPonline, DMPTool and Argos are the three leading platforms for writing a data management plan (DMP): DMPonline (Digital Curation Centre, UK) and DMPTool (California Digital Library, US) share the same open-source DMP Roadmap codebase, while Argos (OpenAIRE) is built for machine-actionable, European open-science workflows. The right choice depends on your funder’s templates, whether your institution offers a branded instance, and whether you need structured API export.

    A data management plan tool is software that walks a researcher through funder- and institution-specific questions, stores the resulting answers as a structured document, and — increasingly — exports that document in a machine-readable format rather than as static prose. DMPonline is the Digital Curation Centre’s web-based DMP-writing service, built on the open-source DMP Roadmap platform it co-develops with the California Digital Library. This guide compares it against DMPTool and Argos on the three factors that actually decide adoption: funder-template coverage, institutional branding, and API export.

    What is DMPonline, and who runs it?

    DMPonline is a free web application, developed and hosted by the Digital Curation Centre (DCC), based at the University of Edinburgh. It supports researchers in producing a data management plan against a specific funder or institutional template, with embedded guidance text at each question. It is the standard reference tool for UK Research and Innovation (UKRI) grant-holders and is widely adopted across UK and European universities.

    Many institutions run their own branded instance rather than sending researchers to the generic service — the University of Manchester, University of Sheffield, University of Plymouth and University of Exeter all operate dedicated DMPonline subdomains with local templates and guidance layered on top of the shared DCC platform.

    DMPonline vs DMPTool: same codebase, different communities

    DMPonline and DMPTool are not separate products built by rival teams — they run on the same open-source codebase, DMP Roadmap, jointly developed by the DCC and the California Digital Library (CDL). The practical difference is community and funder coverage, not underlying functionality.

    DMPTool, operated by the CDL (part of the University of California system), is the default choice for US-based researchers, carrying templates for agencies such as the National Science Foundation (NSF) and National Institutes of Health (NIH). DMPonline carries the equivalent depth for UK and European funders, including UKRI’s constituent research councils and Wellcome Trust. Because both draw on the same codebase, a plan exported from either tool follows a broadly comparable data model — the divergence sits in which templates, guidance text and institutional branding are pre-loaded, not in the software itself.

    What is Argos, and how does it differ?

    Argos is a DMP-writing platform developed within OpenAIRE, the European open-science infrastructure, rather than from the DMP Roadmap lineage. Argos was designed from the outset around machine-actionable output, producing plans as structured objects intended to connect into the wider European research-information graph rather than sit as a standalone PDF.

    Its templates lean towards Horizon Europe and European Research Council (ERC) requirements, and its architecture emphasises linking a DMP’s contents — datasets, repositories, funders, organisations — to persistent identifiers already circulating in the OpenAIRE Research Graph. For a European-funded project embedded in that ecosystem, this integration is a genuine functional difference, not just a branding one.

    Funder-template coverage: which tool fits your funder

    Template coverage is usually the deciding factor, since a funder-specific template determines exactly which questions a plan must answer. The table below summarises where each platform’s template strength lies.

    Platform Steward Strongest funder coverage Typical user base
    DMPonline Digital Curation Centre UKRI councils, Wellcome Trust, UK institutional templates UK and European universities
    DMPTool California Digital Library NSF, NIH, US federal agency templates US universities and research institutes
    Argos OpenAIRE Horizon Europe, ERC, EOSC-aligned funders European open-science projects

    None of the three restricts researchers to their “home” funder templates — DMPonline hosts non-UK institutional templates, and DMPTool lists non-US funders too — but the depth of guidance and the freshness of template maintenance concentrate where each tool’s steward organisation has direct funder relationships.

    Institutional branding and API export compared

    Beyond templates, two practical factors distinguish the tools for an institution deciding which one to adopt.

    • Institutional branding. Both DMPonline and DMPTool support institution-specific branded sub-sites — a university can present its own logo, guidance text and curated template list under its own subdomain while the underlying platform remains centrally maintained. Argos, built for the OpenAIRE/EOSC ecosystem, is more typically deployed as a shared service with organisation profiles rather than fully white-labelled institutional instances.
    • API and machine-actionable export. All three platforms are converging on the RDA DMP Common Standard, developed by the Research Data Alliance’s working group on machine-actionable DMPs, which defines a shared JSON structure for exporting plan content. This is what allows a plan written in one tool to be read, in principle, by a funder system, a repository, or a research-information system rather than only by a human reader.

    For research administrators evaluating tools as part of broader research administration workflows, the practical question is less “which tool is best” and more “which tool’s export format and branding options integrate with our existing repository, CRIS and grants-management systems”.

    Common questions about choosing a DMP tool

    Do I need a data management plan?

    Most major funders — including UKRI, Wellcome Trust, the NSF, the NIH and Horizon Europe — require a data management plan as a condition of funding. If your grant application names one of these funders, you need a DMP, and using DMPonline, DMPTool or Argos is the fastest route to a compliant one.

    How do I write a data management plan?

    Writing a DMP means working through a funder-specific template — covering what data you will create, how it will be documented, where it will be stored, and how it will be shared or preserved. DMPonline, DMPTool and Argos each provide the relevant template with embedded guidance, rather than requiring you to draft one from a blank page.

    What is included in a data management plan?

    A DMP typically covers the types of data to be produced, the metadata and documentation standards used, access and sharing policies, and the plan for long-term archiving and preservation. Machine-actionable tools structure these elements so they can be exported and reused by other systems, not just read once.

    Choosing a tool: what the decision actually hinges on

    Because DMPonline, DMPTool and Argos are all converging on the same RDA DMP Common Standard for export, the choice between them is rarely a compatibility question. It comes down to fit: which platform already carries deep templates for your funder, whether your institution operates a branded instance you are expected to use, and whether your downstream systems consume RDA-conformant JSON export.

    For a UK or European researcher working with UKRI or Wellcome funding, DMPonline is the default starting point. For a US researcher working with NSF or NIH funding, DMPTool serves the equivalent role. For a Horizon Europe or ERC-funded project deeply embedded in the EOSC ecosystem, Argos’s machine-actionability and graph integration make it the stronger fit. As the RDA Common Standard matures further, expect the practical differences between the three to narrow to templates and branding alone, with export interoperability becoming a solved problem rather than a selection criterion.

  • Research Data Steward Job Description and Skills

    A research data steward is the named individual within a university, institute, or funded project who takes operational responsibility for the quality, FAIR compliance, documentation, and lifecycle management of a defined set of research datasets — distinct from the data owner, who holds accountability and sign-off authority, and the data custodian, who runs the technical storage infrastructure. The role sits inside the institutional research data management (RDM) team, typically reporting through the research office or library, and exists specifically because generic corporate data-steward job descriptions do not map cleanly onto grant-funded, multi-investigator, publicly scrutinised research data.

    Corporate data stewardship (the model most job-description templates online describe) is built around commercial master data, customer records, and regulatory compliance such as GDPR. Research data stewardship is built around a different set of pressures: funder-mandated Data Management Plans (DMPs), the FAIR Guiding Principles, discipline-specific repositories, and long-term reuse by researchers who were not part of the original project. This article defines the research-specific version of the role, maps it against the data owner and data custodian, and shows exactly where it sits in an institutional RDM structure.

    What Does a Research Data Steward Do?

    A research data steward manages the day-to-day quality, description, and reuse-readiness of research datasets on behalf of a principal investigator, department, or institutional repository. The role is operational, not accountable: a data steward implements policy, while a data owner sets it.

    Core duties typically include:

    • Reviewing datasets against the FAIR Guiding Principles — Findable, Accessible, Interoperable, Reusable — before deposit in a repository.
    • Writing and maintaining metadata, codebooks, and data dictionaries so a dataset is comprehensible to someone outside the original research team.
    • Advising researchers on Data Management Plan (DMP) compliance during grant applications and at project milestones.
    • Coordinating with disciplinary or institutional repositories on deposit, embargo periods, and licence selection.
    • Liaising with the data custodian (IT/systems) on storage, backup, and access-control implementation.
    • Flagging data quality issues — missing consent documentation, inconsistent variable coding, broken file formats — before they reach publication or reuse.

    UKRI’s Concordat on Open Research Data (2016) states that institutions are expected to have “clearly assigned responsibilities for the management of research data,” which is the direct policy basis most UK universities cite when creating dedicated data steward posts inside RDM or library services.

    Research Data Steward vs Data Owner vs Data Custodian

    These three roles are frequently conflated in generic data-governance content, but in a research setting they map to distinct, complementary functions. The data owner holds accountability; the data steward holds operational responsibility; the data custodian holds technical infrastructure responsibility.

    Role Primary focus in RDM Typical post-holder Accountable for
    Data owner Accountability and sign-off Principal Investigator or Head of Department Decisions on access, sharing, and retention of a specific dataset
    Data steward Operational quality and FAIR compliance Research data steward / RDM officer, often in the library or research office Metadata, documentation, DMP compliance, deposit readiness
    Data custodian Technical storage and access control Research IT / systems administrator Backup, encryption, storage infrastructure, access provisioning

    A single dataset can pass through all three roles: the PI (owner) approves that a dataset can be shared, the data steward prepares it to FAIR standard and selects the repository and licence, and the data custodian executes the technical transfer and sets the access permissions.

    What Skills and Qualifications Does the Role Require?

    Research data stewards need a blend of technical data-management skills and subject-domain fluency that generic corporate data-steward job descriptions rarely specify. Institutions increasingly treat this as a distinct career pathway rather than an IT-adjacent generalist role.

    • Working knowledge of the FAIR principles and metadata standards (Dublin Core, DDI, discipline-specific schemas).
    • Familiarity with persistent identifier infrastructure — DOIs assigned via DataCite, and researcher identifiers via ORCID — for correctly attributing and citing datasets.
    • Understanding of funder DMP requirements, including Horizon Europe’s and cOAlition S’s expectation that funded research data be FAIR by default.
    • Basic data-cleaning and documentation skills (spreadsheet/database literacy, controlled vocabularies, version control).
    • Communication skills sufficient to negotiate data-sharing terms between researchers, ethics committees, and repository managers.

    Professional bodies including ARMA (Association of Research Managers and Administrators) and INORMS now track research data stewardship as a recognised strand within the broader research-administration career pathway, reflecting its growing separation from generic corporate data governance.

    How Does This Differ from the CRediT “Data Curation” Role?

    The ANSI/NISO Z39.104-2022 CRediT taxonomy — originated by CASRAI in 2014 and now stewarded by NISO — includes “Data Curation” as one of fourteen contributor roles credited on a published paper. This is a per-publication authorship credit, not a job title or institutional post. A research data steward, by contrast, is an ongoing operational role that may perform data-curation work across many projects and papers, only some of which will formally credit them under the CRediT taxonomy. Conflating the two is a common error in job-description drafting.

    Where Does the Role Sit in the Institutional RDM Team?

    Research data stewards typically sit within one of three institutional homes: the library/research-data-services team, the central research office, or a departmental/faculty RDM function. Reporting lines vary, but the steward almost always works across, not inside, individual research groups.

    • Library-based model: data steward reports into research data services alongside repository managers and scholarly-communications staff — common where the institution treats RDM as an extension of open-access infrastructure.
    • Research-office model: data steward sits alongside grants and ethics administrators, closer to the DMP-compliance and funder-reporting workflow.
    • Departmental model: larger science faculties sometimes embed a data steward within a department, working directly with PIs on discipline-specific formats and repositories.

    In all three models, the data steward reports functionally to institutional data governance policy (set by data owners at PI or departmental-head level) while collaborating operationally with IT-based data custodians on infrastructure. The four core stewardship areas identified in institutional data-governance models — operational oversight, data quality, privacy/security/risk management, and policies and procedures — apply directly to this reporting structure.

    Answer-First Q&A

    What skills do you need to be a data steward?

    A data steward needs both technical and business-facing skills: metadata and data-modelling literacy, familiarity with data-quality tooling, and strong communication skills to translate governance policy into day-to-day research practice. In a research context, this also requires knowledge of FAIR principles, funder DMP requirements, and discipline-specific repository standards.

    What are the four main roles of an effective data stewardship model?

    An effective stewardship model groups responsibilities into four areas: operational oversight, data quality, privacy, security and risk management, and policies and procedures. Research data stewards typically own operational oversight and data quality directly, while collaborating with data owners and custodians on the remaining two areas.

    What makes a good data steward?

    A good data steward combines subject-domain credibility with disciplined documentation habits — able to identify data-quality problems early, communicate clearly with both researchers and technical staff, and apply governance rules consistently. In research settings, respect from the researcher community is essential, since the steward has no direct authority over the data owner.

    What is another title for a data steward?

    Common alternative titles include research data manager, data curator, RDM officer, and domain data steward. Institutions vary in naming, but the underlying responsibilities — FAIR compliance, metadata quality, and DMP support — remain consistent across these titles.

    Implications for Research Institutions

    As funders including UKRI, Horizon Europe, and cOAlition S tighten FAIR data requirements within grant conditions, institutions without a clearly defined research data steward role risk inconsistent DMP compliance and poor dataset discoverability after project closure. Writing a job description that borrows directly from generic corporate data-governance templates will under-specify the FAIR, DMP, and repository-liaison duties that make the research variant of the role effective.

    Institutions building or revising this post should draft the job description around the three-way split set out above — owner accountability, steward operations, custodian infrastructure — rather than treating “data steward” as a single undifferentiated data-governance title.

  • NERC Large Grants vs Standard Grant Eligibility

    NERC Large Grants fund £1.12 million–£3.45 million environmental-science projects through a two-stage, panel-gated review with no organisational demand-management cap — a materially different route from a generic “UKRI Standard Grant,” since each UKRI council runs its own standard/responsive-mode scheme with a different funding ceiling, eligibility rule and review structure.

    NERC Large Grants are a competitively assessed, two-stage funding scheme within the Natural Environment Research Council’s (NERC) Discovery Science portfolio, supporting large-scale, multidisciplinary environmental science research lasting up to five years. Research offices comparing this scheme against a “standard grant” need to understand one thing first: UKRI does not operate a single, unified Standard Grant product. Each of UKRI’s nine councils — NERC included — runs its own version, with its own rules. This guide sets out exactly how NERC’s Large Grant scheme is built, who can apply, how it is assessed, and where it genuinely diverges from the responsive-mode/standard routes offered elsewhere in UKRI.

    What are NERC Large Grants?

    NERC Large Grants fund researchers tackling major, often multidisciplinary environmental science questions that a single-investigator project cannot address. Under the current call structure, NERC funds between £1.12 million and £3.45 million per award, calculated at 100% full economic cost (FEC), of which NERC pays 80% FEC — the standard UKRI cost-sharing rate applied across the councils. Awards can run for up to five years, longer than most responsive-mode grants elsewhere in UKRI.

    Large Grants sit alongside two other NERC applicant-led routes: Pushing the Frontiers (curiosity-driven, no deadline, up to £950,000) and Urgency Funding (fast-track, up to £100,000, for time-critical environmental events). All three, including Large Grants, are explicitly exempt from NERC’s organisational demand-management quota system — a distinction that matters operationally and is detailed below.

    Who is eligible to apply for a NERC Large Grant?

    Eligibility for NERC Large Grants follows the standard UKRI organisational-eligibility framework: the lead applicant must be based at a UK research organisation recognised as eligible for NERC funding, and the proposed research must fit predominantly within NERC’s remit, though it can legitimately cross into other research council areas given the scale and multidisciplinary nature of these projects.

    Because Large Grants exist to fund large-scale, complex, often multi-institutional consortia, research offices should treat the eligibility bar as functionally higher than for a standard responsive-mode grant, even though the formal organisational rules are the same. In practice this means:

    • Co-investigators are typically drawn from multiple departments or institutions to justify the scale of funding requested.
    • Proposals must demonstrate the project cannot be delivered through NERC’s smaller Discovery Science or Pushing the Frontiers routes.
    • There is no organisational demand-management cap restricting how many Large Grant outlines an institution can submit — unlike some of NERC’s other responsive-mode schemes, where a quota system can apply if an institution’s success rate falls below a threshold.

    How does the NERC Large Grant peer-review process work?

    NERC Large Grants use a two-stage application and assessment process, distinct from the single-stage review used by most standard/responsive-mode grants elsewhere in UKRI. Outline applications are submitted first and assessed by a dedicated assessment panel; only applicants invited on the strength of their outline may submit a full proposal, which then undergoes expert (external) review followed by assessment from a moderating panel.

    For the current cycle, the British Antarctic Survey’s official funder guidance records outline proposals closing around 26 February 2026, with invited full proposals due around 5 November 2026 — a roughly eight-month gap between stages that research offices must plan resourcing around, since full proposals require substantially more development time than a standard single-stage grant.

    This gated, two-tier structure exists specifically to protect reviewer capacity: because each Large Grant represents a multi-million-pound, multi-year commitment, NERC screens ambition and fit at outline stage before committing full peer-review resource to detailed technical and financial scrutiny.

    NERC Large Grants vs UKRI Standard Grant: what’s different?

    This is the comparison research offices most often get wrong, because “UKRI Standard Grant” is not a single scheme name — it is shorthand researchers use for whichever council’s own responsive-mode grant applies to their discipline. EPSRC, for example, runs a route it calls “Standard Research,” for which official UKRI guidance states plainly that “there is no limit on the value of the grant or length of the project.” That is the opposite design choice to NERC Large Grants, which impose a fixed £1.12m–£3.45m ceiling and a hard five-year cap.

    Feature NERC Large Grants EPSRC Standard Research (typical “standard grant” comparator)
    Funding ceiling £1.12m–£3.45m at 100% FEC (fixed band) No upper value limit
    Project duration Up to 5 years (fixed cap) No fixed length limit
    Application stages Two-stage: outline, then invited full proposal Single-stage: full proposal submitted directly
    Assessment Assessment panel (outline), then expert review plus moderating panel (full) Expert reviewers, applicant response, then funding panel
    Submission timing Fixed annual deadlines (outline ~Feb, full ~Nov) Can be submitted at any time
    Demand management Explicitly exempt Varies; not scheme-specific in the same way

    The same pattern holds across UKRI more broadly: the Medical Research Council (MRC) and the Biotechnology and Biological Sciences Research Council (BBSRC) each run their own standard/responsive-mode research grants with separate eligibility text, funding ceilings and panel timetables. Researchers searching for “EPSRC small grants” are usually looking for the lower end of EPSRC’s uncapped Standard Research route, since EPSRC does not brand a separate small-grant tier the way NERC brands Large Grants, Pushing the Frontiers and Urgency Funding as distinct named products. Treating “UKRI Standard Grant” as one comparator, rather than nine council-specific routes, is the single most common eligibility-mapping error research offices make.

    Frequently asked questions

    What is NERC funding?

    NERC funding is grant support from the Natural Environment Research Council, one of UKRI’s nine councils, for environmental science research spanning earth, biological, atmospheric, ocean and polar sciences. It includes responsive-mode Discovery Science routes, Large Grants, Pushing the Frontiers, and Urgency Funding, alongside strategic and directed programmes.

    What is NERC in the UK?

    NERC is a UK public funding body that sits within UK Research and Innovation (UKRI), alongside councils such as EPSRC, MRC, ESRC, AHRC and BBSRC. It funds and coordinates independent research and training in the environmental sciences at UK research organisations and its own research centres, including the British Antarctic Survey.

    What is the success rate of the NERC grant?

    Historical reporting from Research Professional News found NERC’s overall responsive-mode success rate was around 24% in one funding round, down from 28% the year before — illustrating how competitive standard NERC schemes are even before reaching Large Grants, where the multi-million-pound threshold narrows the field further to a small number of full proposals each year.

    What are the odds of winning a grant?

    Odds vary by scheme, institution and round, but NERC’s demand-management policy is a useful signal: institutions whose success rate falls below a set threshold can be subject to a submission-quota system on affected schemes. Large Grants, Pushing the Frontiers and Urgency Funding are explicitly exempt from that quota system, so institutional track record does not restrict how many outlines a research office can submit to these three routes.

    What this means for research offices

    Research offices supporting environmental-science principal investigators should map funding options by scheme name, not by the generic label “standard grant.” NERC Large Grants demand early, resource-intensive outline development, a realistic assessment of whether a project is genuinely large-scale enough to justify the £1.12m–£3.45m band, and a long lead time between outline and invited full proposal. By contrast, a council running an uncapped, single-stage responsive-mode route rewards a faster, more opportunistic submission strategy.

    Because Large Grants sit outside NERC’s demand-management quota system, institutions with weaker recent success rates on other NERC schemes are not penalised here — a fact worth flagging explicitly to research administration teams building internal triage rules for which NERC route a given proposal should target. As UKRI continues to differentiate its councils’ funding architectures rather than converge on a single model, treating each council’s “standard” route as a distinct product, with its own ceiling, timetable and review structure, will remain the more accurate planning assumption for institutions across the sector.

  • BA/Leverhulme Small Research Grants: Field Guide

    BA/Leverhulme Small Research Grants are a British Academy/Leverhulme Trust funding scheme offering up to £10,000 over one to 24 months to postdoctoral scholars, including independent scholars, ordinarily resident in the UK. Unlike most UKRI council grants, the scheme sits outside the Full Economic Costing (fEC) regime and is administered through the British Academy’s own Flexi-Grant portal, not the UKRI Funding Service.

    The British Academy/Leverhulme Small Research Grants scheme is one of the British Academy’s highest-volume programmes, making awards to academics working at around 100 institutions across the UK. It is funded as a public-private partnership between the Department for Science, Innovation and Technology (DSIT), the Leverhulme Trust and the Wellcome Trust, alongside several named Special Funds. For humanities and social science researchers who sit outside the large UKRI research councils, it is one of the few nationally competitive routes to discrete, project-defined funding.

    This guide sets out who can apply, what the money can and cannot be spent on, how reporting works, and — critically — how the scheme’s rules diverge from EPSRC, MRC and the wider UKRI funding architecture.

    What are the BA/Leverhulme Small Research Grants?

    The BA/Leverhulme Small Research Grants scheme is a competitive award covering the direct expenses of a clearly defined humanities or social science research project. Awards are worth up to £10,000 and are tenable for between one and 24 months, with a minimum award of £500 for a discrete, identifiable piece of work.

    According to the British Academy’s own scheme guidance, funding is intended to cover initial project planning and development, direct research costs such as travel, subsistence and specialist research assistance, and the advancement of research through workshops, conferences or visits to and from partner scholars. It is explicitly not a personal fellowship or salary-replacement scheme.

    Who is eligible to apply?

    Eligibility is narrower than many applicants assume, but it is also more open in one important respect: independent scholars are welcome.

    • Applicants must be postdoctoral scholars or equivalent and ordinarily resident in the United Kingdom.
    • Applications need the approval of the applicant’s employing institution where one exists, but are not restricted to a particular grade (Lecturer, Professor or otherwise).
    • Independent scholars without an institutional affiliation may apply directly, selecting “independent scholar” in the Flexi-Grant portal.
    • Co-applicants may be based anywhere in the world, provided the Principal Applicant is ordinarily resident in the UK.
    • Postgraduate students are not eligible — this is a postdoctoral-and-above scheme.

    From the 2026 application round, the British Academy introduced a distinct submission window for independent scholars, who must now submit at least five working days before the round closing date; late submissions in this category are not processed. This is a genuine procedural detail that trips up first-time independent applicants, who often assume the standard deadline applies to them.

    What can the budget cover — and what is excluded?

    Because the scheme sits outside UKRI’s Full Economic Costing framework, the budget rules are simpler than a typical research council application, but also more restrictive in specific ways.

    Allowed Not allowed
    Travel and subsistence for fieldwork or archive visits Replacement teaching costs
    Specialist research assistance Payment in lieu of salary
    Workshop, conference and collaboration costs tied to the funded project Computer equipment/hardware
    Project planning and development costs Attendance-only conference fees with no defined research objective

    Applications purely to organise or attend a third-party conference — the kind of activity once covered by the Academy’s discontinued Conference Support Grant and Overseas Conference Grant schemes — will not be considered unless directly tied to disseminating results from the funded project. Grants are also not intended to fund UK–overseas scholarly interchange where there is no defined programme of activity behind it.

    How does reporting and compliance work?

    Reporting obligations scale with the size and simplicity of the award rather than mirroring the multi-year monitoring cycle of a UKRI standard grant. Award-holders submit progress and financial reporting through Flexi-Grant, and extensions to the tenure of an award (up to the 24-month ceiling) can be requested for a defined set of reasons set out in the British Academy’s current guidance for grant-holders.

    Because the £10,000 ceiling is a direct-cost allocation to the award-holder rather than an institutional fEC award, host institutions typically have a lighter administrative burden than for a UKRI grant — there is no 20% institutional contribution to manage, and no Je-S or UKRI Funding Service record to maintain. This is a material difference for research administration teams that otherwise triage every award through the same fEC costing workflow.

    How does this compare with EPSRC, MRC and the UKRI new funding model?

    Researchers moving between disciplines often assume every UK grant sits inside the same UKRI application and costing system. BA/Leverhulme Small Research Grants are a useful case study in why that assumption fails.

    Feature BA/Leverhulme Small Research Grants EPSRC (UKRI) MRC (UKRI)
    Administering body British Academy (with Leverhulme Trust, DSIT, Wellcome Trust) UK Research and Innovation UK Research and Innovation
    Application portal Flexi-Grant (British Academy’s own system) UKRI Funding Service UKRI Funding Service
    Typical award scale Up to £10,000, direct costs only Responsive-mode/standard grants, typically far larger Responsive-mode/standard grants, typically far larger
    Full Economic Costing (fEC) Not covered by fEC — award is direct-cost only fEC applies; UKRI funds 80% of the Full Economic Cost, institution covers the remainder fEC applies; UKRI funds 80% of the Full Economic Cost, institution covers the remainder
    Independent scholar eligible Yes, with a dedicated submission window Generally requires an eligible host institution Generally requires an eligible host institution

    UKRI’s own reform programme — often referred to informally as the UKRI new funding model — has spent recent years consolidating research council applications onto the single UKRI Funding Service (replacing the legacy Joint Electronic Submission, or Je-S, system) and harmonising grant terms and conditions across councils. BA/Leverhulme Small Research Grants sit deliberately outside this consolidation: they are not migrating to the UKRI Funding Service, and they retain the Academy’s own Flexi-Grant portal and a distinct, non-fEC costing model. For research administrators building a single institutional workflow across funders, that is the single most consequential operational fact in this comparison.

    Answer-first Q&A

    How much can a BA/Leverhulme Small Research Grant cover?

    Awards run from a minimum of £500 up to a maximum of £10,000, tenable for between one and 24 months. The award funds a single, clearly defined piece of research with an identifiable outcome, not an open-ended programme of work or a personal fellowship.

    Who is eligible for BA/Leverhulme Small Research Grants?

    Postdoctoral scholars or equivalent who are ordinarily resident in the UK, including independent scholars without institutional affiliation. Co-applicants can be based anywhere, but the Principal Applicant must be UK-resident, and postgraduate students are not eligible.

    Are BA/Leverhulme Small Research Grants covered by Full Economic Costing?

    No. The scheme is explicitly outside the fEC regime that governs most UKRI research council grants. The £10,000 ceiling is a direct-cost award to the researcher, not an institutional fEC settlement, which removes the usual 80/20 UKRI-institution cost split entirely.

    What can BA/Leverhulme Small Research Grant funding not be used for?

    Funds cannot cover replacement teaching, payment in lieu of salary, or computer equipment. Grants also exclude stand-alone conference attendance or UK–overseas interchange that lacks a defined research objective tied to the funded project.

    Implications for humanities and social science applicants

    The practical takeaway for applicants and research administration offices is that BA/Leverhulme Small Research Grants require a genuinely different compliance checklist from an EPSRC or MRC application. Institutions whose research administration workflows route every funder through the same fEC costing template risk misclassifying this scheme — either by over-costing an award that is meant to be direct-cost only, or by missing the independent-scholar submission window introduced for the 2026 round.

    As UKRI consolidates research council funding onto a single portal and cost model, schemes like BA/Leverhulme Small Research Grants remain a deliberate exception — and, for humanities and social science researchers, an opportunity: a low-friction, direct-cost route to project funding that never touches the UKRI Funding Service. Teams that keep a funder-specific map of eligibility, costing and reporting rules, rather than one generic template, turn that simplicity into an advantage rather than a compliance gap.

  • EPSRC Grants on the Web: Practical Search Guide

    EPSRC Grants on the Web is a legacy name for the Engineering and Physical Sciences Research Council’s public grant records, which today live inside UKRI’s Gateway to Research (GtR) — not a standalone EPSRC portal. Research administrators who search “EPSRC grants on the web” are usually looking for pipeline intelligence — who has been funded, at what value, on what panel — and that data is now accessed through GtR’s project, person, organisation and publication search tabs, with facets and Boolean syntax most users never open.

    EPSRC Grants on the Web is the name research administrators still use for EPSRC’s public record of funded projects, even though EPSRC itself no longer runs a separate database under that title. UK Research and Innovation (UKRI) — the body that has governed EPSRC since its formation in April 2018 from a merger of seven UK research councils, Research England and Innovate UK — now reports funding data centrally through Gateway to Research. This guide explains where the old records went, how to run an effective search across UKRI’s award database, and which search fields administrators most often overlook.

    What is EPSRC Grants on the Web?

    EPSRC Grants on the Web is a defined term: a public register of grants awarded by the Engineering and Physical Sciences Research Council, historically published as a searchable database in its own right and now consolidated into UKRI’s cross-council Gateway to Research service. The phrase persists in search behaviour and in older bookmarks, guidance documents and institutional wikis, but the underlying dataset is maintained centrally by UKRI rather than by EPSRC alone.

    For funding decisions made before 2018, EPSRC’s historic “funding rates” data — what the council called success and funding rates prior to the UKRI merger — sits in the UK Government Web Archive rather than in any live, searchable interface. That distinction matters for benchmarking: pre-2018 figures require an archive lookup, not a GtR query.

    Where did EPSRC’s “Grants on the Web” go?

    EPSRC’s council-specific funding page on ukri.org — last updated 29 September 2025 — directs users to Gateway to Research (gtr.ukri.org) for “research and training grants funded by EPSRC,” alongside a Tableau dashboard of panel outcomes. There is no standalone “EPSRC Grants on the Web” URL left to bookmark; the consolidation happened as UKRI centralised funding reporting across its research councils.

    This is a genuine source of confusion in the sector, because not every council followed the same path. NERC still operates its own distinct “Grants on the Web” portal at gotw.nerc.ac.uk, separate from Gateway to Research. Administrators who assume EPSRC has an equivalent standalone tool will end up on an archived or dead link instead of the live dataset.

    • EPSRC-funded projects, people and organisations: searchable live via Gateway to Research.
    • EPSRC panel outcomes and funding application results: a dedicated Tableau dashboard, linked from ukri.org.
    • Pre-2018 EPSRC funding/success rates: UK Government Web Archive snapshot only.
    • NERC awards: a separate, still-branded “Grants on the Web” portal at gotw.nerc.ac.uk.

    How do you search UKRI’s award database for EPSRC awards?

    Gateway to Research is built on Elasticsearch and Apache Lucene, so it supports full Boolean and field-level search syntax that most casual users never invoke. To find EPSRC awards specifically, run a keyword search and then apply the “Funder” facet to restrict results to EPSRC — the same mechanism works for MRC, NERC, BBSRC, ESRC, AHRC, STFC, Research England and Innovate UK, since all sit inside the same index.

    The search fields research administrators most often miss are the ones below the basic keyword box:

    • Quoted phrases — wrapping a term in quotation marks (e.g. "quantum sensing") matches the exact phrase rather than the individual words, which cuts noise dramatically on common technical terms.
    • Boolean operators — AND, OR and NOT must be capitalised to function; lower-case “and” is treated as a stray keyword, not an operator.
    • Wildcards — a question mark (?) matches a single character and an asterisk (*) matches zero or more, useful for catching spelling variants across a large grant corpus.
    • Fuzzy and proximity search — a tilde after a term (test~0.8) finds near-matches; a tilde after a quoted phrase ("test blood"~10) finds terms within a set word distance of each other.
    • Resource-type tabs — Projects, Persons, Organisations and Publications each expose a different advanced-search form, so a search run on the Projects tab will not surface matching Person or Organisation records by default.
    • Facets — ordered alphabetically and additive; selecting facets across categories (funder, scheme, research topic, lead organisation) narrows a result set, but switching tabs clears facets from the previous search.

    For institutional benchmarking, combine a funder facet (EPSRC) with an organisation facet and a date range, then bookmark the query URL — GtR search results are shareable by link, useful for a live funding-strategy dashboard rather than a static export.

    How does EPSRC’s data compare with MRC, NERC and BBSRC?

    Not every UKRI council presents its award data the same way. The table below summarises where each dataset actually lives, which is the detail administrators need before writing a search strategy that spans more than one funder.

    Council Primary live database Legacy/standalone portal Notes
    EPSRC Gateway to Research (gtr.ukri.org) None — retired into GtR Panel outcomes tracked separately via Tableau; pre-2018 rates in the Government Web Archive
    MRC Gateway to Research (gtr.ukri.org) None — retired into GtR MRC award and studentship data reported through the same GtR index as EPSRC
    NERC Gateway to Research (gtr.ukri.org) gotw.nerc.ac.uk (“Grants on the Web”) NERC still runs a dedicated legacy portal alongside GtR
    BBSRC Gateway to Research (gtr.ukri.org) Referenced as “Grants on the Web” in search behaviour, no dedicated live URL Council-specific funding page links back to GtR

    A single, correctly faceted Gateway to Research query will retrieve EPSRC, MRC, BBSRC and most other UKRI council awards from one interface — but anyone chasing NERC records should also check gotw.nerc.ac.uk, since it is not a simple synonym for GtR.

    Answer-first Q&A

    What is an EPSRC grant?

    An EPSRC grant is a funding award made by the Engineering and Physical Sciences Research Council to support research or training in engineering, mathematics, physical sciences and related disciplines. Awards are assessed at panel meetings, recorded centrally by UKRI, and searchable through Gateway to Research alongside awards from every other UKRI council.

    What is the EPSRC standard grant?

    The EPSRC standard grant is EPSRC’s core responsive-mode funding route, supporting investigator-led research proposals that fall within the council’s engineering and physical sciences remit. It sits alongside programme grants, fellowships and other UKRI application routes, and outcomes for standard-grant applications appear in the same panel-outcomes Tableau dashboard as other EPSRC schemes.

    Who is eligible for EPSRC funding?

    Eligibility for EPSRC funding generally requires an applicant to be based at an eligible UK research organisation and to hold, or be applying for, a role recognised by UKRI as suitable for a principal or co-investigator. Exact eligibility rules vary by funding scheme, so administrators should check the specific opportunity’s guidance on ukri.org before assuming a route applies.

    Are UKRI and EPSRC the same?

    No — UKRI and EPSRC are not the same body. UKRI is the umbrella organisation formed in 2018 that brings together seven research councils (including EPSRC and MRC), Research England and Innovate UK. EPSRC is one constituent council operating under UKRI’s governance, which is why EPSRC’s award data now reports through UKRI’s shared Gateway to Research rather than a council-only system.

    What this means for research administrators

    Treating “EPSRC Grants on the Web” as a live, separate URL wastes time chasing archived or dead pages. The efficient workflow is to query Gateway to Research directly, apply the EPSRC funder facet, and layer in Boolean, wildcard or proximity syntax when a common technical term returns too much noise. Institutions building funding-pipeline dashboards for research administration teams should bookmark faceted GtR query URLs rather than static exports, since the index updates as new awards are recorded.

    As UKRI continues centralising reporting across its councils, expect fewer standalone legacy portals to survive outside NERC’s. Administrators who build benchmarking habits around GtR’s search syntax now will not need to relearn an interface if NERC’s “Grants on the Web” is eventually folded into the same system.

  • UKRI Standard Grant Compared: 4 Core Grant Types

    The UKRI Standard Grant is UK Research and Innovation’s open-call, investigator-led funding route — no closing dates, no fixed value cap, no length limit. Frontier Research, Programme and Block grants each serve a narrower purpose: guarantee funding for European Research Council award-holders, large-scale team challenges, and institutional open-access costs respectively. Choosing the right one depends on team size, project duration and how much reporting your institution can absorb.

    UKRI’s Standard Grant is best defined as follows: it is the default, responsive-mode mechanism through which any eligible UK researcher can seek funding for a well-defined project, assessed purely on research quality by independent peer review, with no predetermined ceiling on award size or duration.

    What is the UKRI Standard Grant?

    The Standard Grant is UKRI’s most flexible, investigator-led route. According to EPSRC’s guidance for applicants (updated 7 May 2026), standard research funding carries “no closing dates – applications may be submitted at any time” and “no limit on the value or length of the grant.” Proposals are judged on international excellence and national importance as determined by independent peer review, not on fit against a themed call.

    The same “standard grant” label is used across research councils with council-specific framing. AHRC’s responsive-mode standard research grant, for example, funds “well-defined collaborative projects across the arts and humanities,” while EPSRC’s version spans everything from small feasibility studies to multimillion-pound programmes. This makes the Standard Grant the right starting point for most single-investigator or small-team proposals that do not fit a themed or strategic call.

    What is the UKRI Frontier Research Grant?

    This is the term most often misunderstood, including by AI search summaries that describe it as a loosely defined thematic label. In practice, the UKRI Frontier Research Grant is the domestic guarantee mechanism for UK-based researchers who win a European Research Council (ERC) grant under Horizon Europe — it mirrors the ERC’s own Starting, Consolidator, Advanced and Synergy Grant tiers rather than constituting a separate UKRI competition. Documented recipients, such as an Oxford economics fellow awarded “UKRI Frontier Research Guarantee” funding for a Horizon Europe-equivalent project, confirm this guarantee framing.

    Because it tracks ERC rules, duration follows ERC norms: Starting, Consolidator and Advanced Grants typically run up to five years, and Synergy Grants up to six. Applicants are assessed through the ERC’s own peer-review process, with UKRI stepping in only to administer the UK-side award and reporting. Do not confuse this with NERC’s separate “Pushing the Frontiers” discovery-science scheme or the Human Frontier Science Program (HFSP), both of which use “frontier” language but run entirely different application routes.

    How does the UKRI Programme Grant differ?

    Programme Grants exist for a different scale of problem. EPSRC describes them as “a mechanism to provide flexible funding to world-leading research groups to address significant major research challenges” (UKRI, updated 1 May 2026). Unlike the single-PI Standard Grant, a Programme Grant backs a multi-investigator team pursuing a coherent, multi-year research vision rather than one discrete project.

    The application route reflects that scale: applicants submit an outline proposal first, and only invited teams proceed to a full proposal — a staged process that does not exist for Standard Grants. This structure exists because Programme Grants fund substantially longer, larger and more interdisciplinary work than a single responsive-mode award, and the reporting burden scales accordingly, typically including milestone and work-package-level progress reporting rather than a single end-of-grant report.

    What does the UKRI Block Grant cover?

    The Block Grant sits apart from the other three because it does not fund research directly — it funds compliance. UKRI’s Open Access Block Grant (OABG) is paid to eligible research organisations, not to individual investigators, to help meet the costs of UKRI’s open access policy. UKRI states it is providing “up to £46.7 million per year to support the overall implementation” of that policy.

    Institutions use OABG funds to cover article processing charges (APCs) for peer-reviewed journal articles and conference proceedings arising from UKRI-funded research. The grant explicitly cannot be used for page or colour charges, and it does not cover monographs or book chapters, which draw on a separate long-form open access fund. Hybrid-journal APCs are eligible only where the title sits within a Transitional Agreement holding Transformative Journal status. Researchers apply to their own institution’s library or research office, never to UKRI directly.

    Which UKRI grant type fits your project?

    The table below maps the four grant types against the three variables that matter most when choosing a route: team size, duration and reporting burden.

    Grant type Who applies Typical team size Typical duration Reporting burden
    Standard Grant Individual investigator or small team 1–5 researchers No fixed limit; open-ended, project-driven Standard annual/final reporting
    Frontier Research Grant Single PI (ERC guarantee award-holder) PI plus group members Up to 5 years (up to 6 for Synergy) Follows ERC/Horizon Europe reporting cycle
    Programme Grant Multi-investigator research group Several co-investigators and teams Multi-year; longer than Standard Grants Staged outline/full proposal, then milestone reporting
    Block Grant (OABG) Research organisation (not individuals) Institutional — no project team Annual allocation cycle Institutional compliance reporting to UKRI

    For research administration teams triaging incoming proposals, the practical rule is: route single-investigator, open-scope ideas to the Standard Grant; route ERC-guarantee cases to Frontier Research; route large, team-based, multi-year challenges to Programme Grants; and manage Block Grant allocations centrally through the library or research office rather than per-project.

    Frequently asked questions

    What is a UKRI Standard Grant?

    A Standard Grant is UKRI’s responsive-mode, investigator-led funding route with no fixed closing date, value cap or duration limit. Proposals are assessed purely on research quality through independent peer review, making it the default option for single-investigator or small-team projects that do not fit a themed call.

    What is a UKRI Frontier Research Grant?

    A Frontier Research Grant is UKRI’s guarantee funding for UK-based researchers who win a European Research Council grant under Horizon Europe. It mirrors ERC Starting, Consolidator, Advanced and Synergy Grant tiers rather than being a standalone UKRI competition with its own criteria.

    How long does a UKRI Programme Grant last?

    Programme Grants run substantially longer than Standard Grants because they fund multi-investigator teams tackling significant, multi-year research challenges. Applicants submit a staged outline proposal before an invited full proposal, and the extended timeline supports interdisciplinary work across several linked work packages.

    Who can apply for a UKRI Open Access Block Grant?

    Only eligible research organisations — not individual researchers — can hold a UKRI Open Access Block Grant. Institutions use the allocation to cover article processing charges for UKRI-funded journal articles, while researchers request funds through their own university’s library or research office.

    Implications for research administrators

    The four grant types are not interchangeable entry points into the same competition — they are four separate governance structures with different applicants, timelines and reporting obligations. Institutional research offices that route proposals correctly at intake avoid two common failure modes: individual researchers mistakenly treating Programme Grant scale ambitions as Standard Grant submissions, and confusion between UKRI’s Frontier Research guarantee funding and NERC’s differently-named “Pushing the Frontiers” scheme.

    As UK association to Horizon Europe continues, expect the Frontier Research Grant guarantee mechanism to shrink in volume relative to direct ERC applications, while Programme Grants and the Open Access Block Grant remain the stable, UKRI-administered backbone of team-scale research funding and open access compliance respectively. Research administrators should treat grant-type selection as a governance decision made before drafting begins, not a formality resolved at submission.