CASRAI Dictionary

Category: Guides & Explainers

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

  • FORCE11 Scholarly Communication Institute 2026: A Career Pathway for Research-Support Staff

    The FORCE11 Scholarly Communication Institute (FSCI) is an annual week-long summer training programme, co-hosted by FORCE11 and the UCLA Library, that teaches researchers, librarians, publishers, funders, and research administrators the practical skills of open scholarly communication. For research-support professionals specifically, FSCI functions less like a one-off conference and more like a structured training pathway: a recognised route to build open-science, data-stewardship, and research-metrics competence that can be cited on a CV or used to justify a promotion case. FSCI 2026 runs 27–31 July 2026.

    The FORCE11 Scholarly Communication Institute is best defined this way: it is a volunteer-run, multi-day summer school in which attendees select one week-long “morning course” plus a rotation of shorter afternoon electives covering topics such as FAIR data stewardship, persistent identifiers, peer review, and research metrics. It was first launched in 2017 and is modelled on the longer-running Digital Humanities Summer Institute in Victoria, British Columbia.

    What is the FORCE11 Scholarly Communication Institute?

    FSCI is the training arm of FORCE11, the community that originated in 2011 around “the Future of Research Communications and e-Scholarship.” Since 2017, FSCI has been co-organised with the UCLA Library and runs each summer, alternating in recent years between in-person, online, and hybrid formats. Course materials from FSCI 2020 through FSCI 2024 have been archived openly on Zenodo and the Open Science Framework, so the institute leaves a durable, citable training record rather than a one-time event.

    FORCE11’s broader track record matters for credibility: the same community co-developed the FAIR Data Principles and the Joint Declaration of Data Citation Principles, two frameworks that underpin research-data policy at funders and repositories worldwide. FSCI teaches practitioners to apply that same body of work operationally, rather than simply reading about it.

    Who should attend FSCI as a career-development step?

    FSCI is explicitly multi-audience: researchers, librarians, publishers, funders, university research-administration staff, students, and postdocs all attend the same institute, choosing courses at introductory or advanced level. For a research-support professional — someone working in a research office, library scholarly-communication unit, or funder programme team — this cross-sector mix is the point.

    Rather than training in isolation with only colleagues from one institution, attendees benchmark their skills against a global peer group. A 2018 Serials Review analysis of the institute (Rodriguez, 2018, DOI: 10.1080/00987913.2018.1555510) described FSCI as training people “not for where we’re at, but for where we’re going” — a framing that positions the institute as anticipatory skills-building rather than remedial catch-up.

    • Research administrators managing open-access compliance or data-management-plan review
    • Library staff moving into or already working in scholarly-communication roles
    • Early-career researchers who want to specialise in research infrastructure rather than bench/field research
    • Funder programme officers who need to understand practitioner-level workflows, not just policy text
    • Publishing and repository staff building peer-review, persistent-identifier, or metrics expertise

    How does the FSCI course structure work?

    Each attendee commits to one week-long morning course, which allows sustained, cohort-based depth on a single subject, and supplements it with shorter afternoon elective courses on adjacent topics. This structure is designed to produce both a depth credential (the morning course) and breadth exposure (the electives), which is unusual among short-format professional development options in the research-support field.

    Topics have included FAIR data management and stewardship, persistent identifiers, peer-review innovation, new forms of publication, research-metrics literacy, and — in recent years — AI governance in scholarly communication. Plenary sessions, “do-a-thons,” and structured networking events run alongside the coursework, which is what distinguishes FSCI from a standard webinar series.

    What does FSCI cost, and are scholarships available?

    FSCI publishes its registration fees and scholarship terms on the official FORCE11 site ahead of each year’s institute, and pricing has varied by year and by in-person/online format. FORCE11 has consistently run a scholarship programme to support attendance from historically underrepresented regions; organisers have reported scholarship recipients from six continents, including documented career-changing participation from institutions in Nigeria and Pakistan. For a research-support professional building a career-development business case, the scholarship route is often the most persuasive argument to an institution reluctant to fund a full-fee place.

    Attribute FSCI (FORCE11) Formal scholarly communication librarian role
    Format One-week intensive summer institute Ongoing salaried position
    Entry route Open registration; no degree prerequisite Typically requires an MLIS or equivalent
    Cost to individual Course fee, offset by scholarships N/A — paid employment
    Output Practical skills, network, open course materials Institutional job title and remit
    Best used as A training pathway feeding into or alongside a role The destination role itself

    How does FSCI differ from a formal scholarly communication librarian role?

    It is worth being precise about the distinction, because the two are often conflated in search results. A scholarly communication librarian is a formal, usually MLIS-qualified, salaried institutional role with responsibilities such as running an institutional repository, advising on copyright and open-access policy, or managing an “office of scholarly communication.” FSCI is not that role — it is a training pathway that can be undertaken by someone already in such a role, by someone aspiring to move into one, or by a research administrator, funder officer, or publisher who never intends to hold that job title at all.

    This distinction matters for career planning. Treating FSCI as a credential-building input — alongside, not instead of, formal qualifications, ORCID-linked professional profiles, and institutional experience — is the more accurate way to use it. Institutions considering whether to fund staff attendance should therefore evaluate FSCI as continuing professional development, comparable to funding attendance at ARMA, NCURA, or EARMA training events, rather than as a substitute for a formal library or research-office qualification.

    Frequently asked questions

    What is FSCI 2026 and when does it take place?

    FSCI 2026 is the annual FORCE11 Scholarly Communication Institute, running 27–31 July 2026. It follows the institute’s established format of a week-long morning course paired with rotating afternoon electives on open-science and research-communication topics for a global, cross-sector audience.

    How much does FORCE11 FSCI cost to attend?

    Registration fees are set and published by FORCE11 for each year’s institute and vary by format and early registration. FORCE11 runs a dedicated scholarship programme that has supported attendees from underrepresented countries and regions, which materially lowers the effective cost for many participants.

    Who should attend the FORCE11 Scholarly Communication Institute?

    FSCI is designed for researchers, librarians, publishers, funders, and research administrators at any career stage, plus students and postdocs. Courses are offered at introductory and advanced levels, so attendees choose a track matched to their existing scholarly-communication knowledge.

    Are FSCI course materials available after the event?

    Yes. FORCE11 has archived FSCI course materials from 2020 through 2024 openly on Zenodo and the Open Science Framework, meaning the training content remains accessible as a reference resource even for people who did not attend that year’s live sessions.

    What this means for research-support careers

    For institutions, FSCI attendance is a low-cost, high-signal way to build in-house open-science capacity without hiring a new specialist role. For individuals, it is a documented, citable training credential that sits alongside — not in place of — formal qualifications and institutional experience. As open-access mandates, data-management requirements, and AI-governance expectations continue to expand across funders including UKRI and cOAlition S signatories, the practical skills FSCI teaches are becoming a standard expectation of research-support work rather than a specialist add-on.

    Research offices, libraries, and funder teams weighing professional-development budgets in 2026 should treat FSCI as one input in a broader research-support career pathway: a way to keep staff current with FAIR data practice, persistent identifiers, and evolving scholarly-communication standards, while formal qualifications and institutional experience continue to do the work of defining the job itself.

  • DDI Metadata Standard: FAIR Data Checklist for Survey Archives

    The DDI metadata standard (Data Documentation Initiative) is an international, XML-based specification for documenting surveys, censuses, and other social, behavioural, and economic science microdata at both the study and variable level. It is the metadata backbone that most social science data archives use to make survey data findable, accessible, interoperable, and reusable (FAIR) — turning a raw data file plus a PDF codebook into a machine-readable, citable, cataloguable research object.

    DDI is not a government mandate or a funder requirement; it is a community-maintained documentation standard. The DDI Alliance, an international collaboration established in 2003, maintains the specification and its schemas. This guide explains what the standard covers, who uses it, how it maps onto the FAIR principles, and the practical steps a repository or research team needs to adopt it.

    What is the DDI metadata standard?

    The Data Documentation Initiative is a metadata standard for describing the full lifecycle of a research data collection: study design, sampling, data collection, processing, variables, and access conditions. It was built specifically for social, behavioural, and economic sciences data — surveys, censuses, panel studies, and administrative microdata — rather than as a general-purpose schema.

    Records are encoded in Extensible Markup Language (XML), which makes them machine-readable and harvestable. A DDI catalogue record typically documents three layers: the study description (bibliographic citation, scope, geography, time period, methodology), the data file description (format, structure, missing-data conventions, weighting), and the variable description (question text, value labels, codes). This granularity is what separates DDI from simpler discovery schemas such as Dublin Core, which describe a resource but not its internal variable structure.

    Who maintains DDI and which archives use it?

    The DDI Alliance, an international collaboration of research institutions, statistical agencies, and data archives established in 2003, develops and maintains the specification. DDI is listed as a recognised research-data metadata standard in the Research Data Alliance Metadata Standards Catalog (entry m13), which documents its scope, schemas, and adoption.

    According to the UK Data Service, DDI “is used by most social science data archives in the world” to structure catalogue records, and it forms the basis of the discovery metadata behind its own collection. The Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan and the members of CESSDA, the Consortium of European Social Science Data Archives, likewise build their cataloguing infrastructure on DDI, harvesting records via the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) so aggregators can index them without direct database access.

    How does DDI support the FAIR data principles?

    The FAIR Guiding Principles — findable, accessible, interoperable, reusable — were formalised for the research community in 2016. DDI operationalises each principle for survey and social science data specifically, rather than leaving them as abstract goals.

    • Findable: structured study-level metadata (title, creators, keywords, abstract, coverage) makes records indexable by catalogues and search engines, and DDI records are commonly assigned persistent identifiers, including DOIs registered through DataCite.
    • Accessible: standardised access-condition fields tell a would-be reuser exactly how to request or download the data, and harvesting via OAI-PMH gives repositories a predictable retrieval protocol.
    • Interoperable: a shared XML vocabulary and controlled thesauri — the European Language Social Science Thesaurus (ELSST), maintained by CESSDA, is one widely used example — let metadata move between archives and languages without semantic drift.
    • Reusable: variable-level documentation (question wording, value labels, derivation logic) and provenance information are what actually let a second researcher re-run or extend an analysis, which is the point FAIR exists to serve.

    DDI-Codebook vs DDI-Lifecycle vs DDI-CDI: which do you need?

    DDI is not a single schema. Three variants serve different documentation depths, and choosing the wrong one is the most common early adoption mistake.

    Variant Best for Documents Status
    DDI-Codebook (DDI-C) A single finished dataset Study, file, and variable description for one deposit Simpler, widely used legacy format
    DDI-Lifecycle (DDI-L) Longitudinal or multi-wave studies The full research lifecycle: concept, instrument, collection, processing, archiving, reuse Comprehensive, versioned in the 3.x series
    DDI-CDI (Cross-Domain Integration) Integrating structured data across statistical and research domains Model-driven descriptions that link datasets, variables, and classifications across systems Developed jointly by the DDI Alliance and the SDMX community

    A single-wave survey deposited once needs only DDI-Codebook. A cohort study revisited over years — the kind of resource the UK Data Service and ICPSR both hold in volume — needs DDI-Lifecycle to capture instrument changes between waves. DDI-CDI is aimed at repositories that need to align microdata with aggregate statistics (for example, linking a survey to official statistics published under SDMX), which is an emerging rather than default requirement.

    A practical checklist for adopting DDI

    Repositories and research teams introducing DDI documentation for the first time should work through these steps in order:

    1. Identify your lifecycle stage. A one-off dataset needs DDI-Codebook; a repeated or panel study needs DDI-Lifecycle.
    2. Model metadata before ingest, not after. Capture study description, sampling, collection dates, and variable labels/codes at deposit time using a structured deposit form, as the UK Data Service does, rather than reverse-engineering them from a finished file.
    3. Use a DDI-aware authoring tool (for example Colectica or Nesstar-derived CESSDA tooling) instead of hand-writing XML, which is error-prone at scale.
    4. Register a persistent identifier. Crosswalk core fields to the DataCite metadata schema so the dataset gets a citable DOI alongside its DDI record.
    5. Adopt a controlled vocabulary such as ELSST for subject keywords to keep records interoperable across languages and archives.
    6. Enable OAI-PMH harvesting so catalogue aggregators and search services can index the record without bespoke integration work.
    7. Validate against peer practice — check the record structure against the RDA Metadata Standards Catalog entry and against comparable ICPSR or CESSDA holdings before publishing.

    Answer-first Q&A

    What is the metadata standard DDI?

    DDI (Data Documentation Initiative) is an international metadata standard for documenting socioeconomic surveys, censuses, and microdata. It is maintained by the DDI Alliance, encoded in XML, and used by most social science data archives worldwide to capture study, file, and variable-level documentation in one structured record.

    What is the best metadata standard for survey data?

    For general resource discovery, Dublin Core (ISO 15836) is the simplest and most widely implemented option. For social science survey and microdata specifically, DDI is the domain standard, because it documents variables and methodology in a depth Dublin Core does not attempt.

    How does DDI support the FAIR data principles?

    DDI supports FAIR by pairing structured, machine-readable metadata with persistent identifiers for findability, standardised access fields for accessibility, a shared XML vocabulary and thesauri for interoperability, and variable-level provenance for reusability — the depth needed to re-run a secondary analysis.

    What is the difference between DDI-Codebook and DDI-Lifecycle?

    DDI-Codebook documents a single finished dataset. DDI-Lifecycle documents the entire research process — instrument design, fieldwork, processing, and archiving — across multiple waves, making it the correct choice for longitudinal and panel studies rather than one-off deposits.

    What this means for research data repositories

    Funder and journal data-sharing policies increasingly ask for FAIR-compliant deposits, but “FAIR” is a set of principles, not a file format. DDI is one of the few domain standards that translates those principles into a concrete, testable schema for survey and social science data — which is why it underpins the cataloguing infrastructure at the UK Data Service, ICPSR, and CESSDA member archives rather than being a niche archival choice.

    Institutions building or upgrading a research data repository for social science holdings should treat DDI-Lifecycle adoption, ELSST keywording, and DataCite DOI registration as a single connected workflow rather than three separate projects. Repositories that skip variable-level documentation still get a catalogue entry, but they do not get reuse — and reuse, not deposit, is the actual measure of FAIR success. Institutional research administration and data management guidance should reference DDI explicitly wherever survey or microdata deposit is in scope.

  • MRC Grants Awarded: How to Read the Register

    MRC grants awarded data is published across three separate UKRI sources — Gateway to Research, the legacy Grants on the Web (GOTW) register, and MRC’s board and panel outcomes pages — and reading it correctly for benchmarking means matching each source to a different question: what was funded, who applied, and how competitive each specific panel meeting was.

    The MRC grants awarded register is the collective term for the public funding-decision records that UK Research and Innovation (UKRI) publishes for the Medical Research Council, spanning historical award spreadsheets, a live searchable grants database, and meeting-by-meeting board and panel outcome listings. For research office staff building competitor intelligence or benchmarking their institution’s success against peers, the register is genuinely useful — but only if its structure and its stated caveats are understood before the numbers are used.

    What is the MRC grants awarded register?

    There is no single document called the “MRC grants awarded register” — it is a set of linked publications UKRI maintains under its “What MRC has funded” pages. These cover awarded grants and fellowships from April 2006 to December 2019 as a downloadable spreadsheet, interactive Tableau dashboards for 2022–23 funding decisions, and rolling board and panel outcome listings for funding meetings from 2017 onward, with earlier records held in the UK Government Web Archive.

    Before 2018, MRC referred to this material as “success rates”; UKRI has since folded the reporting into the wider board and panel outcomes format used across all seven research councils. Any benchmarking exercise therefore has to account for a terminology and format change partway through the period being analysed.

    Where to find MRC grants-awarded data: three sources compared

    Three distinct tools hold MRC award data, and each answers a different research-intelligence question. Confusing them is the single most common reading error institutions make when building competitor comparisons.

    Source What it covers Update pattern Best use
    Gateway to Research Full award records once a grant has started, including principal investigator, institution and value, across all UKRI councils Continuous, as grants start Cross-council portfolio and competitor analysis
    Grants on the Web (GOTW) Legacy register of MRC-administered grants, fellowships and training grants, filterable by institution Static; predates the UKRI merger Institution-level historical lookups
    Board and panel outcomes Score out of ten and funding decision for every application discussed at a given meeting Usually within four weeks of each meeting Competitive positioning within a specific funding round
    Archived spreadsheet and success-rate data Award listings April 2006–December 2019 and pre-2018 success-rate summaries Frozen, held on the UK Government Web Archive Long-run trend analysis

    For most benchmarking work, Gateway to Research and the board and panel outcomes pages should be the primary pair: the former gives the awarded portfolio, the latter gives the competitive context each award was won against.

    How to read board and panel outcomes for benchmarking

    MRC scores every application from one to ten, with ten the best, and this scoring structure applies across all types of MRC funding meeting. Applications are then listed in numerical order within blocks according to their median score group and funding decision, according to UKRI’s published board and panel outcomes guidance.

    Outcomes are usually published within four weeks of a meeting, though UKRI notes this can sometimes take longer. Crucially, applications that are unsuccessful after an earlier shortlisting stage are not discussed at the funding meeting and are therefore not included in board and panel outcomes at all — a data-quality point that matters enormously for anyone computing a success rate, since the visible denominator understates total submissions.

    • Score and decision are recorded per application, not per institution, so institution-level rates must be aggregated manually.
    • Shortlisting-stage rejections are invisible in this dataset — factor this into any success-rate calculation.
    • Full award detail (value, abstract, classification) only appears on Gateway to Research once the grant has actually started.

    How to benchmark success rates and competitor institutions correctly

    UKRI states explicitly that funding decisions are made “in circumstances unique to each panel meeting” and that the funding cut-off is dependent on the budget available at that specific meeting — not a fixed quality threshold. UKRI’s guidance is direct: institutions should not compare funding cut-off points made in different meetings, and UKRI will not consider challenges or enquiries based on such comparisons.

    This has a practical consequence for benchmarking: a proposal scoring 7/10 that was funded in a budget-flush round and a proposal scoring 8/10 declined in a tighter round are not evidence that the second panel was harsher. A robust competitor-analysis method therefore favours relative, within-round comparisons — an institution’s share of awards made at a given meeting, or across a given scheme over several rounds — over any single cross-period success-rate percentage pulled from a headline figure.

    Combining Gateway to Research (what was funded), board and panel outcomes (how competitive that round was), and GOTW’s institution filter (a second, independent cross-check for MRC-specific awards) gives a defensible three-source method rather than a single-source snapshot.

    Common questions on reading the MRC register

    How do I search MRC grants awarded by institution?

    Use Grants on the Web (GOTW), the legacy register hosted at gotw.nerc.ac.uk, and filter by “Institution > Medical Research Council (MRC)”; each project links to the full grant record, including principal investigator and value. For more current, cross-council records, Gateway to Research offers the same institution-level filtering.

    Where can I find MRC board and panel outcomes?

    UKRI publishes MRC’s board and panel outcomes in the “What MRC has funded” section of ukri.org, usually within four weeks of each funding meeting. Outcomes list every application discussed, its score out of ten and its funding decision, allowing panel-by-panel benchmarking rather than reliance on one headline figure.

    Is there a live MRC grants search tool?

    Gateway to Research is UKRI’s live, searchable database of funded projects across all seven research councils, updated continuously as grants start. Grants on the Web remains a parallel legacy tool for MRC-administered awards, useful for cross-checking older or training-grant records.

    Can I compare MRC funding cut-off scores between panel meetings?

    No — UKRI explicitly advises against this. Each meeting’s funding cut-off depends solely on the budget available at that specific meeting, not a fixed quality bar, so scores funded in one round and declined in another are not directly comparable as evidence of relative panel rigour.

    Implications for research offices and what happens next

    For research administration and funding-intelligence teams, the practical implication is that MRC grants-awarded data supports rigorous benchmarking only when the three sources are triangulated and UKRI’s own comparability caveats are respected. A single downloaded spreadsheet or a bare success-rate percentage, taken in isolation, will systematically misrepresent competitive position because of the shortlisting-stage exclusion and the meeting-specific funding cut-off.

    UKRI last updated its board and panel outcomes guidance on 3 March 2026 and its “What MRC has funded” summary page on 29 September 2025, and continues to migrate historical reporting into Tableau-based dashboards — most recently for 2025 panel outcomes and attendance. Institutions building recurring funding-intelligence dashboards should expect this format to keep evolving, and should re-check source URLs each reporting cycle rather than hard-coding links to any single spreadsheet. Research administration teams that build this triangulated method once can reuse it across other UKRI councils, since board and panel outcomes reporting now follows a common structure council-wide.

  • UKRI Grant Tracker vs Funding Finder: Which to Use

    The UKRI grant tracker — officially named Gateway to Research (GtR) — is UKRI’s public, post-award database of funded projects, while Funding Finder is the pre-award tool for discovering open competitions. Use GtR to see what has already been funded and by whom; use Funding Finder to find and apply for a live opportunity. Confusing the two wastes time at both ends of the grant lifecycle.

    Gateway to Research is UKRI’s searchable record of research and innovation projects it has already funded, spanning UKRI’s seven research councils, Research England and Innovate UK.

    What Is the UKRI Grant Tracker (Gateway to Research)?

    Gateway to Research (GtR), hosted at gtr.ukri.org, is UKRI’s public gateway onto publicly funded research. It is a retrospective, analytical tool, not a submission portal: researchers, administrators and journalists use it to look up who has already received UKRI funding, for what, and with which collaborators.

    GtR supports structured search syntax rather than a simple keyword box. Search terms can be combined with capitalised Boolean operators — AND, OR, and by implication exclusion logic — and exact phrases can be isolated by wrapping them in quotation marks (for example, “big data”). This makes GtR closer to a bibliometric research tool than a funding-opportunity search engine, and it is the correct destination when the underlying question is “who funds this kind of work” rather than “how do I apply for funding.”

    • Records cover projects across all seven UKRI research councils, Research England and Innovate UK.
    • Each project record can include the funded organisation, the named investigators, and linked outputs where reported.
    • GtR is read-only: it has no application or sign-in function, and cannot be used to submit a bid.

    What Is UKRI Funding Finder and How Does It Differ?

    UKRI Funding Finder, at ukri.org/opportunity, is the live, forward-looking search tool for current and upcoming funding competitions. Where GtR looks backwards at what has already been awarded, Funding Finder looks forwards at what can still be applied for. Each listing states eligibility criteria, assessment approach, and — increasingly — whether the call is open to all applicants or restricted to invited organisations.

    At the time of research for this article, Funding Finder listed 124 open opportunities across UKRI’s councils, spanning fields from quantum computing hardware to obesity research and zero-emission vehicle manufacturing. Listings can be sorted by publication date, opening date or closing date, and results can be followed via an RSS feed for teams monitoring a discipline continuously. Opportunities that closed before 20 September 2020 are not held on the live site; UKRI directs users to the UK Government Web Archive for that historical record — a detail that matters for administrators auditing older award terms.

    Which Tool Should You Use at Each Stage of the Grant Lifecycle?

    The two tools map cleanly onto opposite ends of the grant lifecycle. Funding Finder belongs to the pre-award, opportunity-scouting stage; GtR belongs to the post-award, evidence and landscape-analysis stage. Treating them as interchangeable is the single most common source of wasted searches reported by research office staff.

    Grant lifecycle stage Correct tool Primary purpose Typical user
    Scoping a new proposal Funding Finder Find open competitions, deadlines, eligibility Principal investigators, research development staff
    Benchmarking success rates or prior awards in a field Gateway to Research (GtR) Analyse what UKRI has already funded and where Research strategy and analysis teams
    Preparing and submitting an application UKRI Funding Service Complete, submit and track an application through assessment Applicants and research office administrators
    Identifying potential collaborators or reviewers Gateway to Research (GtR) Search funded projects by investigator or organisation Principal investigators, partnership teams
    Reporting institutional funding landscape to leadership Gateway to Research (GtR) Extract award data and trends across councils Research administrators, PVC Research offices

    In practice, a full application cycle touches all three UKRI digital services in sequence: Funding Finder to find the call, the UKRI Funding Service to submit and monitor the application, and GtR afterwards — both to check the eventual public record of the award and to inform the next round of proposal scoping.

    Where Does the UKRI Funding Service Fit In?

    The UKRI Funding Service, at funding-service.ukri.org, is a third, distinct property that is frequently conflated with both GtR and Funding Finder. It is the sign-in application portal: the system used to prepare, submit and monitor a funding application once a suitable opportunity has been identified via Funding Finder.

    Administrators searching for uk research and innovation ukri funding service are usually trying to reach this sign-in and case-tracking system, not the public search tools. This is a navigational query, and getting the destination wrong at this stage delays submission rather than discovery — a costlier mistake than a slow search on GtR or Funding Finder.

    • Funding Finder — discover the opportunity (no account needed).
    • UKRI Funding Service — sign in, complete the form, submit, and track assessment status (account required).
    • Gateway to Research — see the public record once the award is live (no account needed).

    Common Questions About UKRI’s Grant Tools

    What is the UKRI grant tracker used for?

    The UKRI grant tracker, Gateway to Research, is used to look up already-funded projects across UKRI’s councils, Research England and Innovate UK. Research offices use it for landscape analysis, benchmarking prior awards in a field, and identifying named investigators or partner organisations before submitting a related proposal.

    Is UKRI Funding Finder the same as Gateway to Research?

    No. Funding Finder lists open, forward-looking competitions for researchers still seeking funding, while Gateway to Research is a retrospective public database of projects UKRI has already awarded. They serve opposite ends of the same lifecycle and are maintained as separate services with separate URLs.

    How do I track a UKRI grant after it has been awarded?

    Once a grant is live, its public record — including the funded organisation and lead investigator — typically appears on Gateway to Research. Day-to-day case management, reporting obligations and correspondence for an active award are instead handled through the UKRI Funding Service account, not GtR.

    Do I need an account to search UKRI Funding Finder?

    No account is required to browse or search Funding Finder listings, including filtering by opening or closing date. An account on the separate UKRI Funding Service is only required at the point of actually starting, saving or submitting an application.

    Key Takeaways for Research Administrators

    The practical rule is straightforward: search Funding Finder for what can still be won, consult Gateway to Research for what has already been won, and use the UKRI Funding Service to actually submit and manage the application in between. Bookmarking all three separately — rather than treating “the UKRI grant tracker” as a single catch-all site — removes the single most common navigation error research offices report when supporting first-time applicants.

    As UKRI continues to consolidate its digital services, research administration teams should expect closer integration between these platforms, but the underlying separation of pre-award discovery, application management and post-award transparency is unlikely to disappear, since each serves a distinct statutory and operational purpose. Institutions building internal guidance for applicants — as part of broader research administration support — should signpost all three tools explicitly rather than defaulting to whichever one appears first in a search engine.

  • Research Misconduct vs Misbehaviour: FFP vs QRPs

    Research misconduct is a narrow, formally sanctionable transgression — fabrication, falsification, or plagiarism (FFP) committed intentionally, knowingly, or recklessly — while research misbehaviour is the much broader, informally policed category of questionable research practices (QRPs) that fall short of that threshold but still corrode trust in the research record. Confusing the two matters: one triggers a formal investigation and possible dismissal or retraction; the other typically triggers correction, training, or an editorial note.

    This distinction between research misbehavior and research misconduct is not academic hair-splitting. Regulators, universities, funders, and journal editors all apply a threshold test before they open a formal case, and where that line sits differs by jurisdiction. Research misconduct is fabrication, falsification, or plagiarism in proposing, performing, reviewing, or reporting research, committed with intent, knowledge, or recklessness — a definition codified in the United States under 42 CFR Part 93 and echoed, with local variation, across UK, European, and international frameworks.

    What is research misconduct? The formal FFP test

    Research misconduct has a narrow, legalistic definition. In the United States, the Office of Research Integrity (ORI) — part of the Department of Health and Human Services — defines it under 42 CFR Part 93 as fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. Each term is precisely scoped: fabrication is making up data or results and recording or reporting them; falsification is manipulating research materials, equipment, or processes, or changing or omitting data so the research record is misrepresented; plagiarism is appropriating another person’s ideas, processes, results, or words without appropriate credit.

    Crucially, ORI’s definition explicitly excludes honest error or genuine differences of opinion. A finding of misconduct also requires that the act was committed intentionally, knowingly, or recklessly — not through a documented, defensible mistake. This intent threshold is what separates misconduct from misbehaviour, and it is the single fact most competitor explainers state without ever mapping it against a second jurisdiction.

    What is research misbehaviour? Where QRPs fit

    Research misbehaviour is an umbrella term for actions that deviate from responsible research practice without meeting the fabrication-falsification-plagiarism bar. It is most often used interchangeably with “questionable research practices” (QRPs) — a term formalised in the UK’s Concordat to Support Research Integrity, first published by Universities UK in 2012 and revised in 2019, which defines QRPs as “minor infractions or research practices, including avoidable errors, which fall short of the definition of intentional research misconduct.”

    Common QRPs include selective reporting of favourable results, “p-hacking” data until a significant finding emerges, HARKing (presenting a post-hoc hypothesis as though it were pre-registered), salami-slicing a single dataset into multiple papers, and inappropriate authorship allocation. A 2009 meta-analysis by Daniele Fanelli, published in PLoS ONE, found that on average only 1.97% of surveyed scientists admitted to fabricating or falsifying data at least once — but up to 33.7% admitted to other questionable research practices, and the figure rose sharply when respondents were asked about colleagues’ behaviour rather than their own. That roughly seventeen-fold gap is the empirical case for treating misbehaviour as a distinct, much larger risk surface than misconduct.

    Authorship disputes sit squarely in this grey zone. CASRAI originated the CRediT contributor role taxonomy in 2014. The standard is now stewarded by NISO as ANSI/NISO Z39.104-2022, and consistent use of its CRediT contributor roles is one of the more effective structural fixes institutions have for the ghost- and guest-authorship misbehaviours that recur in authorship disputes.

    How do regulators draw the line?

    No single global definition governs the misconduct/misbehaviour boundary. Each major framework sets its own threshold language, and the differences are consequential for cross-border collaborations and multi-national author teams.

    Framework / body Core threshold language Legal or policy basis Standard of intent
    US Office of Research Integrity (ORI) Fabrication, falsification, or plagiarism (FFP) 42 CFR Part 93 Intentional, knowing, or reckless
    UK Concordat to Support Research Integrity “Behaviours that deliberately or recklessly fall short of the standards expected” Universities UK Concordat (2012, rev. 2019) Deliberate or reckless
    World Health Organization “Wrongdoing” — FFP plus misrepresentation and other fraudulent behaviour WHO Code of Conduct for Research Intentional, knowing, or reckless
    Committee on Publication Ethics (COPE) Overlapping guidance distinguishing retraction-triggering misconduct from correction-triggering QRPs COPE flowcharts and guidelines for editors Proportionate to severity and evidence

    Notice the pattern: every framework anchors misconduct to intent or recklessness, and every framework treats everything short of that — errors, sloppy practice, grey-zone shortcuts — as a separate, lower-tier category, whether it is called a QRP, an “avoidable error,” or simply “wrongdoing” of a lesser kind.

    What happens after a finding? Sanctions compared

    The practical consequence of the misconduct/misbehaviour distinction is procedural. A misconduct finding typically follows a formal, panel-based investigation and can result in retraction, funding debarment, employment termination, or referral to a professional regulator. A misbehaviour or QRP finding more commonly results in a correction to the published record, mandatory training, enhanced supervision, or an editorial expression of concern — remedial rather than punitive action.

    • Misconduct outcomes: retraction, debarment from funding, dismissal, professional sanction, referral to law enforcement in extreme cases.
    • Misbehaviour/QRP outcomes: correction or erratum, mandatory research-integrity training, revised authorship credit, closer supervisory oversight.
    • Shared consequence: both can damage institutional reputation and require correction of the scholarly record, which is why UKRIO and equivalent bodies investigate both under a shared procedural umbrella even though the findings differ.

    Research institutions and research administration offices increasingly triage complaints against this two-tier structure before deciding whether a matter warrants a full misconduct panel or a lighter-touch integrity review — a proportionality principle that COPE explicitly recommends to journal editors handling post-publication concerns.

    Common questions about misconduct and misbehaviour

    What are the three types of research misconduct?

    Under the US federal definition, the three types are fabrication (inventing data or results), falsification (manipulating processes or altering data so the record misrepresents what occurred), and plagiarism (appropriating others’ ideas, words, or results without credit). Together these form the FFP standard used by ORI and mirrored internationally.

    What are the five unethical practices most often cited in research ethics literature?

    A widely cited framework lists falsification of data, failure to credit others, plagiarism, undisclosed conflicts of interest, and biased design or interpretation driven by outside influence. Some of these meet the formal misconduct threshold; others, like undisclosed conflicts, more often sit in the misbehaviour category depending on intent and severity.

    What is research misbehaviour, precisely?

    Research misbehaviour is any deviation from responsible research conduct — including questionable research practices and avoidable errors — that falls short of intentional fabrication, falsification, or plagiarism. It is a broader, less formally policed category than misconduct, typically addressed through correction and training rather than disciplinary panels.

    What actions count as research misconduct in UK institutional policy?

    UK institutional policies, following the Concordat to Support Research Integrity, typically list plagiarism, fabrication, falsification, breaching ethical or legal research requirements, proceeding without required approvals, and failing to manage conflicts of interest as research misconduct, provided the conduct was deliberate or reckless rather than an honest error.

    Implications for institutions and research administrators

    For research administrators, publishers, and funders, the practical task is triage: distinguishing an honest error or a QRP from conduct that meets the intent threshold for a formal misconduct investigation, before committing to a resource-intensive panel process. Institutions that document this distinction clearly in their code of practice — and train staff and early-career researchers on where the line sits — reduce both the number of misdirected formal investigations and the risk of under-reacting to genuine misconduct.

    As research-integrity offices, funders, and publishers converge on shared vocabulary for this spectrum, consistent taxonomy work — from CRediT-style contributor attribution to standardised institutional definitions — will keep doing more to prevent misbehaviour from escalating into misconduct than any single enforcement action can.

  • ACM Open Access vs Plan S: 2026 Compliance Check

    ACM open access is now the default, not an option: since 1 January 2026 the Association for Computing Machinery publishes all journals, conference proceedings and magazines under a fully open-access model, replacing its previous hybrid Read & Publish arrangement. Under the CC BY licence, zero-embargo release and author-retained copyright that now apply across the ACM Digital Library, the model satisfies cOAlition S’s Plan S licensing, immediacy and rights-retention requirements — closing a compliance gap that existed while ACM operated as a transformative agreement.

    ACM Open is the Read & Publish framework through which participating institutions pay a fixed annual fee, based on their average publishing output over the previous three years, in exchange for unlimited open-access publishing by their corresponding authors and full institutional read access to the ACM Digital Library.

    What is ACM open access?

    As of 1 January 2026, ACM transitioned every journal, magazine and conference proceeding in the ACM Digital Library to full open access, removing the mixed subscription/hybrid model that had applied since the ACM Open programme launched in 2020. The ACM Digital Library itself was split into two tiers on the same date: a free Basic edition giving open access to ACM’s full published corpus, and a paid Premium edition adding discovery tools, usage metrics, citation management and the ACM Guide to Computing Literature.

    Institutional participation still runs through ACM Open, ACM’s Read & Publish framework. Corresponding authors at a subscribing institution publish an unlimited number of open-access articles without paying an article processing charge (APC) directly; the institution instead pays one fixed annual fee tied to its historical publishing volume. Authors at non-participating institutions can still publish open access but may be liable for an APC.

    What does Plan S actually require?

    Plan S is the funder-driven open-access mandate coordinated by cOAlition S, a consortium of national and charitable research funders including UKRI, Wellcome and members of the European Research Council network. It sets three non-negotiable conditions for compliant publication, in force since the policy’s 2021 implementation date:

    • Licensing — the published article must carry a Creative Commons Attribution (CC BY) licence, or an equivalent that permits free reuse, as a default condition.
    • Immediacy — there can be no embargo period; the Version of Record, or an accepted manuscript carrying the same licence, must be open at the moment of publication.
    • Rights retention — authors, not publishers, must retain the rights needed to comply, formalised in cOAlition S’s Rights Retention Strategy (RRS), which lets funded authors apply a CC BY licence to their accepted manuscript regardless of the publisher’s own copyright terms.

    cOAlition S also phased out support for hybrid and transformative-journal routes: funding for APCs in hybrid subscription journals was withdrawn after 2024, meaning publishers relying on transformative agreements needed to complete a full flip to open access to remain straightforwardly fundable under Plan S.

    Does ACM Open satisfy cOAlition S requirements?

    Measured against each Plan S condition, ACM’s current model clears the bar directly rather than through a transitional workaround. The table below maps ACM’s terms to the three cOAlition S requirements.

    Plan S requirement ACM Open / ACM Digital Library position
    CC BY licence by default CC BY is the default licence under ACM Open; authors may select an alternative Creative Commons licence such as CC BY-NC-ND where a funder permits it.
    No embargo (immediacy) Zero embargo — the Version of Record is openly accessible in the ACM Digital Library at the point of publication for every ACM title.
    Author/institution rights retention ACM ceased requiring copyright transfer from authors; authors grant ACM a non-exclusive licence to publish rather than assigning copyright, satisfying the Rights Retention Strategy.
    Sustainable, transparent cost model ACM Open’s Read & Publish fee is fixed for the agreement term and based on three-year historical output, giving institutions a predictable APC-equivalent cost.

    The practical effect for a cOAlition S-funded computer scientist is that publishing in an ACM venue no longer requires checking whether a specific journal is “transformative” or tracking an embargo clock — the open-access, CC BY, zero-embargo position now applies uniformly across the ACM catalogue.

    What happened to ACM’s transformative agreements?

    Before the January 2026 flip, ACM Open operated as a transformative agreement: a Read & Publish deal under which subscription revenue was gradually redirected toward open-access publishing, with the expectation that the journal portfolio would eventually convert fully to open access. UK higher-education institutions negotiated ACM Open terms through Jisc, whose subscriptions catalogue still lists the prior “ACM OPEN Journals 2023-2025” agreement as the precursor arrangement that libraries used to budget for the transition.

    ACM’s own SIGGRAPH leadership signalled the scale of this shift well in advance: in a June 2024 community Q&A, ACM SIGGRAPH chair Jonathan Aldrich stated that ACM anticipated 60-65% or more of authors would already be covered by institutional open-access agreements by the time of the full transition, with the remainder needing an author-paid or waiver route. That anticipated coverage gap is precisely what the January 2026 full flip was designed to close, since every article — not just those from ACM Open institutions — is now open access regardless of the author’s institutional agreement status.

    What this means for institutions and researchers

    For research administrators tracking funder compliance, ACM’s flip removes a recurring due-diligence step: computer-science output published with ACM no longer needs an individual title-by-title check against a cOAlition S-approved transformative journal list, because the requirement is now met at the publisher level. Institutions still weighing whether to join ACM Open should note that the Read & Publish fee is separate from open-access compliance itself — declining to subscribe does not make an ACM article closed, but it may shift APC liability onto individual authors or their grants.

    For authors publishing under UKRI, Horizon Europe or other cOAlition S-aligned funder mandates, the practical takeaway is that ACM venues can now be selected on scholarly merit without a separate compliance audit — a meaningful simplification for research administrators supporting authors across computing, information systems and related interdisciplinary fields.

    Frequently asked questions

    What is ACM open access?

    ACM open access refers to ACM’s publishing model, under which, as of January 2026, all ACM journals, conference proceedings and magazines are freely accessible with no reader-side subscription barrier. Authors retain copyright and publish under a CC BY licence by default, typically funded through their institution’s ACM Open Read & Publish agreement rather than a per-article fee.

    Is ACM open access free for readers?

    Yes. The ACM Digital Library’s Basic edition gives free, open-access reading of ACM’s full published corpus. A separate paid Premium edition exists, but it adds discovery and analytics tools rather than gating access to the research articles themselves.

    Does ACM’s open-access model satisfy Plan S?

    Yes. ACM’s default CC BY licence, zero-embargo release of the Version of Record, and author rights retention policy together meet all three of cOAlition S’s core Plan S conditions, without relying on a transformative-agreement exception.

    What licence does ACM Open use?

    ACM Open’s default licence is CC BY (Creative Commons Attribution), which permits free reuse with attribution and satisfies cOAlition S’s licensing requirement. Authors may request an alternative Creative Commons licence, such as CC BY-NC-ND, where their funder’s terms allow it.

    Looking ahead

    ACM’s move puts one of computing’s two dominant scholarly publishers — alongside IEEE, which retains a hybrid subscription model for most titles — fully inside the Plan S compliance perimeter without caveats. For funders and institutions monitoring discipline-specific open-access uptake, ACM’s flip is a useful signal that field-specific societies can complete a full transition to open access while keeping a Read & Publish fee structure recognisable to library budgets. Research administrators supporting computer-science authors should update internal compliance checklists to reflect that ACM no longer requires case-by-case verification against transformative-journal criteria.

  • PMC Open Access Subset vs Plan S: Not the Same

    The PMC Open Access Subset and Plan S are not the same thing. The PMC Open Access Subset is a licensing classification inside PubMed Central (PMC) that flags which archived articles carry reuse-permitting licences for text mining and redistribution. Plan S is a funder mandate from cOAlition S that requires immediate open access publication of funded research. One is a repository filter; the other is a compliance requirement — and confusing them leads authors to think a PMC listing satisfies a funder’s open access policy when it may not.

    The PMC Open Access Subset is the portion of PubMed Central’s full-text archive made available under Creative Commons or similar licences that permit reuse beyond reading, including text mining and redistribution. This distinction — repository versus mandate — is the source of a persistent mix-up among authors preparing to comply with funder open access requirements.

    What Is the PMC Open Access Subset?

    The PMC Open Access Subset is maintained by the U.S. National Library of Medicine (NLM), part of the National Institutes of Health (NIH). It contains articles and preprints made available under machine-readable licences — Creative Commons or similar — that permit reuse beyond simple reading access.

    NLM groups the subset into three licence tiers:

    • Commercial Use Allowed — CC0, CC BY, CC BY-SA, CC BY-ND licences
    • Non-Commercial Use Only — CC BY-NC, CC BY-NC-SA, CC BY-NC-ND licences
    • Other — no machine-readable licence, no licence, or a custom licence, with restricted redistribution on the PMC Cloud Service

    As of the NIH’s most recent update, the subset spans well over 3.4 million journal articles and preprints, retrievable via the PMC FTP Service, Cloud Service, OAI-PMH Service, or BioC API. Not every article in PMC belongs to the Open Access Subset — many PMC-hosted articles remain under standard copyright and are excluded from bulk text-mining retrieval.

    This is a critical, frequently missed distinction: PMC itself (the archive) and the NIH Public Access Policy (which mandates deposit of NIH-funded manuscripts into PMC) are separate from the Open Access Subset (the licensing classification). An article can be freely readable in PMC under the Public Access Policy while still sitting outside the Open Access Subset, because it lacks a reuse-permitting licence.

    What Is Plan S?

    Plan S is a funder-driven open access initiative launched in September 2018 by cOAlition S, a coalition of national and international research funders including UKRI, Wellcome, and members of the European Commission’s Horizon Europe programme. It requires that peer-reviewed publications arising from funded research be made immediately and fully open access, with no embargo period.

    Under Plan S principles, compliant publication routes include:

    • Publishing in a fully open access journal or platform
    • Publishing in a subscription journal while depositing the accepted manuscript in an open access repository immediately on publication (the “Rights Retention Strategy”)
    • Publishing on an open access platform or in a repository that meets cOAlition S technical requirements

    cOAlition S states that authors or their institutions should retain copyright, and that a Creative Commons Attribution (CC BY) licence is the preferred licence type. Compliance is assessed against funder-specific policy terms, not against any single repository’s inclusion criteria.

    PMC Open Access Subset vs Plan S: Key Differences

    The clearest way to separate these two is by function: a repository classification versus a funder policy. The table below sets this alongside a third commonly conflated mechanism — the United States’ federal public access requirement — since UK and international researchers frequently encounter all three in the same compliance conversation.

    Feature PMC Open Access Subset Plan S US federal public access mandate
    Nature Repository licensing classification Funder policy mandate Federal agency policy (via OSTP)
    Governing body National Library of Medicine (NIH) cOAlition S funders Office of Science and Technology Policy (OSTP)
    What it governs Reuse rights of archived articles Where/how funded research is published Timing of public access to federally funded research
    Embargo position Not applicable — licence-based, not time-based Zero embargo required from 2021 Zero embargo required by 31 December 2025 (OSTP’s 2022 Nelson Memo)
    Geographic scope Global archive, US-hosted Primarily European and international funders United States federal agencies
    Enforcement mechanism None — it is a content filter, not a compliance check Funder grant conditions Agency public access plans

    The overlap that causes confusion: research funded under Plan S can end up in the PMC Open Access Subset if it carries a qualifying licence, but Plan S compliance is judged by the funder against its own policy terms, not by whether NLM has classified the article into the subset.

    Does Plan S Compliance Require the PMC Open Access Subset?

    No. Plan S does not name the PMC Open Access Subset as a compliance route. cOAlition S funders accept publication in a compliant journal, an institutional or subject repository meeting technical requirements, or immediate deposit of the accepted manuscript under an approved licence. PMC is one possible repository destination for biomedical research, but Plan S compliance is assessed by licence terms and embargo length, not by NLM’s internal subset classification.

    Authors publishing biomedical research funded by a cOAlition S member should check the funder’s own open access policy and, separately, confirm whether their institution or publisher will additionally deposit the manuscript into PMC. These are two distinct actions that happen to intersect for US-relevant biomedical literature, not one unified process.

    Common Questions

    What is PMC open access?

    PMC open access refers to the PMC Open Access Subset, the portion of PubMed Central archived under licences — typically Creative Commons — that permit reuse, including text mining and redistribution. It is not a funder policy; it is a licensing classification applied to specific articles already deposited in PMC.

    Are PMC and PubMed the same?

    No. PubMed is a database of citations and abstracts, while PMC (PubMed Central) is a full-text archive of biomedical journal articles. Both are maintained by the National Library of Medicine, but PubMed indexes metadata, whereas PMC stores the complete article text, of which only a subset carries reuse licences.

    Is PMC free to use?

    Yes, reading PMC articles is free. However, reuse rights differ by article: NLM states that PMC provides long-term preservation and free reading access, but text mining or redistribution beyond fair use requires the article to carry a qualifying licence within the Open Access Subset — free-to-read is not the same as free-to-reuse.

    Implications for Authors and Institutions

    For authors, the practical takeaway is definitive: satisfying a funder’s Plan S obligation and appearing in the PMC Open Access Subset are two separate compliance checks. Meeting one does not automatically satisfy the other. Institutional research administration teams tracking funder compliance should verify licence type, embargo length, and deposit location independently for each requirement, rather than treating “it’s in PMC” as proof of open access mandate compliance.

    For publishers and repository managers, the distinction matters for metadata accuracy: an article’s PMC Open Access Subset licence tag should be checked and communicated separately from any funder compliance statement attached to the same article.

    Looking ahead, the gap between these mechanisms is narrowing. The US federal government’s move toward zero-embargo public access by the end of 2025, alongside Plan S’s established zero-embargo requirement since 2021, signals convergence on immediate access as the global norm — even though the underlying legal and technical mechanisms (funder mandate versus repository licence versus agency policy) remain distinct and will continue to require separate verification.

  • Journal Finder Tools Compared for Plan S Authors

    Springer, Elsevier, Wiley and Taylor & Francis each run a free journal finder that matches a manuscript’s title, abstract or keywords to journals in their own portfolio — but none of them checks Plan S open-access compliance. That verification step belongs to cOAlition S’s separate Journal Checker Tool, which authors should run after shortlisting journals, not instead of it.

    A journal finder is a publisher-run search tool that recommends candidate journals for a manuscript by matching its subject area, title or abstract text against that publisher’s own list of active titles. This distinction matters more than it first appears: a Plan S-funded author who only uses a publisher’s finder can end up with a well-matched journal that is not, in fact, a compliant venue for their grant.

    What Do Publisher Journal Finder Tools Actually Do?

    Every major publisher-run journal finder performs the same core function: it takes a manuscript’s title, abstract or keywords and returns a ranked list of journals from that publisher’s own portfolio likely to fit the manuscript’s scope. None of them search across competing publishers, and none independently verify a journal’s open-access route against a specific funder’s mandate.

    • Input is usually a title, abstract or a short set of keywords, sometimes with a subject-area filter.
    • Output is a ranked shortlist, often annotated with impact metrics, acceptance rate or review speed.
    • Coverage is limited to titles the publisher itself owns or manages — this is the single biggest limitation for cross-publisher comparison shopping.

    How Do Springer, Elsevier, Wiley and Taylor & Francis Compare?

    Elsevier’s Journal Finder lets authors search by journal title, subject area or aims and scope, or run a “match my abstract” search against Elsevier’s own journal list. Springer Nature’s Journal Suggester, reached via the Springer Nature Link journals hub, matches manuscript details against the combined Springer, Nature, BMC and Palgrave Macmillan portfolio and surfaces open-access funding options alongside journal suggestions. Wiley’s Journal Finder states on its own page that it lets authors “search and filter across 1,800+ journals” by keyword, subject or abstract match. Taylor & Francis’s Journal Suggester, hosted on its Author Services site, uses a short five-question, AI-assisted form to recommend titles from the Taylor & Francis and Routledge list.

    Tool Provider Input method Portfolio scope Checks Plan S compliance? Best for
    Journal Finder Elsevier Title/abstract match, subject/scope search Elsevier’s own journals No Fast shortlisting within Elsevier imprints
    Journal Suggester Springer Nature Title, abstract or keyword input Springer, Nature, BMC, Palgrave Macmillan No (shows OA funding options, not funder-mandate checks) Authors targeting Springer Nature imprints
    Journal Finder Wiley Keyword, title or abstract search, with filters 1,800+ Wiley journals Partial — separate Wiley Author Compliance Tool checks funder policy Discipline-specific filtering within Wiley’s list
    Journal Suggester Taylor & Francis Five-question AI-assisted form Taylor & Francis / Routledge portfolio No Quick AI-generated shortlist
    Scopus Source Search Elsevier (Scopus) Lookup by ISSN or title, not manuscript matching Scopus-indexed sources, cross-publisher No Verifying CiteScore or indexing status of a journal already in mind
    Journal Checker Tool cOAlition S Funder, institution and journal input Any journal, cross-publisher Yes — this is its sole purpose Confirming a compliant open-access route before submission

    Does Scopus Have Its Own Journal Finder?

    Scopus, Elsevier’s abstract-and-citation database, does not run a manuscript-matching journal finder in the way Elsevier, Springer Nature, Wiley or Taylor & Francis do. Its Scopus Source Search instead looks up journals you already have in mind, by ISSN or title, to confirm indexing status and metrics such as CiteScore.

    Authors who search “journal finder scopus” are usually trying to do one of two different things, and conflating them causes wasted time. If the goal is to discover new candidate journals for a manuscript, a publisher’s own finder (or a cross-publisher tool such as JournalGuide) is the right starting point. If the goal is to confirm that a journal you have already chosen is Scopus-indexed, Scopus Source Search is the correct tool, not a substitute for journal discovery.

    Do Any of These Tools Check Plan S Compliance?

    Not directly, with one partial exception. Plan S, launched by cOAlition S in 2018 and taking effect for grants awarded from 2021, requires that publications from funded research appear in a fully open-access journal, on a compliant platform, or via a transformative arrangement recognised by the funder. Publisher journal finders match content to scope; they do not check a specific funder’s mandate against a specific journal’s business model.

    Wiley is the partial exception: alongside its Journal Finder, it offers a separate Author Compliance Tool that checks whether a given Wiley journal’s policies align with a named funder’s requirements. For every other publisher listed above, compliance checking sits outside the finder entirely.

    The authoritative cross-publisher tool is cOAlition S’s Journal Checker Tool (JCT). It requires three inputs — the author’s cOAlition S funder, their institution, and the intended journal — and returns whether that journal offers a Plan S-compliant route: full open access, a transformative agreement, or a self-archiving right that satisfies the funder’s policy. Authors should treat this as a mandatory second step after shortlisting journals with a publisher finder, never as an optional extra.

    Self-archiving (green open-access) rights specifically were historically checked via Sherpa/RoMEO. That lookup function has since migrated into Jisc’s Open Policy Finder, which now performs the same self-archiving and copyright policy search that Sherpa/RoMEO ran for over two decades, and remains a useful companion to the JCT when a transformative agreement is not available. Research administration teams tracking institutional compliance across multiple funders often run the JCT and Open Policy Finder together as a two-step check before an author submits.

    Common Questions From Plan S Authors

    Is Wiley JournalFinder free to use?

    Yes. Wiley’s Journal Finder is a free public tool at wiley.com that lets authors search or filter across 1,800+ Wiley journals by keyword, subject area or manuscript abstract. No login or subscription is required to generate a shortlist, though saving results and using the separate Author Compliance Tool may require a free Wiley account.

    What are the alternatives to Wiley Journal Finder?

    Authors publishing outside Wiley can use Elsevier’s Journal Finder, the Springer Nature Journal Suggester, or the Taylor & Francis Journal Suggester, each matching a manuscript to that publisher’s own portfolio. Cross-publisher alternatives include JournalGuide and Scopus Source Search, though neither replaces a funder-specific Plan S compliance check.

    What is Sherpa Romeo mainly used for?

    Sherpa/RoMEO was historically used to check a journal’s self-archiving policy — whether authors could deposit a preprint, accepted manuscript or published version in a repository. Its self-archiving data has since migrated into Jisc’s Open Policy Finder, which now performs the same green open-access policy lookup for Plan S authors.

    Is Wiley better than Elsevier?

    Neither is objectively “better” — each journal finder only searches that publisher’s own portfolio. Wiley’s tool covers 1,800+ titles with subject filters, while Elsevier’s adds an abstract-matching search across its list. The right choice depends on which publisher’s journals suit the manuscript’s discipline and the author’s funder requirements, not on the tool itself.

    For research administrators and institutional open-access teams, the practical takeaway is procedural rather than technical: publisher journal finders solve the discovery problem, but only a funder-aware checker like the JCT solves the compliance problem, and treating the two as interchangeable is the most common cause of post-acceptance compliance disputes. As more funders align with cOAlition S principles, expect publisher finders to integrate compliance flags directly — Wiley’s Author Compliance Tool is an early sign of that direction — but until that integration is universal, running a publisher finder followed by the Journal Checker Tool remains the safest two-step workflow for Plan S authors.

  • Predatory Journal Checker vs Plan S Compliance

    A Plan S compliant journal is not automatically screened by a predatory journal checker: Plan S tests open-access licensing and Directory of Open Access Journals (DOAJ) registration, not editorial integrity or peer-review conduct. The two checks answer different questions, and treating DOAJ/Plan S clearance as proof a journal is legitimate leaves a real compliance gap that research administrators need to close separately.

    A predatory journal checker is a tool, checklist, or reference list — such as the Think. Check. Submit. checklist, Cabells’ Predatory Reports, or the archived Beall’s List — used to test whether a journal’s peer review, editorial board, and fee practices are genuine rather than a vehicle for harvesting article-processing charges.

    What is a predatory journal checker?

    A predatory journal checker evaluates the operational and editorial conduct of a journal rather than its licensing terms. It looks at whether peer review actually happens, whether the editorial board is real and contactable, whether article-processing charges are disclosed upfront, and whether the publisher’s indexing claims can be verified.

    Common red flags that these tools and checklists are built to catch include:

    • Unsolicited, aggressive email invitations promising rapid publication
    • No transparent article-processing-charge (APC) schedule until after acceptance
    • An editorial board listing academics without their knowledge or consent
    • A journal scope so broad it covers unrelated disciplines
    • Fabricated or unverifiable impact-factor and indexing claims

    These are the criteria a checker tests. None of them is what Plan S compliance actually checks — which is the source of the confusion this article addresses.

    Does Plan S compliance screen for predatory journals?

    Not directly. Plan S is a funder mandate — led by cOAlition S — requiring that publicly funded research be published open access under specific licensing terms. Its technical requirements state that a fully open-access journal must be listed in the Directory of Open Access Journals (DOAJ), or apply for DOAJ listing within one year of publishing its first article, to count as a compliant venue.

    DOAJ listing is a proxy signal, not a predatory-publishing audit. cOAlition S guidance separately points authors toward the Think. Check. Submit. checklist for journal-selection due diligence — a clear indication that cOAlition S itself does not treat DOAJ/Plan S clearance as a substitute for a dedicated predatory check. Responsibility for the final journal-selection decision sits with the researcher and their institution, not with the funder’s compliance rule.

    DOAJ listing vs a dedicated predatory journal checker

    DOAJ vetting and a predatory journal checker overlap in intent — both aim to exclude disreputable venues — but they differ in scope, update frequency, and what they miss. DOAJ’s 2014–2016 re-application process is a useful illustration: it removed roughly 3,300 previously listed journals that failed revised inclusion criteria, which shows DOAJ listing is a snapshot assessment, not a continuously monitored guarantee.

    Mechanism What it verifies What it misses Best used for
    Plan S / DOAJ listing Open-access licence terms; baseline transparency criteria at time of listing Ongoing editorial conduct; peer-review quality after listing Confirming funder-mandate eligibility
    Predatory journal checker (Think. Check. Submit., Cabells, Beall’s archive) Editorial board authenticity, peer-review conduct, fee transparency Funder licensing compliance Author-level due diligence before submission
    Scopus / Web of Science journal check Active indexing status, citation metrics, discontinued-title flags Newer or non-English-language legitimate journals not yet indexed Cross-checking indexing claims a journal makes about itself
    Publisher/journal finder tools Journal-manuscript fit by scope and audience Legitimacy screening entirely — these tools assume the candidate pool is already vetted Narrowing a shortlist of already-verified journals

    What does a Scopus journal check add?

    A Scopus journal check confirms whether a title is actively indexed, flags titles that have been discontinued from Scopus for quality reasons, and surfaces citation-based metrics. This is a useful cross-check against a journal’s own indexing claims — predatory titles frequently claim indexing status they do not have — but Scopus coverage is not designed as a predatory-publishing screen and does not evaluate peer-review conduct directly.

    It is also asymmetric: a legitimate new journal may not yet be Scopus-indexed, so absence from Scopus is not itself proof of a predatory operation. Administrators should treat a Scopus check as one data point in a layered process, not a standalone verdict.

    How should administrators layer both checks?

    Institutions handling funder-mandate compliance and research-integrity screening as two separate workstreams should merge them into one journal-selection workflow. A practical sequence:

    1. Confirm funder eligibility first. Check DOAJ listing (or ROAD registration) to establish Plan S / open-access mandate compliance.
    2. Run a dedicated predatory check second. Apply the Think. Check. Submit. checklist, or consult Cabells’ Predatory Reports where the institution has a subscription, against the same candidate journal.
    3. Cross-check indexing claims. Verify any Scopus, Web of Science, or PubMed indexing the journal advertises against the indexing service’s own database.
    4. Escalate ambiguous cases to the institution’s research-integrity office or library scholarly-communications team rather than relying on a single automated pass/fail signal.
    5. Record the outcome in the researcher’s submission file, since funders and REF-style assessment exercises increasingly expect an audit trail of due-diligence steps, not just a final compliance flag.

    This sequencing matters because each mechanism fails differently: DOAJ/Plan S can clear a journal on licensing grounds while missing recent editorial decline; a predatory checker can flag conduct issues DOAJ has not yet caught up with; Scopus can catch a false indexing claim that neither of the other two checks is built to test.

    Common questions about predatory journal screening

    How do you check if a journal is predatory?

    Run the Think. Check. Submit. checklist against the journal, verify the editorial board members individually, confirm the article-processing charge is disclosed before submission, and cross-check any indexing claims (Scopus, DOAJ) directly against the indexing service rather than trusting the journal’s own website.

    What is a red flag for a predatory journal?

    Aggressive, unsolicited invitation emails promising unusually fast peer review are the most cited red flag. Other consistent signals include an editorial board that cannot be independently verified, a scope spanning unrelated disciplines, and article-processing fees disclosed only after acceptance.

    How do you check if a journal is reputable?

    Confirm active listing in DOAJ or an equivalent recognised index, verify the publisher belongs to COPE or a comparable ethics body, check that peer-review policy is published and specific, and confirm the editorial board’s affiliations independently rather than trusting journal-supplied contact details.

    What is considered a predatory journal?

    A predatory journal is one that charges publication fees while failing to provide the genuine editorial and peer-review services legitimate scholarly journals promise, prioritising revenue from article-processing charges over publication quality and research integrity, per definitions developed by COPE and reflected in Frandsen et al.’s peer-reviewed literature review.

    Implications and the path forward

    For institutional research offices, the practical implication is procedural: a single “is this journal Plan S compliant?” check cannot double as a research-integrity sign-off, and treating it that way creates audit risk when a funder or REF-style exercise later asks how a submission venue was verified. Layering a DOAJ/Plan S check with a dedicated predatory journal checker and an indexing cross-check is not duplicative effort — each step tests a distinct failure mode that the others do not cover.

    As open-access mandates expand and predatory operations grow more sophisticated at mimicking legitimate indexing and DOAJ-style transparency signals, the gap between funder-mandate compliance and editorial-integrity verification is likely to widen rather than close. Institutions that formalise the layered workflow now — rather than relying on DOAJ/Plan S status as an implicit predatory-publishing seal of approval — will be better positioned as funders tighten reporting expectations around journal-selection due diligence.

  • AI Act Regulation: Penalties for Research Bodies

    AI Act regulation penalises non-compliance on a three-tier scale: up to €35 million or 7% of global annual turnover for prohibited AI practices, up to €15 million or 3% for high-risk and general-purpose AI failures, and up to €7.5 million or 1% for supplying false information to regulators — whichever figure is higher in each case. For a university, spinout, or research consortium, the exposure is rarely the maximum headline number; it is the cost of misclassifying an admissions algorithm, an exam-proctoring tool, or a recruitment screen as “low risk” when the law says otherwise.

    The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) is the harmonised EU law setting risk-based obligations and penalties for AI systems, and it applies to research institutions as deployers whenever an AI system’s output affects people in the EU.

    What actually counts as an AI Act violation for a research institution?

    Universities and consortia rarely build the AI systems they use — they deploy them. Under the Act, a deployer is any organisation using an AI system in a professional capacity, and deployers carry real obligations even when a vendor built the underlying model. A learning-management platform that scores exam integrity, an HR tool that ranks job applicants, or an admissions filter all fall within scope if they touch people inside the EU, regardless of where the institution is based.

    Non-compliance is not a single offence. It spans failing to conduct a fundamental rights impact assessment, deploying an unregistered high-risk system, ignoring human-oversight requirements, or running a system the Act classifies as prohibited. Each failure mode sits on a different penalty tier.

    How much can an AI Act fine cost, tier by tier?

    Article 99 of Regulation (EU) 2024/1689 sets three fine bands. The final figure is whichever is higher — the flat euro cap or the percentage of worldwide annual turnover — which matters enormously for a university with a large total budget but a tiny AI-specific footprint.

    Violation type Maximum fine Turnover percentage Typical trigger for a research institution
    Prohibited AI practices (Art. 5) €35,000,000 7% Emotion-recognition in exams; covert biometric categorisation of students or staff
    High-risk system / GPAI obligation breaches €15,000,000 3% Recruitment or admissions AI deployed without a rights impact assessment
    Supplying incorrect, incomplete or misleading information €7,500,000 1% Inaccurate disclosures to a market surveillance authority or notified body

    Regulators must apply fines proportionately, weighing the nature, gravity and duration of the breach against the size of the organisation. Article 99(6) directs authorities to consider the interests of small and medium-sized enterprises and start-ups — relevant for university spinouts on constrained budgets — but this softens the number, not the underlying obligation.

    • Fines apply per infringement, so a consortium running several non-compliant systems faces cumulative, not capped, exposure.
    • Turnover is calculated on the whole legal entity’s global turnover, not just the department’s AI-related revenue or grant income.
    • National market surveillance authorities, not the EU AI Office, issue most fines against deployers; the AI Office focuses on general-purpose AI providers.

    Which of your institution’s AI systems could be “prohibited” outright?

    Article 5 bans a specific list of practices regardless of sector, and several map directly onto tools already used in higher education and research settings. A prohibited AI practice cannot be risk-managed into compliance — it must be withdrawn.

    The clearest overlaps for a research institution are:

    • Emotion recognition in educational institutions or workplaces, except for narrow medical or safety purposes — implicating some exam-proctoring and staff-monitoring software.
    • Biometric categorisation systems inferring race, political opinion, trade union membership, religion, or sexual orientation from biometric data.
    • Untargeted scraping of facial images from the internet or CCTV to build a recognition database — relevant to campus security systems built on scraped datasets.
    • Social-scoring-style evaluation of individuals by behaviour or personal traits leading to detrimental treatment unrelated to the original context.

    From 2 December 2026, two further prohibited categories take effect under the Digital Omnibus agreement: AI systems that generate or manipulate non-consensual intimate imagery (“nudifier” applications) and systems used to produce child sexual abuse material. Institutions running student-safeguarding or content-moderation tooling should confirm vendor compliance well ahead of that date.

    Has the Digital Omnibus changed the deadlines that matter?

    Yes, but selectively. The Act’s obligations phase in from its 1 August 2024 entry into force: prohibited practices became enforceable on 2 February 2025 (six months later), and general-purpose AI model obligations followed on 2 August 2025 (twelve months later). Both dates already passed and remain in force.

    In November 2025, the Council and Parliament agreed a “Digital Omnibus” simplification package — analysed by law firms including DLA Piper, Gibson Dunn and White & Case — pushing back the two remaining high-risk deadlines. Stand-alone high-risk systems under Annex III (covering most education, employment and public-service AI) now face obligations from 2 December 2027 rather than August 2026, a sixteen-month reprieve. High-risk AI embedded in regulated products under Annex I moves to 2 August 2028.

    Two dates were not delayed: Article 50 transparency obligations — labelling AI-generated content and disclosing chatbot interactions — still apply from 2 August 2026, the same date the Commission gains full penalty-enforcement powers over general-purpose AI providers. Institutions assuming the whole Act slipped to 2027 risk missing this transparency deadline.

    What should a research institution do now?

    The Digital Omnibus buys time on high-risk classification work, not on everything. A defensible position by August 2026 requires:

    • Inventory every AI system touching students, staff, applicants, or research subjects, tagged against the Article 5 prohibited list and Annex III high-risk categories.
    • Confirm any generative AI or chatbot-facing tool meets the Article 50 transparency requirement before 2 August 2026, independent of the high-risk delay.
    • Assign a named owner — typically in research administration or data governance — to track phased deadlines rather than treat the Act as one compliance date.
    • Apply vendor due diligence to procured AI tools, since deployer obligations do not disappear because a third party built the system.

    Answer-first: common questions on AI Act penalties

    Is the AI Act a regulation?

    Yes. The Artificial Intelligence Act is Regulation (EU) 2024/1689, meaning it applies directly and uniformly across all EU member states without needing national transposing legislation. It entered into force on 1 August 2024, and its obligations phase in over a multi-year timeline extending to 2028.

    What is the EU AI Act in 2026?

    By mid-2026, the prohibited-practice and general-purpose AI rules are already fully enforceable, while most high-risk system obligations have been pushed to December 2027 and August 2028 under the November 2025 Digital Omnibus agreement. Article 50 transparency duties and full GPAI enforcement powers still take effect on 2 August 2026 as originally scheduled.

    Does the UK have to comply with the EU AI Act?

    The UK has no domestic equivalent to the AI Act, but the regulation’s extraterritorial scope reaches UK institutions whenever their AI system’s output is used by, or affects, people in the EU. A UK university running an EU-facing admissions or research-collaboration platform can fall within scope despite being outside the bloc.

    Does the UK have any AI regulation of its own?

    Not a single statute. The UK relies on a sector-by-sector, principles-based approach enforced by existing regulators (ICO, EHRC, Ofcom) rather than one AI Act. This is why UK institutions with EU-facing systems must track both the domestic guidance and the EU regulation’s extraterritorial reach separately.

    What this means for institutional risk management

    The headline €35 million figure will rarely apply to a university outright, but the reputational cost of a prohibited-practice finding is not confined to the fine itself. A finding against emotion-recognition exam software invites scrutiny of every other AI-enabled assessment tool on campus, and funders increasingly expect institutions to demonstrate AI governance maturity, mirroring assurance expectations already familiar from research administration compliance frameworks.

    Treating AI Act regulation as a procurement and governance discipline — inventory, classification, named ownership, phased deadline tracking — converts an open-ended legal risk into a manageable operational programme.

    Where this is heading

    The Digital Omnibus shows the EU will adjust timelines under pressure, but it has not softened the penalty structure, and it has added prohibited categories rather than removed any. Research institutions should expect further phased deadlines and continued extraterritorial reach, and should treat every delay as a planning window, not a reason to deprioritise compliance work.