Data Papers Explained: Making Datasets Citable
A data paper is a peer-reviewed publication that makes a dataset citable and FAIR — not just a data availability statement.
Editorial · Practical
Hands-on guidance for research administrators, authors, and institutional teams — compliance walkthroughs, funder templates, certification pathways, and plain-language explainers of the standards vocabulary.
A data paper is a peer-reviewed publication that makes a dataset citable and FAIR — not just a data availability statement.
What a research data manager does, how it differs from data stewards and research administrators, and the career path into the role.
ADR UK gives accredited researchers secure, de-identified access to linked UK government data via Trusted Research Environments.
UK Data Service vs ICPSR: deposit routes, access tiers and citation rules compared for social science researchers.
A practical guide to choosing CC0, CC-BY, or custom terms for FAIR-compliant dataset licensing, with a decision framework for repositories.
ENA, GEO or SRA? Compare deposit rules, metadata standards and funder mandates before you submit.
How the EU-US Data Privacy Framework, UK Extension and SCCs govern lawful research data transfers to US collaborators post-Brexit.
How an institutional research data management policy differs from a per-grant DMP, with a ready template structure.
Compare DMPonline, DMPTool and Argos on funder templates, branding and API export before picking a DMP tool.
How the research data steward role differs from data owner and custodian, and where it fits in an institutional RDM team.
How NERC’s two-stage Large Grant scheme differs from UKRI’s council-specific Standard Grant routes in eligibility, review and funding.
A practical field guide to BA/Leverhulme Small Research Grants: eligibility, budget rules, fEC status and reporting.
EPSRC’s grant records now sit inside UKRI’s Gateway to Research — here is how to search it like an administrator.
A step-by-step UKRI Funding Service walkthrough: account setup, application steps and research-office submission.
Compare UKRI’s Standard, Frontier Research, Programme and Block grants by team size, duration and reporting burden.
How UKRI’s OA block grant is allocated, what it funds, and institutions’ Final Expenditure Statement duties.
How UKRI training grant terms and conditions diverge from standard grant T&Cs on transfer, extension and cohort reporting rules.
UKRI FEC grant guidance explained: how the 80% cost-recovery rule and TRAC set what institutions can claim.
The Research Governance Framework for health and social care was withdrawn in 2017 — here’s what replaced it and what sponsors must do now.
What a research governance officer does, how it differs from research integrity, and where it reports.
Research governance is broader than NHS ethics review; explore the sponsorship, data, finance and integrity framework.
NIH R21 vs R01 eligibility compared: budgets, ESI paylines, and institutional sign-off for first-time PIs.
A field guide to NIH’s R, U, K, F and P activity codes: what each series means and how to read a full grant number.
NIH Matchmaker matches your abstract to funded peers, activity codes, and likely study sections.
U01 cooperative agreements bring NIH programme staff into the research; R01 leaves the investigator in full control.
The NIH Grants Policy Statement sets the compliance terms behind every NIH award, from cost rules to effort reporting.
A practical walkthrough of eRA Commons: registration roles, JIT, RPPR and closeout for NIH award administrators.
What happens to a federal grant during a research misconduct investigation: suspension, cost recovery and funder notice rules.
How the GMC investigates research misconduct: fitness-to-practise stages, sanctions, and how it differs from NHS and university routes.
NHMRC does not investigate misconduct itself. See how the Australian Code defines breaches and who does.
The three formal phases of a research misconduct allegation: inquiry, investigation and adjudication, explained.
ORI publishes named misconduct findings and penalties online — then removes them once sanctions expire.
Research integrity officer roles, UK salary bands (£31k-£80k+) and how to get into research integrity careers.
A practical guide to when accused researchers need legal counsel, the investigation phases, and respondent due-process rights.
COPE and NISO define five required elements for a compliant retraction statement, from reason codes to author sign-off.
How research offices, tenure committees and funders can screen candidates with the Retraction Watch Database and ORI case summaries.
No APC does not mean no risk. Verify DOAJ status, editorial board and COPE/OASPA ties before you submit.
cOAlition S’s 2026 strategy favours diamond OA over gold. Here is the author decision guide.
Open Policy Finder replaced Sherpa Romeo as Jisc’s tool for checking publisher self-archiving and Plan S compliance.
REF 2029 open access policy vs Plan S: embargo limits, licence tiers, exceptions and the 2029 convergence date compared.
How the Rights Retention Strategy lets authors licence their manuscript CC BY and keep reuse rights under Plan S and UKRI mandates.
Read and publish vs transformative agreements explained, with a UK librarian compliance checklist.
No house style for an AI governance framework? Compare NIST, ISO 42001 and McKinsey models, then adapt this research-office template.
Annex III makes exam-scoring, admissions and proctoring AI high-risk under the EU AI Act — here is what follows.
A general-purpose AI model under the AI Act triggers Article 53 duties that differ sharply from a narrow research tool.
Compare UK research contract templates — MTA, mCTA, MNCA and collaboration agreement — to pick the right one for your project type.
What a sponsored programs office does, pre-award vs post-award roles, staffing models, and US vs UK equivalents.
A checklist for financial reconciliation, final reports, and equipment disposition at grant closeout, plus the pitfalls that trigger audit findings.
Why funders reject budget justifications, and how to structure one that survives NIH, NSF, UKRI or Horizon Europe review.
A no-cost extension lets researchers finish the work without new funds. Learn funder rules, deadlines and how to document justification.
A data transfer agreement governs clinical trial data movement, distinct from the MTA (materials) and CTA (trial conduct).
An IRAS PIC agreement covers recruitment-only sites, not full trial delivery. Here’s when you need one instead of a CTA.
What the MNCA template covers, how it differs from the mCTA, and when NHS research sites must use the April 2026 version unmodified.
How the UK ABPI/HRA model clinical trial agreement (mCTA) works, when a bespoke contract applies, and how IRAS routes studies.
What a clinical trial agreement covers, who signs it, and how indemnity, IP and publication clauses get negotiated.
Use this decision framework to work out whether a transfer needs a full MTA, a simple loan letter, or no agreement at all.
What a material transfer agreement covers, when it’s required, and how UK vs US institutional practice differs.
ORCID has no delete button, only deactivation. See what data is removed vs retained, and when visibility settings work better.
How bioRxiv’s Author Area handles manuscript revisions, DOI continuity and version history before journal publication.
What bioRxiv’s screening checks for, and what to do if your preprint is held, escalated, or declined.
Auto-generated CRediT statements can misstate role scope — here’s how to vet generator tools before recommending them.
A governance primer on UK Research Council PhD funding: how DTP and CDT co-investment and reporting duties differ.
A compliance breakdown of UKRI funding eligibility: who can apply, what costs qualify, and how rules differ by council.
An expression of concern flags research under review — a distinct, less final step than retraction.
A side-by-side comparison of Springer, ACS and IEEE open access agreements, mapped against Plan S compliance routes for research-office staff.
How to use Retraction Watch’s hijacked journal checker with Think.Check.Submit and DOAJ to vet journals.
Article 50 of the EU AI Act sets labelling duties for chatbots and synthetic content — here is what university research tools must disclose.
Practical IRAS/HRA walkthrough for research admins: proportionate vs full NHS REC review, committee makeup and realistic approval timelines.
A funder-by-funder comparison of UKRI new investigator routes: MRC, BBSRC, EPSRC, ESRC and NERC eligibility, value and host rules.
Research integrity means proactive honesty and rigour, not the reactive violations of research misconduct. Here’s the difference.
A data management plan sets out how research data is collected, stored, shared, and preserved.
A plain-English guide to Horizon Europe: what it is, its three pillars, UK eligibility, and open-science rules.
A NICRA fixes the indirect cost rate for US federal grants, negotiated with a cognizant agency.
Central IRB vs local IRB review compared: NIH’s single-IRB mandate, reliance agreements, and turnaround trade-offs explained.
What a grant funding agreement covers, how it differs from a contract, and what to check in UK/EU model agreements before signing.
ESRC Postdoctoral Fellowship 2026: eligibility windows, DTP host duties, deadlines and how it fits ESRC’s grants.
How ERC Starting, Consolidator, Advanced and Synergy grants differ on eligibility, panels and deadlines.
What a research administrator actually does: pre- and post-award duties, entry routes, courses and career pathways explained.
A due-diligence checklist for research offices: test grant management software for ORCID, ROR, RAiD and CERIF fit.
A five-criteria framework for comparing preprint servers: screening, licensing, DOIs, indexing, and journal-submission integration.
Flexi-Grant is the shared SaaS portal behind British Academy, Royal Society and CRUK funding — here’s what research administrators need to know.
How DORA, CoARA and the Forum for Responsible Research Metrics translate into hiring and promotion panel criteria.
What institutions actually commit to when signing DORA — and how it differs from CoARA’s reform requirements.
The UK’s national body for responsible metrics use, its DORA/REF remit, and what it means for research office policy.
CoARA is the EU-launched coalition reforming research assessment beyond journal metrics.
Gold or green open access under Horizon Europe: how each route affects APC reimbursement and embargo compliance.
How research offices and journalists find and verify Horizon Europe funded projects using CORDIS and EU open data.
A pre-award guide to tracking 2026 Horizon Europe calls and verifying each call’s open access and data-sharing obligations.
The ten commitments, reporting duties, and realistic timeline institutions should know before signing the CoARA agreement.
CoARA is the coalition reforming how research is assessed. Here is its origin, principles, and what signing means for hiring committees.
A field-by-field walkthrough of the Horizon Europe DMP template for pre-award staff completing it for the first time.
ORE has no Clarivate Impact Factor by design. Here’s what its Scopus indexing and SJR data actually mean.
Open Research Europe is the EU’s fee-free OA platform for Horizon grantees, meeting the open access mandate.
Widening Participation lets under-represented states join Horizon Europe, and the same open access rules apply from day one.
What the Horizon Europe Work Programme 2026-2027 changes — and doesn’t — for open access, FAIR data and DMP clauses.
A guide to UKRI’s New Investigator Award: eligibility, funding limits, and how it complements postdoctoral fellowships.
A reference explainer mapping UKRI’s nine councils — seven research councils plus Research England and Innovate UK — to their remits.
How UKRI Proof of Concept funding routes work, connect to Innovate UK, and what research offices should check first.
UKRI policy internships (3 months, PhD students) vs policy fellowships (18 months, postdocs) — compared.
A practical guide to building a UKRI grant pipeline from Funding Finder, the future-opportunities timeline and the Funding Service.
A practical guide to using UKRI’s Gateway to Research for tracking funded projects, peer benchmarking and institutional reporting.
UKRI’s confirmed 2026/27 PhD stipend is £21,805, up 4.9% from 2025/26 — here’s what research offices must budget for.
Map REF2021 impact case study evidence onto the REF 2029 template using the new Continued ICS route and 2025 weighting changes.
REF 2029 keeps all 34 units of assessment from REF 2021 — but scoring weights and criteria are changing.
REF 2029 drops the single census date for a two-year FTE average. Key dates and eligibility rules for research offices.
REF 2029 impact case studies cut the word limit to 2,200, drop the 2* threshold, and ease minimum submission counts.
How to display your ORCID iD correctly on a manuscript byline, CV and grant biosketch, using the official ORCID icon and URL format.
Why an ORCID iD search returns no results — privacy settings, name variants, unclaimed records — and how to fix each.
Register your ORCID iD before your first paper: the 5-step signup plus what PhD students should add first.
How Elsevier, Wiley and Taylor & Francis authenticate ORCID iDs at submission, and what editorial offices must check.
Step-by-step guide to linking ORCID iD to Google Scholar, Scopus and Web of Science, and fixing mismatched lists.
A practical walkthrough of ORCID visibility settings and how each tier affects auto-updates and funder reporting compliance.
ORCID authentication lets publishers push verified publication records to researcher accounts automatically via Crossref and DataCite.
medRxiv submission for clinical research requires IRB approval, trial registration and a disclaimer distinct from bioRxiv.
Citing bioRxiv? Get the exact APA and Vancouver formats, DOI/version rules, and EndNote/Zotero setup.
How bioRxiv and medRxiv DOIs work across preprint versions — and how to correctly cite v1 vs v3 in your reference list.
A developer’s guide to pulling DOIs, versions, and subject categories from the bioRxiv and medRxiv APIs.
A first-time-author walkthrough of bioRxiv submission: format, template, author area setup and screening.
bioRxiv preprints are citable via DOI but not peer-reviewed — here’s how tenure committees should evaluate them.
bioRxiv preprints undergo basic screening, not peer review. Here is what the checks cover, and what they do not.
Why Nature’s flagship journal still uses a free-text author contributions paragraph, not CRediT dropdowns, and how to translate between the two.
Compare the CRediT grid, free-text and footnote formats journals use, then build one master contribution statement template.
CRediT’s Investigation role means data/evidence collection, not a misconduct inquiry. See how the terms differ.
Authorship and contributorship are distinct concepts under ICMJE and COPE guidance for editors drafting policy language.
MDPI mandates a CRediT-based author contributions statement for every submission; here is the exact format required.
A copy-paste template, CRediT role table, and discipline rules for a defensible statement of equal author contribution.
Compares BMJ’s contributorship model, ICMJE authorship criteria and CRediT statements, with a reconciliation table for editorial staff.
Data management plan templates differ by discipline. Compare physical, life and social science DMP checklists.
NSF data management plan rules now differ by directorate. Compare BIO, ENG, GEO, MPS, OPP and SBE requirements in one guide.
How MRC’s data management plan compares with Wellcome’s outputs management plan for bioscience grantees.
Generalist or discipline-specific repository? A decision framework covering discovery, funder rules and long-term curation.
A practical walkthrough for scoring institutional datasets against the RDA FAIR Data Maturity Model’s 41 indicators.
UK GDPR requires a data sharing agreement for joint-controller research collaborations. See when one applies and what to include.
A practical template for institutional data sharing policies, covering FAIR mandates, core sections, and roles for research offices.
How qualitative research DMPs meet FAIR data mandates while protecting consent, anonymisation and GDPR duties.
DMPonline vs US DMP tools: how UK funder template coverage, institutional branding and export formats compare for research administrators.
A field-by-field breakdown of the Horizon Europe DMP template and how each section maps to FAIR data obligations.
A field-by-field guide to completing UKRI’s data management plan template consistently across MRC, BBSRC, NERC and EPSRC grants.
When does “not applicable” satisfy a data availability statement, and when does it draw an editorial query?
Compliant DAS templates for Nature, Elsevier, Wiley, Springer and MDPI, plus what makes one non-compliant.
Wellcome Trust and CRUK grant rules diverge on open access funding, data sharing and reporting. Compare both funders’ requirements.
How university spinouts meet Innovate UK Smart Grants eligibility, IP and consortium governance rules, plus 2026 funding status.
How NERC, EPSRC and BA/Leverhulme size small versus large research grants — limits, review stages and reporting compared.
How grant offices mine UKRI’s funded projects database (GtR) for benchmarking, competitor tracking and due diligence.
A practical guide to the UKRI Funding Service for institutional grants teams still adjusting workflows after Je-S.
How NIH SBIR/STTR small-business grants differ from R01 research grants in eligibility, governance and commercialisation rules.
A research-office governance guide to NIH F31, F32, K and DP2 awards: eligibility, sponsor duties, effort rules and transfers.
A due-diligence checklist for research offices to verify UKRI, NIH and Grants.gov funding opportunities and spot scam red flags.
A structural walkthrough of Grants.gov: SF-424 form families, AOR roles and what Simpler.Grants.gov changes for administrators.
A working 2026 reference to NIH standard due dates, resubmission windows and cycle changes for research administrators.
A plain-English guide to NIH grant activity codes — how R01, R21, K and T32 differ in scope, funding caps, duration and eligibility.
UKRIO, Epigeum and UCL’s bespoke modules compared — what each research integrity training programme actually covers, and how to choose.
When is splitting one dataset into several papers legitimate, and when does it become duplicate publication? COPE case guidance explained.
How institutions should structure a research integrity office: reporting lines, panel composition and independence from HR.
iThenticate vs Turnitin: how research integrity offices should weigh coverage, false positives and licensing.
A COPE-aligned decision framework for choosing a corrigendum, erratum, or retraction — for editors and research offices.
How UK universities define and detect self-plagiarism, and where COPE journal rules diverge from institutional policy.
A reference guide to which funders back cOAlition S and Plan S today, and which, like Gates Foundation, have diverged.
Plan S green open access explained: the zero-embargo deposit rules, qualifying repositories, and how it differs from rights retention.
cOAlition S’s Transformative Journal model ran 2021-2024. Here is what qualified, why it was retired, and what replaced it in Plan S compliance.
How read and publish agreements let institutions meet Plan S without per-article APCs, and where they fit against APC waivers.
How APC waiver and discount schemes work across seven major publishers under Plan S equity rules.
How the deemed export rule applies when foreign national researchers access AI models, weights and training infrastructure at US universities.
University AI tools lose EU AI Act research-exemption status on deployment. What governance and documentation universities must put in place.
How research offices apply the NIST AI RMF’s four functions and AI 600-1’s GenAI profile to grant compliance.
How ISO 42001 AI-management certification works, differs from ISO 27001, and relates to EU AI Act compliance.
QR funding is Research England’s REF-linked block grant. See how it differs from project grants and what changed for 2025-26.
A practical explainer of the Athena Swan charter: transformed principles, award tiers and the evidence institutions must submit.
IRB (US) and REC (UK) both review human-subjects research under different legal frameworks and routes.
The Researcher Development Concordat is distinct from the Research Integrity Concordat, with its own action-plan reporting cycle.
A practical guide to REF impact case study evidence: the underpinning-research link, REF 2029 thresholds and template pitfalls.
The Concordat’s five commitments, the annual self-assessment duty, and what the 2025 refresh changed for 2026.
How UKRI, Royal Society and British Academy endorsement routes differ for the UK Global Talent visa.
The Research Governance Framework (2005) was replaced in 2017. Here’s what UK institutions must comply with now.
A CDMP governs trial data operations; an RDMP satisfies funder compliance. Here is how the two differ.
A governance primer on the HRA’s UK Policy Framework — sponsor duties, REC review, and NHS approval steps.
A comparative guide to how the US Office of Research Integrity and UK Research Integrity Office handle misconduct allegations tied to funded research.
UKRI paused MRC and BBSRC calls in 2026; here’s the reopening timeline and a planning calendar for administrators.
Federal law splits grants, cooperative agreements and contracts on one test: substantial involvement. Here is what it means for compliance.
NIH biosketches must now be built in SciENcv under the Biographical Sketch Common Form. Here is what changed and how to verify compliance.
A practical walkthrough of NIH RePORTER’s search, filters, and API for portfolio analysis and funding prospecting.
Authors, supervisors and institutions each carry a distinct duty to report suspected research misconduct under UK and US frameworks.
A plain-terms guide to retraction, correction, expression of concern and redaction — and when editors should use each.
What a research integrity officer actually does, how the role differs from research ethics posts, and realistic UK career and salary pathways.
A practical, UKRIO- and ORI-aligned procedure for institutional committees: intake, inquiry, formal investigation and reporting phases explained.
Test excerpt.
How to query the free Retraction Watch database for hiring, grant, and co-author checks — and where its coverage falls short.
cOAlition S’s own EU-funded projects page lists infrastructure grants, not grantee rules. Here’s what still applies on top of Horizon Europe’s OA mandate.
Step-by-step guide to using cOAlition S’s Journal Checker Tool to verify Plan S compliance across gold, green and transformative routes.
ROARMAP is the searchable registry cataloguing institutional and funder open access mandates worldwide, including cOAlition S members’ policies.
UK research offices: a route map showing how Jisc read-and-publish deals map to the three cOAlition S Plan S compliance routes.
BOAI’s voluntary 2002 principles versus Plan S’s binding funder mandate — a practical comparison of open access’s two founding blueprints.
How cOAlition S is governed: the Leaders Group, Executive Steering Group, secretariat and the funders who set Plan S policy.
cOAlition S is the funder coalition behind Plan S, not the mandate itself. Here is who it is, who funds it, and why the distinction matters.
A funder-by-funder compliance checklist for AI use in grant applications, covering NIH, UKRI, ERC and NHMRC, with disclosure templates.
What the 2021 UNESCO AI ethics Recommendation commits states to, and how UK 2025 guidance applies to research offices.
AI Growth Zones bundle grid priority, energy discounts and fast-track planning for data centres. Here is what zone status means for university partners.
A step-by-step Annex III walkthrough for admissions, proctoring, and biometric-profiling tools used in academic research.
What Article 4’s AI literacy duty means for research institutions: who counts as staff, what training suffices, and how to document it.
A plain-English glossary of core sponsored research administration terms for early-career research administrators.
How to evaluate ERA platforms for proposal routing, compliance, and effort reporting under 2026 Uniform Guidance.
A risk-heatmap guide to where audit findings cluster across pre-award and post-award research administration under 2 CFR 200.
Grant administration handles compliance; grant management spans the full funding lifecycle. Here’s how research offices split the two.
GovS 015 update strengthens fraud-risk and security guidance for UK grant-funded bodies.
The de minimis indirect cost rate rose from 10% to 15% of MTDC in 2024 — here’s who qualifies and how it compares to a negotiated rate.
A practical, step-by-step guide to building an indirect cost rate proposal and negotiating a NICRA with a federal cognizant agency.
A crosswalk of NIH, NSF, Horizon Europe, and UKRI data management plan rules, with a modular template structure for multi-funder portfolios.
A decade after Wilkinson et al.’s 2016 framework, FAIR data principles remain unevenly applied — here is a practical map from principle to institutional practice.
A working glossary of NIH Grants Policy Statement terms — no-cost extension, carryover, consortium agreements, and program income — for research administrators.
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Introduction The strategic advancement of Integrating ORCID APIs with CRIS Systems: Streamlining Institutional Reporting is transforming how modern academic institutions catalog, preserve, and evaluate scientific outputs. In an era dominated by rapid open-science transitions and complex funding mandates, establishing unified metadata frameworks, secure persistent identifiers, and collaborative repositories is essential for ensuring institutional transparency and […]
The Drug Supply Chain Security Act’s enhanced traceability requirements move the US pharmaceutical supply chain toward serialised, electronic, interoperable tracing. With phased stabilisation deadlines after November 2024, this explainer describes serialisation, interoperability and how the unit-level tracing model works.
The NIST AI Risk Management Framework is a voluntary US framework for managing AI risk; its Generative AI Profile (AI 600-1) adapts it to generative systems. A neutral explainer of how organisations use them.
Introduction The strategic advancement of GitHub and Zenodo Integration: Minting DOIs for Research Code Releases is transforming how modern academic institutions catalog, preserve, and evaluate scientific outputs. In an era dominated by rapid open-science transitions and complex funding mandates, establishing unified metadata frameworks, secure persistent identifiers, and collaborative repositories is essential for ensuring institutional transparency […]
Predatory publishers take fees while skipping the editorial and peer-review services that legitimate journals provide, trapping the unwary, particularly early-career and Global South researchers. This article sets out a positive way to evaluate a venue: the Think. Check. Submit. checklist, the DOAJ inclusion criteria, and COPE membership. It also examines the troubled history of Beall’s list and why curated allow-lists and education have largely displaced blacklists.
Sharing data about people without exposing the people themselves is one of the hardest problems in research data management. This article distinguishes anonymisation from pseudonymisation, explains the privacy models researchers actually use, k-anonymity, l-diversity and differential privacy, and introduces the practical guidance from the UK Anonymisation Network (UKAN) and the ICO’s anonymisation code. It also confronts the uncomfortable reality that re-identification is often easier than it looks.
PCR and quantitative PCR are core molecular methods, and the MIQE guidelines define what must be reported for results to be reproducible. This guide explains PCR at a high level and the minimum information MIQE requires for transparent qPCR experiments.
The h-index, proposed by Hirsch in 2005, measures a researcher’s productivity and citation impact in a single number. This explainer defines it with a worked example, sets out its limitations, and introduces complementary metrics for responsible use.
Paraphrasing means restating a source’s idea in your own words and structure while still citing it. This guide distinguishes quoting, paraphrasing and summarising, shows how to paraphrase properly, and flags the traps that lead to accidental plagiarism.
Good Clinical Practice is the international standard for designing, conducting and reporting clinical trials. This explainer covers the ICH E6 guideline, its principles and why GCP protects both participants and data.
Self-plagiarism is reusing your own previously published work without disclosure. Learn how it relates to text recycling and duplicate publication, COPE guidance, acceptable reuse, and how to disclose prior work.
An outlier is a data point that lies an unusual distance from the bulk of a distribution. This guide defines outliers, separates measurement error from genuine extremes, and sets out detection methods and principled handling that you report rather than delete silently.
Chicago and Vancouver are two contrasting referencing systems: Chicago offers a notes-bibliography and an author–date variant for the humanities and sciences, while Vancouver uses numeric citations for biomedicine. This guide explains how each works, with worked examples.
A drug recall removes a defective or potentially unsafe product from the market. This explainer describes the FDA recall classes, how recalls are initiated and how traceability makes them possible.
Most empirical research papers follow the IMRaD structure: Introduction, Methods, Results and Discussion, framed by an abstract, references and metadata. This guide explains each section, how to read it and how to write it, plus the role of DOIs.
Citation styles are standardised systems for formatting in-text citations and references. Compare APA 7, MLA 9, Chicago 17 and Vancouver, the disciplines that use them, and when to choose each.
A research abstract is a short, self-contained summary of a whole study. This step-by-step guide explains structured versus unstructured abstracts, the IMRaD-aligned content to include, typical word limits, keywords and the mistakes to avoid.
Big data describes datasets so large, fast or varied that traditional tools cannot handle them. This guide explains the defining Vs, from volume and velocity to veracity and value, how distributed processing copes, and what big data means for research and FAIR data.
Measures of central tendency summarise a dataset with a single typical value. This explainer defines the mean, median and mode, explains when each is appropriate, and shows how skew and outliers affect them, with a worked example.
Preregistration commits researchers to their hypotheses and analysis plan before data collection, while Registered Reports add peer review and in-principle acceptance up front. This guide explains how both curb p-hacking and publication bias, and the role of the Center for Open Science.
Altmetrics track the online attention a paper receives, while the Eigenfactor and Article Influence score weight citations by the standing of the citing journals. This guide explains what each measures, the gap between attention and impact, and how to read them responsibly.
A secondary citation is when you cite a source you have not read, encountered only through another work. The as-cited-in convention lets you do so honestly, while pointing to the original wherever possible. Worked APA, MLA, Harvard and Chicago examples follow below.
Plagiarism detection software compares a document against a large corpus and reports matching text as a similarity score. It flags overlap; it does not judge intent or prove plagiarism. This guide explains how text-matching works, its limits and responsible use.
Correlation measures how two variables move together; causation means one variable produces a change in another. This guide explains Pearson’s r, why correlation does not imply causation, confounding, and the criteria used to support causal inference.
A confidence interval is a range of plausible values for a population parameter, produced by a procedure that captures the true value in a stated proportion of repeated samples. This guide explains the correct interpretation and why intervals often beat bare p-values.
Cloud computing delivers on-demand, elastic, measured computing resources over a network. This explainer defines it using the NIST model, distinguishes IaaS, PaaS and SaaS, and weighs its role in reproducible research alongside cost and governance considerations.
Quantum computing uses qubits, superposition and entanglement to process information in ways classical computers cannot. This explainer defines the principles, situates the NISQ era, and assesses realistic research implications without overstating present-day capabilities.
Model cards and datasheets for datasets are structured documentation that record what an AI model or dataset is, how it was built and where it should not be used. This article explains each, what they record, and how they support reproducibility and accountability.
Reliability and validity are the foundations of sound psychological measurement. This guide defines test-retest, inter-rater and internal-consistency reliability alongside construct, content and criterion validity, and explains why a measure can be reliable yet not valid.
Incidence counts new cases over time, while prevalence counts existing cases at a point or over a period. This guide defines each measure, shows how they are calculated, explains the relationship between them, and clarifies when to use which.
Mass spectrometry measures molecules by converting them to ions, separating those ions by mass-to-charge ratio, and detecting them. This explainer covers ionisation, separation, detection, reading a mass spectrum and common research uses in proteomics and metabolomics.
Reproducible research depends on reporting analytical methods in enough detail that others can repeat them. This article sets out what to record about instruments, parameters, calibration, reference materials and validation, and how reporting guidelines and protocol repositories help.
CRISPR-Cas9 is a programmable gene-editing tool widely used in research. This guide explains how the guide RNA and Cas9 enzyme work, its bacterial origin, and the reproducibility and governance considerations of using it as a laboratory method.
An academic journal is a peer-reviewed periodical that publishes original scholarly research. This explainer covers peer review, the editorial board, the ISSN, volumes and issues, the version of record, and the difference between open-access and subscription models.
Learn how to cite any source in five repeatable steps: identify the source type, capture its metadata, choose a style, build the in-text citation and reference entry, then verify accuracy. A practical, style-agnostic workflow grounded in real standards.
A systematic review is a structured synthesis of all eligible studies; a meta-analysis is the statistical pooling of their results. This guide explains the difference, the role of PRISMA reporting, heterogeneity and forest plots, and when pooling is appropriate.
A science journal is a scholarly periodical focused on the sciences, while an academic journal is the broader category spanning all disciplines. This explainer distinguishes the two, separates peer-reviewed journals from magazines, and explains what makes a journal scholarly.
The Food and Drug Administration regulates medicines, devices and food in the United States. This explainer outlines how its approval pathway works and why its evidence requirements shape the research record.
An in-text citation is a brief marker in the body of a text that points to a full entry in the reference list. Learn how author-date and numeric systems work and how markers map to entries.
Evidence-based medicine is the conscientious, explicit and judicious use of current best evidence in decisions, integrating research with clinical expertise and patient values. This article defines EBM, explains the hierarchy of evidence and shows how GRADE rates certainty.
A placebo is an inactive comparator used to isolate the true effect of a treatment. This explainer covers the placebo effect, blinding, and why placebo controls are central to rigorous trial design.
MLA format uses author–page in-text citations and a Works Cited list built from a single template of core elements. This guide explains the MLA 9th edition container model, Works Cited anatomy and how MLA differs from APA.
Plagiarism is presenting another’s words, ideas or data as your own without proper attribution. Learn the main types of plagiarism, why it breaches research integrity, and how correct citation prevents it.
The Journal Impact Factor measures the average citations to a journal’s recent articles. This explainer shows how it is calculated from the Journal Citation Reports, what it does and does not measure, Garfield’s own caveats, and why DORA warns against misuse.
Scopus and Web of Science are the two leading multidisciplinary citation databases. This comparison weighs coverage, their headline metrics CiteScore and the Journal Impact Factor, and how each is used in research assessment, with a side-by-side table.
Cohort and case-control studies are the two classic observational designs. This methodology guide explains prospective and retrospective cohorts, the case-control logic of looking back from outcome to exposure, and the difference between relative risk and odds ratio at a conceptual level.
Citing a website means capturing the right metadata and formatting it for your style. This step-by-step guide shows what to record, gives worked examples in APA, MLA and Harvard, and explains how to handle missing dates and authors.
Overfitting happens when a model memorises training data instead of learning general patterns, while underfitting means it is too simple to capture them. This guide explains the bias-variance trade-off, regularisation, cross-validation and the threat to reproducible ML.
Effect size measures how large a difference or relationship actually is, independent of sample size. This guide explains Cohen’s d, eta-squared and correlation r, why they complement p-values, and how reporting standards now expect them.
Statistical power is the probability that a study will detect a real effect. This explainer covers Type I and Type II errors, the power = 1 minus beta relationship, the 0.8 convention, a priori power analysis, and why underpowered studies harm reproducibility.
A t-test assesses whether the difference between means is statistically significant. This explainer covers the one-sample, independent-samples and paired t-tests, their assumptions, and how the test relates to p-values and significance.
CiteScore, SNIP and SJR are journal-level metrics that move beyond a simple citation count. This guide explains how each is conceptually calculated, what it adds — from field normalisation to prestige weighting — and how to use them responsibly under DORA.
A double-blind study conceals group assignment from both participants and the researchers who treat and assess them, neutralising the expectations that distort results. This guide explains single, double and triple blinding and the specific biases each design controls.
A citation generator builds a formatted reference from metadata you supply or it retrieves, but the output is only as good as that metadata. This guide explains how generators work, the errors they commonly introduce and how to check every reference.
Reference management software collects, stores and formats citations so researchers can build bibliographies and cite as they write. This neutral comparison of Zotero, Mendeley and EndNote covers collecting references, citation styles, cite-while-you-write and sharing libraries.
A p-value is the probability of observing data at least as extreme as those seen, assuming the null hypothesis is true. This guide explains p-values precisely, summarises the ASA 2016 statement, and corrects common misinterpretations.
Research is the systematic investigation undertaken to establish facts and create new knowledge. This guide defines research, distinguishes basic from applied work, and walks through the research lifecycle from question to dissemination and the lasting scholarly record.
Supervised learning trains on labelled data to predict outcomes; unsupervised learning finds structure in unlabelled data. This explainer defines both paradigms, notes reinforcement learning as a third, and compares their tasks, methods and research uses.
Principal component analysis (PCA) is a dimensionality-reduction technique that re-expresses correlated variables as uncorrelated principal components ordered by variance. This explainer defines PCA conceptually, covers eigenvectors, scree plots, and how it is properly used and frequently misused.
A neural network is a machine-learning model of interconnected units that transform inputs through weighted layers. This explainer covers neurons, weights and activations, training by backpropagation and gradient descent, and what makes a network “deep”.
Generative AI is a class of models that produce new text, images or other content rather than only predicting labels. This explainer defines foundation models, LLMs and diffusion, contrasts them with predictive ML, and sets out the COPE and ICMJE disclosure norms for research.
The DISC test sorts behaviour into Dominance, Influence, Steadiness and Conscientiousness. This article traces its origins in Marston’s work and evaluates such instruments through a measurement lens of reliability, validity and appropriate use.
The Dunning-Kruger effect describes how low performers tend to overestimate their ability. This guide explains the original 1999 study by Kruger and Dunning and the methodological critiques, including regression to the mean and statistical artefacts.
A death rate measures deaths relative to a population, but a crude rate and an age-standardised rate answer different questions. This guide defines both, explains why standardisation is needed for comparison, and outlines cause-of-death coding and data sources.
The polymerase chain reaction copies a chosen DNA sequence millions of times through repeated heating and cooling. This explainer covers thermal cycling, primers, Taq polymerase, exponential amplification and what real-time quantitative PCR adds, strictly as molecular technique.
Terahertz time-domain spectroscopy records the electric-field waveform of an ultrashort pulse directly in time, then Fourier transforms it to amplitude and phase spectra. This explainer covers the physics of the technique and its research applications in materials science.
Statistical software is the toolset researchers use to analyse data — chiefly R, SPSS, SAS, Stata and Python. This guide compares them for research, explains the reproducibility benefits of scripted analysis, and shows why citing software and reporting versions matters.
Genomic data sharing relies on common standards for formats, metadata, consent and controlled access. This guide explains the role of the Global Alliance for Genomics and Health, FAIR principles and controlled-access archives in moving genetic data responsibly.
Web of Science is Clarivate’s selective citation-indexing platform built on the Core Collection. This explainer covers what it indexes, the citation-index concept pioneered by Eugene Garfield, its link to the Journal Citation Reports and how it differs from a search engine.
An APA reference list is the alphabetical, hanging-indented record of every source cited in a paper. This guide builds one step by step, with worked examples for journal articles, books, chapters, websites and datasets, plus DOI and ordering rules.
Peer review is the evaluation of scholarly work by independent experts before publication. This explainer defines peer review, walks through the editorial process, compares single-blind, double-blind, open and post-publication models, and outlines COPE ethics and reform.
A clinical trial is a planned investigation that tests a medical intervention in people. This explainer describes the four phases, how trials are registered and governed, and why transparency standards matter to the research record.
A bibliography is an organised list of sources relevant to a work. Learn what a bibliography is, its main types, how it differs from a reference list, and how to compile and order one correctly.
APA referencing uses an author–date system: brief in-text citations point to full entries in an alphabetical reference list. This guide explains APA 7th edition essentials, reference-list anatomy, DOI formatting and what changed in the latest edition.
Amino acids are the chemical building blocks of proteins. This guide explains the 20 standard amino acids, their one- and three-letter notation, and how protein sequence and structure data are recorded and shared through UniProt and the Protein Data Bank.
A Digital Object Identifier (DOI) is a persistent, unique string that identifies a research output and resolves to its current online location. This explainer covers DOI structure, the Handle System, ISO 26324 and the agencies that assign them.
Open access means free, online, unrestricted access to peer-reviewed research. This explainer defines open access through the Budapest and Berlin declarations and sets out the gold, green, diamond and hybrid routes, Creative Commons licences and Plan S policy.
Good Manufacturing Practice is the quality-assurance system that ensures medicinal products are consistently produced to defined standards. This explainer sets out what GMP covers, who enforces it, and why it underpins trustworthy research.
A citation is a formal reference identifying a source used in a work. Learn what a citation is, its two halves, why it underpins the scholarly record, and how it differs from a reference and a bibliography.
Plan S requires immediate open access to funded research, and its rights retention strategy changes what authors sign away. A plain-English guide to cOAlition S, the compliant routes, and the practical steps an author needs to take.
The narrative CV asks researchers to describe what they contributed rather than list how many papers they published. How R4RI, the Royal Society format, DORA and CoARA reshape assessment, and how to write a narrative CV that actually works.
Footnotes and endnotes carry citations and commentary in note-based styles such as Chicago and Oxford. This guide explains the difference between the two, citation versus content notes, and when notes are preferable to author-date referencing.
IEEE and AMA are both numeric citation systems but they look and behave differently. This guide explains IEEE square brackets for engineering and computing, AMA superscript numbers for medicine, and how each handles in-text references and reference lists.
Natural language processing makes human language machine-processable, from tokenisation and embeddings to transformer models. This guide explains the core building blocks, common tasks such as classification and translation, and what researchers should watch for when using NLP.
The chi-square test compares observed counts with the counts expected under a hypothesis, making it the standard tool for categorical data. This guide covers goodness-of-fit versus independence, assumptions, and how to interpret results for reproducible research.
Regression analysis models the relationship between an outcome and one or more predictors. This introduction explains linear regression, slope and intercept, least squares, R-squared and the all-important caveat that correlation is not causation.
The normal distribution is a symmetric, bell-shaped curve defined by its mean and standard deviation. This explainer covers the 68-95-99.7 rule, the central limit theorem, and what is and is not normally distributed in research.
A randomised controlled trial assigns participants to intervention or comparison groups by chance, using allocation concealment, control and blinding to isolate cause from coincidence. This guide defines the RCT, explains why it is the methodological gold standard, and notes its limits.
The pharmaceutical R&D pipeline is the staged journey a candidate medicine travels from discovery and preclinical testing through phased clinical trials, regulatory review and post-market surveillance. This guide explains each stage and the standards and data that govern it.
An annotated bibliography is a list of sources in which each citation is followed by a short paragraph that summarises, evaluates and explains the relevance of the work. This step-by-step guide shows how to write one, with a worked example.
A DOI is a persistent identifier that resolves to a resource’s current location through the Handle System, while a plain URL points to a fixed web address that can break when a page moves. Here is how each works and when to use them.
Statistics is the science of collecting, analysing and interpreting data under uncertainty. This authoritative definition distinguishes descriptive from inferential statistics, explains populations and samples, and sets out why statistical reasoning underpins credible research.
Standard deviation measures how far observations typically sit from the mean. This guide defines it precisely, distinguishes population from sample formulas, explains the 68-95-99.7 rule, and clarifies when to report standard deviation rather than standard error.
The FAIR principles make research data Findable, Accessible, Interoperable and Reusable. Published by Wilkinson et al. in 2016, they emphasise persistent identifiers and rich metadata. This explainer defines each principle and clarifies how FAIR differs from open data.
A large language model is a neural network trained on vast text to predict tokens and generate language. This explainer defines transformers, tokens, pretraining and fine-tuning, and addresses capabilities, limitations such as hallucination, and responsible disclosure in research.
Machine learning is the study of algorithms that improve at a task by learning from data rather than following hand-written rules. This explainer defines features and labels, the supervised, unsupervised and reinforcement paradigms, and the train/validation/test split that guards against overfitting.
Artificial intelligence is the field concerned with building systems that perform tasks requiring human-like intelligence. This explainer defines AI, distinguishes narrow from general AI, contrasts symbolic and statistical approaches, and traces its history from Dartmouth 1956 to the deep-learning era.
Psychology is the scientific study of mind and behaviour. This definitional guide outlines its scope, major subfields, research methods such as experiments and psychometrics, the role of the scientific method, and the ethical standards that govern the discipline.
The Myers-Briggs Type Indicator sorts people into 16 personality types across four dichotomies. From a measurement-science viewpoint, its reliability and validity raise concerns, and personality researchers favour the continuous Big Five model instead.
A census is a complete enumeration of a population at a defined moment, the backbone of official population statistics. This guide explains how the data are collected and standardised, the roles of national statistics offices and the UN, and the shift toward register-based methods.
Life expectancy is the average number of years a population is expected to live, estimated from a life table built on mortality data. This guide explains the method, the difference between period and cohort measures, and the data sources involved.
Ultrasound is a measurement technique that sends high-frequency sound pulses into a material and times the returning echoes. This explainer covers piezoelectric transducers, pulse-echo timing, depth calculation and the Doppler principle as instrumentation physics.
Magnetic resonance imaging is a measurement technique that maps the behaviour of nuclear spins in a strong magnetic field. This explainer covers the physics of resonance, relaxation and spatial encoding, treating MRI strictly as instrumentation and signal generation.
Introduction to CRIS in Scholarly Spaces Current Research Information Systems (CRIS) are the software backbones of university research administration. They collect, integrate, and showcase institutional research activities, linking researchers, publications, funding, and equipment in a single relational database. The Structural Anatomy of a CRIS System A CRIS system integrates data from payroll, student records, finance, […]
An ORCID iD is only useful when it is connected to your work. A practical guide to setting up your identifier, letting trusted systems write to your record, and linking ORCID to ROR, CRediT and the wider identifier ecosystem.
Harvard referencing is an author-date system, not a single fixed standard. This guide explains in-text citations, reference-list formatting, the institutional variants you will meet and worked examples to keep your citations consistent.
ANOVA, or analysis of variance, tests whether the means of three or more groups differ more than chance would predict. This guide explains the F-statistic, one-way and two-way designs, family-wise error, and post-hoc tests for reproducible research.
Variance is the average squared deviation of values from their mean. This explainer defines variance, distinguishes population from sample formulas, and shows how it relates to the standard deviation, with a clear worked example for researchers.
A grant rarely covers what research actually costs. Beyond salaries and equipment lie the indirect costs — buildings, administration, infrastructure — that keep research possible. Full economic costing, TRAC and funder cost policies determine how the true cost is calculated and recovered.
For research involving people, ethics review is a gateway, not a formality. A plain-language guide to what an IRB or REC does, the review tiers researchers will encounter, and how the Declaration of Helsinki underpins it all.
Most data management plans are written once and filed away. A worked progression from a narrative DMP to a machine-actionable maDMP shows what structured planning makes possible across the research lifecycle.
Author-order disputes are among the most common and bitter conflicts in research. Why they happen, how to prevent them with early agreement and CRediT, and how the COPE flowcharts guide editors when prevention fails.
FAIR is widely cited and often misunderstood. What Findable, Accessible, Interoperable and Reusable actually require in practice, why FAIR is not the same as open, and the concrete steps that move a dataset from a hard drive to a genuinely reusable output.
A dataset without a clear licence is data nobody can confidently reuse. The difference between CC0 and CC BY for data, why software needs different licences, and how to choose a licence that makes your data genuinely reusable.
Honorary names added for status, and the real writers left off entirely, both corrupt the authorship record. What ghost, guest and honorary authorship are, why they matter, and how the ICMJE criteria and CRediT together prevent them.
Research security is not about closing the lab door — it is about asking proportionate questions before entering partnerships, accepting funding or recruiting personnel. How institutions can build risk assessment into research administration without strangling legitimate collaboration.
Personal data is central to vast swathes of research, and the GDPR governs how it may be used. Lawful bases, the special rules for sensitive categories, the research exemptions and the distinction between anonymisation and pseudonymisation all shape what researchers may lawfully do.
An allegation of research misconduct sets in motion a structured process with distinct stages, defined roles and procedural safeguards. A plain-language guide to how inquiries and investigations work, why due process matters, and what outcomes can follow.
Laboratories are among the most resource-intensive spaces on any campus. A practical guide to reducing the environmental footprint of research — from LEAF and My Green Lab to understanding greenhouse-gas scopes — without compromising scientific quality.
Open access is not one thing but several routes, each with different costs, licences and equity consequences. Green, gold, diamond and the colours in between — what each means, who pays, and how Plan S reshaped the landscape.
Conflict-of-interest disclosure protects the reader, not the author. A practical guide to what counts as a competing interest, the ICMJE disclosure model, and how COI sits alongside AI-use and contribution disclosures.
Introduction to NSPM-33 and Research Security National Security Presidential Memorandum 33 (NSPM-33) directs key United States federal funding agencies to establish unified, robust requirements for research security. Primarily targeting academic institutions receiving more than $50 million in annual federal research and development funding, NSPM-33 mandates the implementation of standardized disclosure requirements and formal Research Security […]
Introduction to the Contributor Roles Taxonomy (CRediT) The traditional model of academic authorship—which ranks researchers in a linear sequence (first author, co-author, corresponding author)—fails to reflect the multi-faceted reality of modern scientific collaboration. Large-scale research requires specialized roles, including software development, data curation, project administration, and hardware calibration. To provide granular, machine-readable attribution, CASRAI pioneered […]
A data availability statement is now a routine journal requirement, but “available on request” statements rarely deliver. What to write, how to make data genuinely FAIR, and how to choose between generalist and domain repositories.
CRediT does more than list fourteen contribution roles. Its standard, ANSI/NISO Z39.104-2022, lets each role carry a degree qualifier — lead, equal or supporting — that conveys how much someone contributed. Used well, these qualifiers turn a flat list into a meaningful account of who did what.
Machine-actionable data management planning needs more than a standard — it needs tools. DMPTool, DMPonline and Argos are the three best-known platforms, each rooted in a major open-science infrastructure, and each building towards the RDA DMP Common Standard.
A CRediT author statement is now a routine submission requirement, but many authors still draft it as an afterthought. A practical, step-by-step method for assigning the fourteen roles accurately and producing a statement editors can use.
How production teams should encode CRediT contributor roles in JATS XML so that contribution data survives the journey from manuscript to deposited article. A practical look at the JATS4R recommendations for contrib, role and the credit taxonomy.
Shared first authorship is now common in team science, but it is recorded inconsistently and often invisibly. How to mark equal contribution correctly using author-order conventions, the equal-contribution note, and the CRediT degree-of-contribution qualifier.
An ORCID iD is only as useful as the record behind it. A practical guide to auto-update, trusted organisations, validated assertions and the handful of habits that keep your ORCID profile accurate without manual effort.
Generative AI now touches drafting, analysis, coding and image work, and most journals now require it to be declared. A practical guide to what counts as disclosable use and where the declaration belongs.
A Current Research Information System is the institutional backbone that ties together people, projects, funding and outputs. A plain-language account of what a CRIS does and why it depends on shared vocabulary.
Long before the DOI, books and journals had their own persistent identifiers — the ISBN and the ISSN. Understanding what these international standards identify, how they differ from article-level identifiers, and how they now connect to DOIs is essential to navigating the scholarly record.
Depositing data in a repository is only half the battle — if no one can find it, it might as well not exist. Registries of repositories, dataset search engines and structured metadata are what turn a deposited dataset into a discoverable one.
When a paper’s main output is code, the CRediT Software role bears the load. A practical guide to assigning Software for code-only research outputs.
Depositing research data in a suitable repository is now an expectation of most major funders, but with thousands of repositories in existence — institutional, disciplinary, and general-purpose — choosing the right one is not straightforward. re3data, the Registry of Research Data Repositories, is the principal tool for navigating this landscape: a searchable, indexed registry of more than 3,000 research data repositories worldwide, operated under the auspices of DataCite. This article examines re3data, its metadata schema and badge system for signalling repository properties such as data access, licensing, and persistent identifier support, the main types of repository, how funders including the NIH, Wellcome, and Horizon Europe point researchers towards repository registries for repository selection, and the complementary role of FAIRsharing as a registry of databases, standards, and policies.
Research outputs are no longer static. Datasets are corrected and extended, software is released in successive versions, and preprints are revised in response to feedback. This dynamism creates a persistent identifier problem: should a citation point to a specific, frozen version, or to the evolving work as a whole? The DataCite concept DOI and version DOI model, implemented most prominently by Zenodo, answers this by minting a concept DOI that always resolves to the latest version alongside distinct version DOIs for each release. This article examines the DataCite concept and version DOI model, Crossref’s handling of versioned content, how preprint servers manage versions, the isVersionOf and hasVersion relationship types in the DataCite Metadata Schema, software versioning through the Zenodo-GitHub integration, and why citing a specific version matters for reproducibility.
Regulation (EU) 2024/1689 — the EU AI Act — entered into force on 1 August 2024 and introduces a tiered risk framework for artificial intelligence systems deployed in the European Union. For researchers and research institutions, the Act creates a landscape that is more nuanced than either “AI is banned” or “AI is unrestricted”: a scientific research exemption under Article 2(6) removes most obligations from AI developed or used for R&D purposes, but high-risk AI systems deployed in domains such as education, employment, and essential services remain subject to strict requirements regardless of the research context. General-purpose AI models under Title VI carry their own transparency and copyright obligations. This article examines the Act’s provisions as they apply to research institutions, distinguishes between developing AI and using AI as a research tool, and identifies the obligations that universities and research organisations must meet.
A new generation of artificial intelligence tools has entered the research workflow at the literature review and evidence synthesis stage. Elicit, developed by Ought (now the Elicit PBC), uses language models to extract findings from papers and assist with systematic reviews. Consensus provides AI-driven synthesis of evidence from published research. Rayyan offers machine learning-assisted screening for systematic review teams. SciSpace and Perplexity offer research assistant capabilities drawing on published literature. As these tools become more capable and more widely used, the question of when and how their use should be disclosed in research outputs has become urgent. COPE guidance, emerging journal AI tools policies, and funder transparency expectations all point towards a disclosure norm, but the details remain contested and inconsistently applied across disciplines and publishers.
Horizon Europe supports European research through two complementary but fundamentally different funding pillars: the European Research Council, which funds investigator-driven frontier research through Starting, Consolidator, Advanced and Synergy grants, and the Marie Skłodowska-Curie Actions, which fund researcher mobility and training through Doctoral Networks, Postdoctoral Fellowships and COFUND schemes. The two instruments differ in purpose, eligibility, host institution requirements and the career stages they target. Understanding how ERC grants fund visionary individual researchers pursuing their own scientific ideas, while MSCA schemes prioritise cross-border mobility and structured doctoral and postdoctoral training, helps institutions and researchers identify which instrument best fits their ambitions. This article examines both pillars in depth, including the significance of the UK’s association to Horizon Europe and what this means in practice for researchers based at UK institutions.
Reporting research misconduct requires courage. Despite formal institutional mechanisms and legal protections for whistleblowers in the UK and United States, researchers who raise concerns about fabrication, falsification, plagiarism, or other serious integrity violations frequently face significant personal and professional risk. The UK Research Integrity Office (UKRIO) and the Committee on Publication Ethics (COPE) provide guidance on how investigations should be conducted fairly and transparently. Legal frameworks — including the UK Public Interest Disclosure Act 1998 and US protections under the Federal False Claims Act and Title VII — offer important but imperfect protections for those who report concerns. This article outlines what constitutes reportable misconduct, the barriers researchers face when considering reporting, available legal protections, and how institutional investigations should proceed according to recognised good practice frameworks.
Laboratories are among the most resource-intensive spaces in the university estate, consuming several times more energy per square metre than standard office buildings. Green laboratory certification programmes — including the Laboratory Efficiency Assessment Framework (LEAF) developed at the Universities of Exeter and Cambridge, and the My Green Lab certification programme originating in the United States — provide structured pathways for research teams to audit, improve, and formally recognise sustainable practice. As funders including UKRI incorporate sustainability into their expectations of grant holders, and as institutions pursue net-zero commitments, these frameworks offer researchers practical tools for reducing environmental impact without compromising scientific output. This article examines what LEAF and My Green Lab certification involve, the role of energy-intensive equipment, and how researcher behaviour change underpins lasting improvement.
Clinical trial registration has evolved from a voluntary practice into a legal and ethical obligation in most major research jurisdictions. The WHO International Clinical Trials Registry Platform, ClinicalTrials.gov, and the EU Clinical Trials Regulation 536/2014 together create a near-universal expectation that all interventional trials are publicly registered before participant enrolment begins. The AllTrials campaign and CONSORT 2010 reporting guidelines reinforce these requirements at the publication stage, while the US Food and Drug Administration Amendments Act 2007 introduced enforceable penalties for non-compliance. This article outlines what registration requires, explains the AllTrials transparency agenda, and describes how CONSORT reporting standards interact with registration obligations for research teams and clinical investigators.