CASRAI Dictionary

Tag: scholarly record

  • What Is Research? Meaning, Types and the Research Lifecycle

    Research is a systematic process of investigation undertaken to discover new knowledge, confirm or revise existing understanding, and answer questions that have not yet been adequately resolved. What separates research from casual enquiry is its systematic character: it follows a planned, transparent method, gathers evidence deliberately, and subjects its conclusions to scrutiny. The result is intended to be reliable knowledge that others can examine, build upon and, ideally, reproduce.

    Basic and applied research

    Research is commonly divided into two broad orientations. Basic research, sometimes called fundamental or pure research, seeks to expand understanding for its own sake, without a specific application in mind. Investigating how a protein folds or why a mathematical relationship holds is basic research. Applied research addresses a particular practical problem: developing a treatment, improving a manufacturing process or evaluating a policy. The two are not rivals but a continuum, and basic findings frequently enable later applied advances.

    Type Primary aim Example
    Basic research Advance fundamental understanding Studying the mechanism of cell division
    Applied research Solve a defined practical problem Testing a new drug to prevent a disease

    The research lifecycle

    Most research, whatever its field, moves through a recognisable sequence of stages often described as the research lifecycle. While disciplines differ in detail, the lifecycle gives a shared vocabulary for the work and for the data and outputs it produces.

    Stage What happens
    Question Identify a gap and frame a clear, answerable research question or hypothesis
    Design Choose methods, plan sampling and analysis, address ethics and feasibility
    Data Collect, manage and document data according to the plan
    Analysis Interpret the evidence using appropriate methods and statistics
    Dissemination Report findings through publications, datasets and other shared outputs

    The lifecycle is iterative rather than strictly linear. Analysis often raises new questions, and dissemination feeds the next cycle of enquiry. Crucially, each stage generates information, about methods, samples, instruments and results, that needs to be described consistently so others can understand and reuse it.

    Analysis and the role of statistics

    The analysis stage is where evidence becomes findings. In quantitative research this typically draws on statistics, using descriptive summaries to characterise data and inferential methods to generalise responsibly. Careful analysis distinguishes signal from noise, reports uncertainty honestly through measures such as confidence intervals, and resists over-interpreting chance patterns. Weak analysis is a recognised threat to the trustworthiness of the resulting knowledge.

    Reproducibility and the scholarly record

    Research only contributes durable knowledge if its claims can be checked. Reproducibility, the ability of others to obtain consistent results using the same data and methods, depends on transparent reporting of every lifecycle stage. The scholarly record, the accumulated and citable body of publications, datasets and metadata, is the lasting product of research. CASRAI’s mission is to standardise the terminology used to describe research activities and outputs, which directly supports clearer reporting and reuse. Explore the CASRAI dictionary, the research lifecycle category and the author guidance for related resources.

    Frequently asked questions

    What makes an activity count as research?

    Research is distinguished by being systematic, methodical and aimed at producing generalisable or transferable knowledge. A planned investigation with documented methods and conclusions open to scrutiny qualifies; an unstructured opinion does not.

    Is the research lifecycle the same in every field?

    The broad stages, question, design, data, analysis and dissemination, are common across disciplines, but the methods within each stage vary widely. A laboratory experiment, a clinical trial and an archival history study share the lifecycle shape while differing in technique.

    How does CASRAI relate to research?

    CASRAI develops shared, standardised vocabularies for describing the people, activities and outputs of research. Consistent terminology across the lifecycle makes outputs easier to find, compare, reuse and reproduce, strengthening the scholarly record as a whole.

  • Equity and inclusion in authorship and the scholarly record

    Authorship is supposed to be a record of who did the research. In practice it is also a record of power. Whose name appears, in what position, and on what terms is shaped not only by who contributed but by seniority, geography, language, discipline and the structure of the global research economy. The result is a scholarly record that systematically under-represents some contributors and over-represents others, in ways that compound across careers. Addressing this is the concern of knowledge equity: making the authorship and the scholarly record a fairer, more inclusive account of who actually produces research. This article examines equity and inclusion in authorship, drawing on the knowledge equity domain of the CASRAI Dictionary.

    How authorship reflects power, not just contribution

    The inequities show up in patterns that are by now well documented in the research literature on the subject. Seniority can crowd out the people who did the bench work, with junior researchers’ contributions absorbed into a supervisor’s standing. Authorship position — which carries enormous weight in evaluation — is often negotiated through influence rather than assigned by contribution. And at the global scale, researchers from the global south who collect data, provide local expertise and enable studies in their own contexts are frequently relegated to junior positions or omitted entirely, a pattern sometimes called ‘helicopter’ or parachute research, in which outside researchers extract data and depart, taking the credit with them. None of these patterns is consistent with the principle that authorship should track real intellectual contribution. They reflect, instead, who holds power in the research relationship.

    Why this matters for the whole record

    These are not only individual injustices, serious as those are. When authorship systematically misrepresents who did research, the scholarly record itself becomes distorted. It overstates the role of established centres and understates that of contributors at the margins, which in turn shapes who gets funded, hired and promoted — reinforcing the very imbalances it reflects. A record that does not accurately represent its contributors cannot support fair evaluation, and it gives a misleading picture of where knowledge actually comes from. Equity in authorship is therefore a matter of the record’s accuracy and usefulness, not only of fairness to individuals.

    Contribution transparency as an equity tool

    One of the most practical levers for fairer authorship is making contribution explicit. When a paper records what each person actually did — rather than leaving it to be inferred from author order — several of the mechanisms that disadvantage less powerful contributors lose their grip. A junior researcher’s substantial work becomes visible as a stated contribution rather than being absorbed into a senior name; a local collaborator’s essential role in data collection and contextual expertise is named rather than erased; and disputes about position matter less when the substance of each contribution is on the record. The CRediT taxonomy — whose full set of contribution types is described in our overview of the CRediT roles — is a direct equity instrument in this sense: by making who-did-what explicit and machine-readable, it counteracts the tendency of author order to reward status over contribution. Transparency does not by itself dismantle power imbalances, but it makes them harder to hide and easier to challenge.

    Inclusion across the research relationship

    Equitable authorship is part of a broader practice of inclusion that runs through the whole research relationship, not just the byline. Several principles recur in efforts to make research collaborations fairer:

    • Recognise local and community contributions. The people who enable research in a particular setting — through local expertise, data collection, access and contextual knowledge — should be named as the contributors they are, not treated as facilitators.
    • Share authorship and leadership equitably. Collaborations, especially across resource boundaries, should plan authorship and leadership roles fairly from the outset rather than defaulting to the more powerful partner.
    • Address language barriers. The dominance of a single publication language disadvantages researchers who work in others, and inclusive practice means valuing and supporting research communicated in multiple languages.
    • Discuss credit early. Many inequities and disputes arise because authorship is settled late, under pressure. Agreeing principles for contribution and authorship at the start of a collaboration prevents much later unfairness.

    Bibliodiversity and a plural scholarly record

    Equity in the scholarly record extends beyond individual authorship to the diversity of the record itself — what is sometimes called bibliodiversity. A scholarly system dominated by a narrow set of languages, publishers, formats and regions is less equitable and, ultimately, less rich. Bibliodiversity values a plurality of publishing venues and models, supports research published in many languages and in regional and community contexts, and resists the homogenisation that concentrates the record in a few dominant channels. A more diverse scholarly ecosystem gives a fuller and fairer picture of global knowledge — one in which the contributions of the global south and of smaller research communities are part of the record on their own terms, not only when filtered through dominant centres.

    A consistent vocabulary for a fairer record

    Many of the practical principles discussed here — recognising contribution, agreeing authorship fairly and early, naming local collaborators — are reflected in our broader guidance on authorship. For these principles to make the record genuinely fairer, the way contribution and authorship are described must mean the same thing across the diverse systems, languages and institutions that make up global research. That consistency is what the CASRAI Dictionary provides: a shared vocabulary so that a contribution made anywhere, by anyone, can be described and recognised the same way everywhere. Equity in authorship is, in the end, about making the scholarly record tell the truth about who does research — and a common, well-defined language is part of how that truth is kept.

  • What Is a Citation? Definition, Purpose and Components

    A citation is a standardised reference that identifies a source you have used, quoted, paraphrased or relied upon in a piece of scholarly work. Every complete citation has two halves that work together: a brief in-text marker placed at the point of use, and a full reference entry in a list at the end of the document. Together they let any reader trace a claim back to its origin and locate the exact source consulted.

    Citation is the connective tissue of the scholarly record. It assigns credit, supports verifiability, and links each new contribution to the body of work it builds upon. Without consistent citation, a research claim becomes an assertion that no one can check.

    The two components of a citation

    A working citation is never a single object. It is a pairing:

    • The in-text citation — a compact pointer inside the running text, such as an author–date marker (Smith, 2021) or a numeric marker [4]. It signals that the adjacent statement draws on an external source.
    • The reference entry — the full bibliographic record in the reference list, carrying enough detail (author, year, title, container, publisher or journal, and a persistent identifier) to retrieve the source unambiguously.

    The marker is deliberately short so it does not interrupt reading; the entry is deliberately complete so retrieval never fails. We explore this pairing in depth in in-text citations versus the reference list.

    Anatomy of a reference entry

    Although formatting varies by style, the underlying data elements are stable across the scholarly record:

    Element Purpose
    Author / contributor Assigns credit and supports name disambiguation (often via an ORCID iD)
    Year of publication Places the work in time and signals currency
    Title Identifies the specific work
    Container Journal, book or repository in which the work appears
    Persistent identifier A DOI or Handle that resolves to the source regardless of where it is hosted

    The persistent identifier matters most for durability. A DOI, issued through infrastructure such as Crossref and resolved by the Handle System, points at the work itself rather than a fragile web address, so the citation remains actionable even when a publisher reorganises its site.

    Why citation underpins the scholarly record

    Citation performs several functions at once, and each is essential to how research accumulates.

    Attribution and credit

    A citation acknowledges whose ideas, data or words you are using. Accurate attribution is the practical mechanism by which the authorship contribution of others is recognised, and it is the first defence against plagiarism. Proper citation is precisely what separates legitimate use of a source from plagiarism.

    Verifiability and integrity

    Because a citation lets a reader retrieve the original source, it makes a claim checkable. This verifiability is foundational to research integrity: peer reviewers, replicators and later authors can confirm that a cited source genuinely supports the statement attached to it.

    Discoverability and the citation graph

    Citations connect documents into a navigable network. Following references backwards reveals a work’s intellectual foundations; tracking citations forwards reveals its influence. This citation graph powers literature searches, bibliometric analysis and the everyday act of finding the next relevant paper.

    Citation, reference and bibliography distinguished

    These three terms are frequently confused. They are related but not interchangeable.

    Term What it is
    Citation The complete act of crediting a source — both the in-text marker and its matching entry
    Reference A single full entry in the reference list; a reference list contains only sources actually cited in the text
    Bibliography A broader list that may include background reading consulted but not directly cited

    For a fuller treatment of these lists and how to build them, see our explainer on what a bibliography is and how to compile one.

    Frequently asked questions

    Is a citation the same as a reference?

    No. A reference is the single full entry in your reference list. A citation is the wider act of crediting that source, which includes both the in-text marker and the matching reference entry. Every in-text citation should map to exactly one reference entry, and vice versa.

    What is the difference between a reference list and a bibliography?

    A reference list contains only the sources you actually cited in the text. A bibliography may additionally list works you read for background but did not cite. Some styles use the word “bibliography” for what other styles call a reference list, so always follow your chosen style’s conventions.

    Why do citations include a DOI?

    A DOI is a persistent identifier that resolves to the source even if the hosting URL changes. Including it makes a citation durable and machine-actionable, improving both long-term retrievability and discoverability across the scholarly record.

    Does every citation style format references the same way?

    No. The underlying data elements are stable, but their order, punctuation and emphasis differ by style. Compare the major systems in our guide to citation styles compared, and consult the CASRAI dictionary for standardised term definitions.

  • Preprints and peer review: how the version of record fits together

    A single piece of research now commonly exists in three or four forms at the same time: a preprint posted before review, an accepted manuscript that has passed review but not yet been typeset, and the final published version of record — sometimes with a later corrected or updated version on top. Readers, and even authors, routinely confuse them, and citing the wrong one can misrepresent what was actually validated. This article sets out what each version is and how peer review sits between them. It builds on the broader taxonomy in the research-outputs domain and pairs with the side-by-side explainer at preprint versus published article.

    The versions, in order

    The preprint

    A preprint is a complete research manuscript posted to a public server — arXiv, bioRxiv, medRxiv, SSRN, and many others — before, or in parallel with, formal peer review. Its defining feature is speed and openness: it makes findings available immediately and citable via a persistent identifier, usually a DOI, without waiting for a journal’s review cycle. Its defining limitation is the flip side of the same coin: a preprint has not been through independent peer review, so its claims have not been externally vetted. A preprint is a legitimate, citable output — not a lesser draft — but it carries a different epistemic status from a reviewed article, and that status must be made clear wherever it is used.

    Peer review: the step between

    Between the preprint and the published article sits peer review — independent evaluation by qualified reviewers, organised by a journal editor, which may accept, reject, or (most often) require revision. Peer review is not a guarantee of correctness; it is a quality-control and improvement process. What it changes is the manuscript’s standing: a reviewed and accepted article carries the journal’s editorial endorsement that the work met its standards, which a preprint does not. Understanding this is the key to the whole picture — the versions differ mainly in what has happened to them, and peer review is the event that separates the unreviewed preprint from the validated article.

    The accepted manuscript (postprint)

    Once peer review concludes and the journal accepts the paper, the author’s final reviewed-and-revised file is the accepted manuscript, often called the postprint or author-accepted manuscript (AAM). It contains the intellectual content that passed review but lacks the publisher’s copy-editing, typesetting, and final pagination. The accepted manuscript is the version most commonly self-archived in institutional repositories under green open access, frequently after an embargo. It is content-equivalent to the published article in its claims, but it is not the citable, formatted final object.

    The version of record

    The version of record (VoR) is the final, published, formally citable version: copy-edited, typeset, paginated, assigned its DOI, and lodged with the publisher as the authoritative instance of the work. It is the version the scholarly record points to, the one that carries any later corrections or retractions, and the one that should normally be cited. The concept of a version of record exists precisely so that, among several coexisting forms, there is one designated authoritative object that the record and its corrections attach to.

    How they fit together

    The clean way to hold this in mind is as a sequence of states of one work:

    1. Preprint — complete, public, citable, not peer-reviewed.
    2. (Peer review happens.)
    3. Accepted manuscript / postprint — peer-reviewed content, not yet publisher-formatted; the usual green-OA archive copy.
    4. Version of record — the final, formatted, authoritative, citable version.

    Crucially, these can all exist simultaneously and should link to one another. A well-managed preprint server displays a link from the preprint to the published version of record once it appears; the version of record, in turn, may acknowledge the preprint. Persistent identifiers are what make this linkage reliable: the preprint and the VoR each have their own DOI, and the relationship between them is recorded in metadata so that a reader arriving at one can find the other.

    Which version to cite

    • Cite the version of record where it exists. It is the authoritative, corrected, formally published instance, and citing it ensures your reference points to what was validated and to any subsequent corrections.
    • Cite the preprint as a preprint when that is genuinely what you used — for example a result not yet published elsewhere — and label it clearly as a preprint, with its DOI, so a reader knows it has not been peer-reviewed.
    • Do not cite a preprint as though it were the published article. If a version of record now exists, prefer it; the preprint and the final version can differ in their conclusions after revision.
    • Check for a newer version. Preprints are often updated; the VoR may carry corrections. Cite the specific version you relied on, and prefer the most authoritative current one.

    A note on what preprints do and do not change

    Preprints have made research faster and more open, and they are now a first-class part of the scholarly record rather than a fringe practice. But they do not replace peer review or the version of record; they sit before them. The healthiest reading of the current landscape is not preprint versus journal but a pipeline in which the same work moves from open-but-unreviewed to reviewed-and-authoritative, with each stage clearly labelled and linked. Confusion arises only when the labels are dropped — when a preprint is presented, or cited, as if it had the standing of the version of record.

    Where shared vocabulary fits

    “Preprint”, “postprint”, “accepted manuscript”, and “version of record” are used inconsistently — and sometimes interchangeably — across servers, repositories, and citation styles, which is exactly how the wrong version ends up cited. A shared, federated vocabulary that defines these versions precisely and records the relationships between them is what lets a citation point unambiguously to the right object. Supplying that definitional layer is the role the CASRAI dictionary is designed to play; the relevant terms sit in the research-outputs domain.

    Related reading

  • Retractions and corrections: how the scholarly record self-corrects

    A retraction notice is often read as a verdict of disgrace. It is more accurate, and more useful, to read it as the scholarly record doing the one thing it is supposed to do: correcting itself in public. Science advances by being checkable, and a record that could never be amended would be a record nobody should trust. The mechanisms for amending it — corrections, expressions of concern, and retractions — are part of the basic infrastructure of trustworthy scholarship, and they sit squarely in the research-integrity domain. This article sets out how they differ, what governs them, and why a well-flagged record is a sign of health, not failure.

    Three different instruments for three different problems

    The single biggest source of confusion is treating “retraction” as a catch-all for any post-publication change. In fact there are three distinct instruments, each appropriate to a different situation, and using the wrong one does real damage.

    • Correction (sometimes erratum or corrigendum). The published work is fundamentally sound, but a discrete error needs fixing — a mislabelled figure, a transcription mistake in a table, a wrong affiliation, a miscalculated value that does not change the conclusions. A correction amends the specific error while leaving the article standing. By long convention an erratum denotes a publisher-introduced error and a corrigendum an author error, though many journals now use a single neutral “correction” label.
    • Expression of concern. An interim notice issued when serious questions have been raised about a publication but the matter is not yet resolved — for example, an investigation is under way, or the editors cannot obtain the underlying data. It alerts readers that the work is under scrutiny without prejudging the outcome. It is deliberately provisional, and should later be replaced by a correction, a retraction, or a notice that concerns were not substantiated.
    • Retraction. The strongest instrument, used when the findings are so unreliable that the published conclusions can no longer be relied upon — whether through honest error or misconduct. A retraction does not delete the article; the work remains visible and citable, but it is clearly marked as retracted so that no reader mistakes it for current, dependable science.

    What the COPE guidelines say

    The reference point for how all of this should be handled is the Committee on Publication Ethics (COPE), whose retraction guidelines are the most widely adopted standard among journals and publishers. COPE’s framing is important: retraction exists to correct the literature and protect its integrity, not to punish authors. The guidelines set out the grounds on which editors should consider retraction, including clear evidence that findings are unreliable (from misconduct such as fabrication or falsification, or from honest error), redundant publication, plagiarism, unethical research, or compromised peer review.

    Equally important are COPE’s expectations for the notice itself. A retraction notice should be linked to the retracted article in both directions, be freely available to all readers rather than paywalled, clearly state who is retracting and on what grounds, and distinguish — as far as possible — misconduct from honest error. COPE also stresses that retraction should be reserved for cases where the findings are genuinely unreliable; where the core results hold and only a part is affected, a correction is the proportionate response.

    Honest error is not the same as misconduct

    A persistent and damaging myth is that being associated with a retraction is always a mark of wrongdoing. It is not. A substantial share of retractions stem from honest error — a contaminated cell line, a coding bug in an analysis pipeline, an unreproducible result the authors themselves discovered and reported. Authors who proactively retract their own flawed work are practising good science, and the integrity system should reward that candour rather than penalise it. This is precisely why COPE asks that notices state the reason: a self-initiated retraction for honest error and a retraction forced by an investigation into fabrication are very different events that happen to share a label.

    Where retraction does intersect with misconduct — fabrication, falsification, plagiarism, or the industrial-scale fraud of paper mills — it becomes one of the most important tools the community has for cleaning the record. But conflating the two discourages exactly the honest self-correction the system most needs.

    Why a flagged record is a healthy record

    It can seem paradoxical that visibly marking work as unreliable makes the literature more trustworthy, but it follows directly from how science works. The alternative to a clear retraction is not a pristine record — it is an unreliable result sitting silently in the literature, being cited and built upon as though it were sound. A retraction that is properly linked, freely readable, and clearly reasoned stops that contamination from spreading. The danger is not retraction; the danger is unflagged error.

    This is also why persistence matters. A retracted article should not vanish: its DOI must continue to resolve, ideally to a version prominently watermarked as retracted, so that anyone who follows an old citation arrives at the correct status rather than a dead link or, worse, an unmarked copy. Crossref and similar infrastructure carry retraction status in metadata so that reference managers and discovery tools can surface it automatically — the record corrects itself not only on the page but in the machine-readable layer that downstream systems read.

    Crediting accountability, not just authorship

    Corrections and retractions also raise a question of responsibility, and here the structure of contribution metadata matters. The CRediT taxonomy records who did what on a paper, and one role — the corresponding author’s accountability for the integrity of the work — is precisely the locus of responsibility when something goes wrong. Knowing, in structured form, who curated the data, who ran the analysis, and who supervised the work helps an investigation establish where an error arose and who is answerable for it. Honest contribution records do not prevent error, but they make accountability legible when error surfaces, which is exactly when clarity is most needed.

    Where shared vocabulary fits

    “Retraction”, “correction”, “erratum”, “corrigendum”, and “expression of concern” are used loosely — and sometimes interchangeably — across journals, which muddies a reader’s ability to judge what a notice actually means. A shared, federated vocabulary that defines these instruments precisely — and points back to COPE for the governing guidelines — is what lets a retraction in one venue be understood the same way in another. Supplying that definitional layer is the role the CASRAI dictionary is designed to play; the relevant terms sit in the research-integrity domain.

    Related reading

  • Living and versioned research outputs: dynamic publications and continuous updates

    For most of the history of scholarly publishing, a research output has been a fixed thing. A paper is written, reviewed, published and then, save for the occasional correction, frozen: the version that appears is the version that endures, cited and read in exactly the form it was issued. There is a real virtue in this fixity — a stable, citable record everyone can refer to with confidence. But there is also a tension, because knowledge does not stand still. New evidence arrives, errors are found, methods improve, and a static document published years ago may no longer reflect what is known. A growing class of living and versioned research outputs tries to resolve this tension by allowing outputs to be updated over time while remaining citable and trustworthy. This article explores those outputs and the challenges they raise, drawing on the research outputs domain of the CASRAI Dictionary.

    Living systematic reviews

    The clearest example of a deliberately dynamic output is the living systematic review. A systematic review gathers and synthesises all the available evidence on a question, and it is enormously valuable — but it has a built-in problem: the moment it is published, it begins to go out of date, because new studies keep appearing. In a fast-moving field, a review can be obsolete within a year or two, yet it may continue to be cited as authoritative. A living systematic review addresses this by being continuously or regularly updated as new evidence emerges, rather than being conducted once and left to age. The review becomes an ongoing process — a maintained synthesis that keeps pace with the literature — rather than a one-off snapshot. This is invaluable in areas where keeping current matters most, but it changes the nature of the output: it is no longer a fixed document but a living one, and that has consequences for how it is cited and trusted.

    Versioned preprints

    A different but related development is the versioned preprint. Preprints — research papers shared publicly before, or alongside, formal peer review — are inherently dynamic: an author posts an early version, receives feedback, revises, and posts a new version, often several times. Preprint servers handle this through explicit versioning, so that version 1, version 2 and so on each exist as distinct, citable entities, and a reader can see both the latest version and the history of how the work evolved. This is honest and useful: it shows the work developing, and it lets a reader cite the specific version they actually read. But it also means that “the preprint” is not a single thing — it is a series of versions, and which one a citation refers to genuinely matters.

    The version-of-record problem

    All of this raises a fundamental question that the traditional model never had to face squarely: in a world of multiple versions, what is the version of record? The version of record is, classically, the definitive, citable version of a work — the one the scholarly record points to as authoritative. When outputs were fixed, this was simple. When an output exists in many versions, or is continuously updated, several questions become pressing:

    • Which version is authoritative — the latest, or the one a given reader relied upon?
    • How do citations stay precise when the thing being cited keeps changing?
    • How is the history preserved so that a claim made on the basis of an earlier version can still be checked against that version?
    • How does a reader know they are looking at the current state of a living output, rather than a superseded one?

    These are not merely technical questions; they go to the heart of what makes the scholarly record reliable. A record that changes without trace would be untrustworthy; a record that cannot be updated would be inaccurate. The challenge is to allow updating while preserving citability and history.

    How DOIs handle versions

    The infrastructure that makes versioned outputs workable is the persistent identifier, and in particular the way DOIs can be assigned to versions. A common and powerful pattern is to mint a DOI for each specific version of an output and a separate “concept” or top-level DOI that always points to the latest version of the work as a whole. This gives the best of both worlds: someone who wants to cite exactly what they read can cite the version-specific DOI, confident it will always resolve to that exact version; while someone who wants to point readers to the current state can use the concept DOI, which follows the work as it evolves. Versioning at the identifier level is what lets a living output be both stable (each version is fixed and permanently citable) and dynamic (the work as a whole keeps moving forward). It reconciles the apparent contradiction between fixity and change.

    Continuously updated outputs more broadly

    Living reviews and versioned preprints are the prominent cases, but the underlying pattern — outputs that are maintained and updated rather than issued once and frozen — appears elsewhere too: datasets that grow and are re-released, software that moves through versions, guidelines and protocols that are revised as practice changes. In each case the same principles apply: clear versioning, persistent identifiers for both specific versions and the evolving whole, and transparent records of what changed and when. The broad taxonomy of modern research outputs increasingly has to accommodate things that change over time, not just things that are finished and fixed.

    A shared vocabulary for versions and outputs

    For versioned and living outputs to work across repositories, publishers and citing systems, the concepts involved must be described consistently — what a version is, how it relates to the work as a whole, which is the version of record, and how the relationships between versions are expressed. Inconsistency here breaks exactly the citability that versioning is meant to preserve. That consistency is what the CASRAI Dictionary supports: a shared vocabulary so that version and output information is understood identically wherever it appears. And because maintaining a living output over time is genuine, ongoing contribution, the work can be described in the same framework used for every other — the CRediT taxonomy and its full set of contribution roles. The scholarly record is learning to do something it never used to: stand still enough to be trusted while moving enough to stay true.

  • Post-publication peer review and research sleuths: PubPeer and self-correction after publication

    It is tempting to think of peer review as a gate: a manuscript is scrutinised, it passes, it is published, and the matter is closed. But publication is not the end of scrutiny — or it should not be. Errors slip through review, problems become visible only once a paper is read widely, and occasionally misconduct is detected only after the work is in the literature. A scholarly record that could never be questioned after publication would accumulate its mistakes forever. Post-publication peer review is the practice of continuing to scrutinise work after it appears, and it has become an essential part of how the literature corrects itself. This article examines that practice and the people and platforms behind it, drawing on the research integrity domain of the CASRAI Dictionary.

    What post-publication peer review is

    Post-publication peer review is exactly what its name suggests: the evaluation of a published work by the community after it has appeared, rather than only by selected reviewers before it appears. It can take many forms — a published commentary, a letter to the editor, a structured review on a dedicated platform, or an informal note on social media. What unites them is the recognition that the few reviewers who assessed a paper before publication are not the last word on it, and that the wider community of readers can identify problems the original reviewers could not. It treats the published paper not as a closed case but as a claim that remains open to examination.

    PubPeer and the online commentary layer

    The best-known infrastructure for post-publication review is PubPeer, an online platform that allows readers to comment on published papers, identified by their DOI or other identifier. PubPeer functions as a kind of comment layer over the literature: a place where someone who notices a problem — an apparently duplicated image, an implausible statistic, a method that does not add up — can post their observation for others to see and discuss, often anonymously. Anonymity is a deliberate and important feature, because raising concerns about published work, particularly the work of senior or powerful researchers, can carry real professional risk. PubPeer has become a significant venue where concerns about specific papers are aired, examined and, in many cases, ultimately acted upon by journals and institutions. It has made post-publication scrutiny visible and persistent in a way that scattered private worries never were.

    Research sleuths

    Alongside the platforms is a community of individuals who have become known as research sleuths or integrity investigators: people who systematically examine the published literature for signs of error or misconduct. Some focus on image integrity, developing a practised eye for duplicated, manipulated or reused figures; others look for statistical impossibilities, tortured phrasing characteristic of manipulated text, or patterns suggesting paper-mill production. Their work is often painstaking, frequently voluntary, and sometimes carried out at personal cost. These sleuths have been responsible for surfacing a substantial number of serious problems that formal pre-publication review missed, and their findings — often posted on platforms like PubPeer — have triggered investigations, corrections and retractions. They represent a distributed, motivated form of scrutiny that complements the formal systems, catching things those systems were never designed to catch.

    From concern to correction

    Raising a concern is only the beginning; the question is what happens next. The journey from an observation to a formal change in the record typically runs through several stages:

    • A concern is raised — on a platform such as PubPeer, in a letter to the journal, or directly to an institution.
    • The journal or institution investigates. Editors may issue an expression of concern to flag that a paper is under question while inquiries proceed.
    • A correction is made where the problem is genuine but limited — a corrigendum that fixes the specific error.
    • A retraction is issued where the problems are serious enough to undermine the work’s reliability, formally signalling that the findings should not be relied upon.

    These mechanisms are how the published record is actually changed, and they are the formal counterpart to the informal scrutiny that surfaces the problems in the first place.

    The role of COPE

    The handling of these situations is not improvised; it is guided by established norms. The Committee on Publication Ethics (COPE) provides guidance to editors and publishers on how to respond to concerns about published work — how to investigate fairly, when an expression of concern is appropriate, how to handle corrections, and the proper grounds and process for retraction. This guidance matters because post-publication scrutiny, for all its value, must be handled responsibly: authors are entitled to due process, a concern is not the same as a proven fault, and the record must be changed carefully and transparently rather than reactively. COPE’s frameworks give editors a principled basis for turning a raised concern into a fair and proportionate response.

    Self-correction as a feature, not a failure

    It is worth stating plainly: a retraction or correction is not a sign that science is broken. It is a sign that the self-correcting mechanism is working. The alternative — a literature in which flawed work, once published, can never be challenged or corrected — would be far worse. Post-publication peer review, the platforms that host it, the sleuths who drive much of it, and the editorial processes that turn its findings into formal action are together the visible machinery of a scholarly record that takes its own reliability seriously. The willingness to revisit and correct published work is one of the things that distinguishes a healthy research culture from a complacent one.

    Describing integrity work consistently

    For concerns, investigations, corrections and retractions to be handled and recorded consistently across journals and institutions, the terms involved must mean the same thing everywhere — what counts as an expression of concern, a correction or a retraction, and how each is recorded. That consistency is what the CASRAI Dictionary supports: a shared vocabulary so that the status of a published work is understood identically wherever it appears, which underpins sound research administration. And because scrutiny after publication is itself genuine scholarly contribution, the work of reviewing and correcting can be described in the same framework used for every other — the CRediT taxonomy and its full set of contribution roles. The scholarly record is trustworthy not because it is never wrong, but because it has robust ways of putting itself right.