Tag: credit taxonomy examples

  • CRediT Taxonomy Examples: Why Fields Differ

    CRediT taxonomy examples look very different depending on where they are published: a life-sciences paper in MDPI or PLOS typically lists all 14 roles with named contributors, while a humanities article often still carries a single sentence such as “the author confirms sole responsibility for this work.” The gap is not accidental. It traces directly to publisher policy — mandatory in most STEM journals, opt-in or absent across much of the humanities — and it creates a real coordination problem for cross-disciplinary teams trying to standardise credit.

    CRediT (the Contributor Roles Taxonomy) is a 14-role system for describing the specific contributions each author made to a research output, originated by CASRAI in 2014 and now formalised as ANSI/NISO Z39.104-2022, stewarded by NISO. This article examines why uptake diverges so sharply by field, with real examples from both ends of the spectrum, and what that divergence means for teams working across disciplinary lines.

    What is the CRediT taxonomy?

    The Contributor Roles Taxonomy (CRediT) is a standardised set of 14 roles — Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft, and Writing – Review & Editing — used to describe what each named author actually did on a research output.

    CASRAI originated the CRediT contributor role taxonomy in 2014, building on earlier contributorship work from a 2012 workshop convened by Nature, Harvard University, and the Wellcome Trust. The standard is now stewarded by NISO as ANSI/NISO Z39.104-2022, published under a CC-BY 4.0 licence. Authors select only the roles relevant to their own contribution — a single author does not need to fulfil all 14.

    Why does CRediT adoption vary so much by field?

    CRediT adoption tracks publisher policy far more closely than it tracks research quality or complexity. In fields where publishers made CRediT statements mandatory at submission — largely biomedical, life-science, and multidisciplinary mega-journals — contribution statements are now routine. In fields where publishers left CRediT as an optional field or omitted it entirely — much of the humanities and parts of the social sciences — author contribution statements remain rare or absent.

    Three structural factors reinforce this split:

    • Authorship norms differ. Life-science papers routinely carry five, ten, or dozens of co-authors performing distinct technical roles, which is exactly what CRediT was built to disaggregate. Humanities scholarship is disproportionately single-authored, where a 14-role statement adds little practical value.
    • Submission-system defaults matter. Where a manuscript system makes the CRediT field required before submission, compliance is near-universal by construction. Where it is optional or absent from the template, uptake depends on individual editors and authors.
    • Funder and integrity pressure is uneven. Biomedical funders and journals face more frequent authorship disputes and integrity investigations, which has pushed publishers such as Elsevier and PLOS toward mandatory disclosure. That pressure is far lighter in most humanities publishing.

    What do CRediT taxonomy examples look like across disciplines?

    The clearest way to see the divide is to compare a typical statement from a mandating STEM publisher with a typical humanities author note.

    A life-sciences example, in the multi-role format required by publishers such as MDPI and PLOS:

    • Author 1: Conceptualization, Methodology, Software, Writing – original draft.
    • Author 2: Data curation, Formal analysis, Visualization.
    • Author 3: Investigation, Resources.
    • Author 4: Supervision, Funding acquisition, Writing – review & editing.

    A journal using the “degree of contribution” variant (as documented in Wiley’s author guidance) adds weighting:

    • Kerys Jones: Conceptualization (lead); writing – original draft (lead); formal analysis (lead); writing – review and editing (equal).
    • Elisha Roberto: Software (lead); writing – review and editing (equal).

    By contrast, a typical humanities article — for example in a history, literature, or philosophy journal that has not adopted CRediT — carries no role breakdown at all, often just: “The author declares sole responsibility for the research and writing of this article,” or, for co-authored humanities work, “Both authors contributed equally to the conception and writing of this paper.” Neither statement maps to any of the 14 CRediT roles.

    The table below sets out where major publishers currently sit on the mandate spectrum.

    Publisher / journal group Primary discipline mix CRediT policy
    PLOS Life and biomedical sciences Mandatory; among the earliest adopters, integrated into submission in 2016
    MDPI Multidisciplinary, life-science-heavy Mandatory across its journal portfolio; structured CRediT statement required at submission
    Elsevier Multidisciplinary CRediT author statement published with the article across participating journals
    Springer Nature (Nature-branded titles) Life and physical sciences Author contributions statement required; CRediT roles encouraged
    Wiley Multidisciplinary Journal-by-journal mandate; degree-of-contribution format offered
    Taylor & Francis Multidisciplinary, incl. humanities and social sciences Rolling adoption; not required across all journals
    Sage Social sciences and humanities-heavy Per-journal; Sage’s own author guidance states “not all of Sage’s journals have adopted CRediT”

    How do publisher policies drive the STEM–humanities divide?

    Publisher policy, not discipline itself, is the direct lever. Elsevier and PLOS built CRediT into the submission workflow as a required field, so authors cannot submit without completing it. MDPI applies the same mandatory approach across its entire portfolio regardless of subject area, which is why even MDPI’s humanities and social-science titles show comparatively higher CRediT completion than peer humanities journals at other presses.

    Sage and Taylor & Francis, whose portfolios include large humanities segments, have taken the opposite approach: CRediT is available but adopted journal-by-journal, and Sage explicitly tells authors to check whether their journal has adopted it before submitting. The resulting patchwork correlates with discipline mainly because humanities-heavy publishers were slower to flip the mandate switch — not because CRediT is technically unsuited to humanities scholarship.

    What does this mean for cross-disciplinary collaboration?

    The uneven mandate creates a practical problem for teams that span disciplines — digital humanities, science communication, bibliometrics, area studies with quantitative components, or any project combining a life-science co-investigator with a humanities co-investigator. One team member’s home journal may require a full CRediT breakdown; the other’s may have no contributorship field at all.

    For research administrators and institutional leaders coordinating such teams, three practical steps reduce friction:

    • Agree contributor roles internally using the CRediT taxonomy at project outset, so the record exists even if the target journal does not require it.
    • Where the venue omits a CRediT field, add a voluntary CRediT-mapped acknowledgement in the author note or supplementary material.
    • Reference the ANSI/NISO Z39.104-2022 definitions directly, rather than a publisher’s paraphrase, so contributions remain comparable across journals with different house styles.

    As more funders and institutions use contributorship data for research assessment and expert discovery, the absence of a CRediT statement in humanities-authored work increasingly reads as a data gap rather than a disciplinary choice — one that cross-disciplinary teams have a direct incentive to close voluntarily, even where their venue does not require it.

    Common questions about CRediT taxonomy examples

    What is the CRediT taxonomy?

    CRediT is a standardised, 14-role taxonomy for describing individual author contributions to a research output, covering everything from Conceptualization and Methodology to Writing – Review & Editing. It replaces vague author-order conventions with an explicit, comparable role list.

    What are the 14 roles of the CRediT taxonomy?

    The 14 roles are Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft, and Writing – Review & Editing. Authors select only the roles that genuinely apply to their contribution.

    What does “Investigation” mean in the CRediT taxonomy?

    Under CRediT, Investigation covers conducting the research process itself — specifically performing experiments or carrying out data and evidence collection. It is distinct from Methodology (designing the approach) and Formal Analysis (analysing the resulting data).

    How do authors give CRediT to a co-author in a contribution statement?

    Authors list each co-author by name followed by their applicable CRediT roles, optionally with a degree of contribution such as “lead,” “equal,” or “supporting.” For example: “Author A: Conceptualization (lead), Writing – original draft (lead).”

    The disciplinary gap in CRediT adoption is a policy artefact, not a verdict on whether contributorship matters outside the life sciences. As cross-disciplinary funding calls, digital-humanities partnerships, and research-assessment exercises increasingly draw on contributorship data, journals that have left CRediT optional will face growing pressure — from funders, from co-authors in mandating fields, and from researchers building a verifiable contribution record — to close the gap rather than leave it to the discipline they happen to publish in.

  • CRediT Roles for Data Curation and Software

    CRediT roles such as Data Curation and Software give data managers and research software engineers a standardised, citable way to be formally recognised for research contributions that byline authorship rules routinely exclude. Two of the taxonomy’s fourteen roles map directly onto their work, and institutions can use those role tags — including the optional “degree of contribution” qualifier — as documentary evidence in annual review, promotion and tenure cases.

    The Contributor Role Taxonomy (CRediT) is a controlled vocabulary of fourteen contributor roles used to describe the specific contributions individuals make to a research output, independent of authorship order. CASRAI originated the CRediT contributor role taxonomy in 2014; the standard is now stewarded by NISO as ANSI/NISO Z39.104-2022, approved in 2022.

    What Do the Data Curation and Software CRediT Roles Cover?

    Data Curation and Software are two of the fourteen roles in the CRediT contributor role taxonomy, and together they cover most of the technical infrastructure work that keeps a research output usable and reproducible. Under NISO’s definitions, Data Curation covers management activity that annotates, cleans and maintains research data — including software code where it is needed to interpret that data — for both initial use and later reuse. Software covers programming and software development: designing programs, implementing code and algorithms, and testing existing code components.

    These definitions were written broadly enough to capture roles that rarely appear on a title page:

    • Research data managers and data stewards who build metadata schemas and manage repository deposits
    • Research data librarians who oversee data management plans and long-term preservation
    • Research software engineers (RSEs) who build, maintain and test the pipelines and analysis code a study depends on
    • Bioinformaticians and computational scientists whose code is central to the result but who did not draft the manuscript

    Several adjacent roles frequently apply to the same people: Data Curation and Software combine most often with Methodology, Validation, Resources (for computing infrastructure) and Visualization. A single individual can — and typically does — hold more than one CRediT role on the same output; NISO’s implementation guidance is explicit that a role can also be assigned to multiple contributors on the same paper.

    Why Are Data Managers and Software Engineers Excluded From the Byline?

    Byline authorship is governed by criteria such as those from the International Committee of Medical Journal Editors (ICMJE), which require substantial contribution to conception, drafting or critical revision, plus final approval and accountability. Building a data pipeline or curating a dataset frequently fails one of those tests — usually drafting or revision — even when the contribution was essential to the result.

    CRediT was designed to sit alongside, not replace, those authorship criteria. NISO’s own guidance states plainly that CRediT “is not designed to determine authorship” but instead documents the specific contributions of authors and other contributors, including people who would otherwise only appear in an acknowledgements line. That separation is precisely what makes it useful for technical staff: a data manager or RSE can receive a formal, structured, machine-readable Data Curation or Software credit on an output without needing to clear the higher bar of full authorship.

    How Can Institutions Use CRediT Roles in Performance Review?

    Research institutions can treat a contributor’s accumulated CRediT role tags as structured evidence of impact, distinct from and complementary to publication counts or authorship position. Because the roles are standardised and, where publishers tag them in JATS XML, machine-readable, they can be aggregated across a person’s ORCID record rather than re-argued from scratch at every review cycle.

    Traditional CV evidence CRediT-based evidence Use in review
    Author position (2nd, 5th, etc.) Named role (Data Curation, Software) Documents what was actually done, not just list order
    General “contributed to analysis” statement Structured, standardised role plus optional degree of contribution Comparable across papers, journals and disciplines
    Acknowledgements-only mention Formal CRediT role on the same footing as co-authors Countable, citable line in annual review or promotion dossier
    Manual claim, hard to verify Machine-readable tag exportable via ORCID / Crossref metadata Independently verifiable by a review committee

    Concrete steps an institution can take:

    • Require staff to list their specific CRediT roles — not just “co-author” — against each output in annual review and promotion documentation
    • Instruct principal investigators to assign Data Curation and Software roles at the manuscript-submission stage, before contributor memory fades
    • Ask review committees to weight a sustained pattern of Data Curation or Software roles as evidence of infrastructure contribution, on comparable footing with first authorship in relevant career tracks
    • Encourage contributors to keep their ORCID record current so CRediT roles from publishers using CRediT-tagged JATS XML populate automatically

    What Does CRediT Leave Undefined? The Degree-of-Contribution Gap

    CRediT includes an optional qualifier — “lead”, “equal” or “supporting” — that can be attached where several people share the same role. This degree-of-contribution tag is exactly what a performance-review committee needs to distinguish a data manager who led curation for a multi-year cohort study from one who supported it for a single deposit. It is the single most under-used lever institutions have available inside a taxonomy most already partially adopt.

    Two constraints matter for institutions relying on it. First, NISO’s implementation guidance is explicit that degree-of-contribution is not currently part of the CRediT standard itself — individual publishers decide whether to request it, so its presence in a contributor statement is inconsistent across journals. Second, adoption of CRediT overall is uneven: PLOS has made CRediT its sole standard across all journals, while others offer it optionally through Editorial Manager (integrated since 2016) or Clarivate’s ScholarOne (integrated since 2018). Crossref has stated it will add CRediT to its publisher metadata schema in 2026, which should make role and degree-of-contribution data far easier to aggregate at the institutional level once adopted — but until then, institutions auditing technical contributions cannot assume degree-of-contribution data exists for every paper in a portfolio, and should ask contributors to supply it directly where the publisher record is silent.

    Frequently Asked Questions About CRediT Roles

    What is a credit role?

    A CRediT role is one of fourteen standardised labels — such as Data Curation, Software, Methodology or Investigation — used to describe a specific type of contribution an individual made to a research output. Roles are assigned independently of authorship order and can be combined, so one contributor may hold several roles on the same paper.

    What are the 14 credit contributor roles?

    The fourteen roles are Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, and Writing – review & editing, as defined under ANSI/NISO Z39.104-2022.

    What does role taxonomy mean?

    A role taxonomy is a fixed, controlled vocabulary that classifies types of contribution rather than free-text description. CRediT’s role taxonomy standardises how contributions are labelled across journals and disciplines, so a “Software” credit means the same thing whether the paper is in genomics or economics.

    Implications for Research Assessment

    As Crossref’s planned 2026 metadata integration and continued publisher adoption make CRediT data more machine-readable, the practical barrier to using it in institutional review shifts from availability to policy: whether promotion committees are willing to treat a Data Curation or Software role, especially one tagged “lead”, as comparable evidence to first authorship in the relevant career track. Institutions that update review criteria now — ahead of that data becoming routine — will be positioned to credit data managers and research software engineers on the strength of a standard that, unlike free-text acknowledgements, is built to be counted.