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?
- Why Are Data Managers and Software Engineers Excluded From the Byline?
- How Can Institutions Use CRediT Roles in Performance Review?
- What Does CRediT Leave Undefined? The Degree-of-Contribution Gap
- Frequently Asked Questions About CRediT Roles
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.