From DAS to Deposit: Navigating Publisher Data Policies
If you have submitted a paper in the last few years, you have probably been asked for a Data Availability Statement (DAS). What that request means, however, varies widely. Some journals treat open data as a condition of publication. Others mainly want a statement, while leaving deposit optional or journal-dependent. A smaller group still has little more than encouragement, or no dedicated research-data policy at all.
To make that landscape usable, we started from the CHORUS Publisher Data Availability Policies Index. CHORUS maintains a regularly updated list of publisher and journal data-availability policy pages, which is practical and broad enough to cover major commercial publishers, academic societies, and open-research platforms in one place. We coded every unique entry on that index into three groups by what authors must actually do.
Most of the index sits in Group 2 (39 of 65, 60%).
Three groups, three personalities
Once the policies are grouped, common features become clearer:
Group 1: often society-led, often early
The hard open-data cluster is disproportionately shaped by academic societies and open-research platforms: earth and space science (American Geophysical Union, Copernicus / European Geosciences Union, Geological Society of America), microbiology and life-science mandates (American Society for Microbiology, Life Science Alliance), economics replication regimes (American Economic Association; University of Chicago Press titles), and open-data natives (Public Library of Science, GigaScience Press, F1000-style platforms such as Health Research Board Open Research and Routledge Open Research). Multidisciplinary hard rules from AAAS/Science, the Royal Society, Proceedings of the National Academy of Sciences, and Frontiers sit here too. These actors were frequently early adopters: FAIR / COPDESS culture, Public Library of Science–era data policies, and replication archives arrived before “DAS required” became the commercial default.
Group 2: the commercial mainstream
Group 2 is where most researchers live. It is dominated by large commercial publishers and their tiered toolkits (Springer Nature, Wiley, Elsevier, Taylor & Francis, SAGE Publishing, Oxford University Press, Cambridge University Press, American Chemical Society) plus society and journal policies that require a DAS while stopping short of a uniform public-deposit mandate (American Speech-Language-Hearing Association, Journal of Orthopaedic & Sports Physical Therapy, Society of Exploration Geophysicists, MDPI, Rockefeller University Press, The Company of Biologists, Wolters Kluwer Health). Clinical journals that follow International Committee of Medical Journal Editors (ICMJE) trial data-sharing statements (New England Journal of Medicine, American College of Physicians / Annals of Internal Medicine) also belong here: a statement is required, but open patient-level deposit is not prescribed.
Group 3: still catching up
Group 3 is smaller and uneven. It includes encouragement-only guidance (IEEE), optional artifact cultures (Association for Computing Machinery), thin or unverified dedicated mandates in some society pages, and true gaps, especially mathematics (American Mathematical Society; Society for Industrial and Applied Mathematics) and some engineering venues (SPIE; American Institute of Aeronautics and Astronautics) where CHORUS links do not lead to a research-data availability policy.
Where subjects differ
Field culture still matters. Earth and space science lead on hard mandates; life sciences are close behind; economics can be as strict as any science, technology, and medicine field while broader humanities and social sciences are mixed; clinical and health research is statement-rich but deposit-cautious; physical sciences and engineering are split; mathematics is the clearest public-policy gap.
Policy groups by subject area
How publishers specify the “level” of sharing
| Guidance model | What it means for authors | Examples | Usually maps to |
|---|---|---|---|
| Publisher policy tiers | Journal selects encouragement → DAS → deposit on a published ladder | Springer Nature, Wiley, Taylor & Francis, Elsevier, SAGE Publishing, Oxford University Press, Cambridge University Press | Group 2 |
| Uniform hard mandate | One high bar for open/public underlying data; narrow exceptions only | Public Library of Science, American Geophysical Union, Copernicus, American Society for Microbiology, Royal Society, AAAS/Science | Group 1 |
| Replication package | Data + code (+ README) sufficient to reproduce results | American Economic Association; University of Chicago Press economics titles | Group 1 |
| Artifact badges | Optional reviewed artifacts / badges (culturally powerful, not always required) | Association for Computing Machinery | Group 3 |
| ICMJE / clinical statement | Declare whether/what/when/how trial data will be shared; deposit often controlled | New England Journal of Medicine; American College of Physicians / Annals | Group 2 |
| Platform-native deposit | Data guidelines baked into the open-research publishing workflow | Health Research Board Open Research; Routledge Open Research | Group 1 |
Standards you will keep seeing: FAIR, TOP, ICMJE
Publisher data policies rarely invent requirements from scratch. Many explicitly align, or at least signal alignment, with community standards that funders, repositories, and research offices already recognize. Reading a journal’s data page is therefore also a way of seeing which external frameworks that publisher has chosen to endorse.
FAIR (Findable, Accessible, Interoperable, Reusable) is the cross-cutting vocabulary in earth/space science and increasingly across science, technology, and medicine publisher frameworks. TOP Guidelines (Transparency and Openness Promotion Guidelines, from the Center for Open Science) show up in psychology/behavioral and some transparency-focused venues. ICMJE (International Committee of Medical Journal Editors) shapes clinical trial data-sharing statements. Domain repositories (GenBank, the Protein Data Bank, the Sequence Read Archive, Gene Expression Omnibus, and peers) often function as de facto mandates in biomolecular fields even when the publisher page is short.
Software availability is catching up to data
Stronger policies increasingly treat code as part of the reproducibility package, not an afterthought. Patterns include required data-and-software availability statements (American Meteorological Society), encouraged public code with a minimum-access floor (The Company of Biologists), code folded into the definition of shareable research objects (Society of Exploration Geophysicists, SAGE Publishing, MDPI), editor-requested statistical code (American College of Physicians / Annals), and either optional artifact badges (Association for Computing Machinery) or mandatory replication code (American Economic Association).
One nuance matters for authors: including software in scope does not automatically mean deposit is mandatory. The Society of Exploration Geophysicists, for example, strongly encourages sharing but explicitly welcomes industry papers built on unsharable data or code.
How datasets and software are expected to be cited
Among the clearer policies, citation guidance is nearly as important as sharing guidance. Authors are typically asked to do more than drop a URL into a DAS.
| Citation practice | What to put in the paper | Publisher examples |
|---|---|---|
| DataCite-style elements | Creator, year, title, publisher/repository, persistent identifier in the reference list | SAGE Publishing; many FAIR-aligned journals |
| FORCE11 data citation principles | Full reference-list citation with DOI or accession; treat data as a first-class research object | Society of Exploration Geophysicists; The Company of Biologists; Oxford University Press |
| FORCE11 software citation | Cite software with version, license, and access notes | Oxford University Press; American Meteorological Society examples |
| DAS + repository link | Named repository + DOI/URL in the availability statement (sometimes also a formal cite) | MDPI; many Group 2 tiered publishers |
| ICMJE statement fields | Declare whether/what/when/how trial data will be shared | New England Journal of Medicine; American College of Physicians / Annals |
| Domain accession numbers | GenBank / Sequence Read Archive / Protein Data Bank (etc.) in the availability paragraph and references | American Society for Microbiology; life-science societies |
Explore the 65 publishers
Use the filters and list to browse the coded set. Select a publisher to open a fact card with domain, DAS expectations, open-data guidance, whether the policy is tiered, software availability expectations, and the best online policy URL.
Public Library of Science (PLOS)
What this means if you are submitting
For most researchers, the useful question is not which coarse bucket a publisher falls into. It is whether you can answer, before submission: Where are my data? Who can access them? Can someone re-run the analysis?
Here is some advice:
- Write the Data Availability Statement as a real methods paragraph. Treat it as part of the science, not a formality. Say what data exist, where they live (repository name and persistent link if public), who can access them, and any legal or ethical limits. “Available on request” alone is increasingly weak: it tells readers little about location, reuse conditions, or long-term access. If data cannot be shared openly, say why and describe the governed route instead.
- For commercial publishers, go further than the publisher brand. Springer Nature, Wiley, Elsevier, Taylor & Francis, SAGE Publishing, Oxford University Press etc often publish ladders of research-data strength. Two journals under the same imprint can differ. Always check the target journal’s selected research-data level or instructions for authors, not only the publisher’s general policy page.
- If you work with human participants or clinical data, plan governed access early. Many medical journals ask for an ICMJE-style data-sharing statement rather than open patient-level files. Align consent language, ethics approval, and controlled-access pathways with what you can honestly promise. Retrofitting a sharing plan after acceptance is much harder than designing one at protocol stage.
- Package software with the same care as datasets when results depend on code. Prefer a public repository or compute capsule with version and license notes. Even when deposit is only encouraged, reviewers increasingly ask how analyses can be repeated. A README and pinned versions often matter as much as the scripts themselves.
- Cite the data and software you share. Add repository DOIs or accession numbers to the reference list, not only a bare URL in the DAS. Where journals follow DataCite or FORCE11 guidance, treat datasets and software as first-class research objects. Domain databases (for example GenBank or the Protein Data Bank) should appear as formal citations.
- Even when a journal’s policy looks optional, do not assume that means “do nothing.” Funder or institutional rules may still require deposit. Use a trusted repository when you can: it protects you if the journal later tightens policy, and it helps readers even when the journal does not mandate it.
