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name: sci-data description: Use to build Science's data, code, and materials availability — mandatory deposition in approved repositories, accession numbers, a compliant data-availability statement, and materials/reagent sharing.

Data, Code & Materials Availability (sci-data)

When to trigger

• There is no data-availability statement, or it says "available on request".
• Sequences/structures/datasets are not deposited or have no accession numbers.
• Custom analysis code is not in a public repository.
• Unique reagents/strains/cell lines have no sharing plan.

Science's standard (the bar)

Science requires that all data and methods needed to evaluate and reproduce the conclusions be available at publication. "Available upon request" is not sufficient for primary data underlying the results.

Deposit in approved repositories (with accessions)

Data type	Deposit in (examples)
Nucleotide / genome sequences	GenBank / ENA / DDBJ
High-throughput sequencing	GEO / SRA / ArrayExpress
Protein structures	PDB; maps → EMDB
Proteomics	PRIDE / ProteomeXchange
Crystallographic data	CCDC / CSD
Generic datasets	Dryad / Zenodo / Figshare / OSF
Code	GitHub/GitLab + archived to Zenodo (DOI)

• Obtain accession numbers / DOIs before submission; cite them in the data-availability statement and Methods.
• Code that produces the results must be public; archive a release to get a citable DOI (a bare GitHub link is not durable).

Data-availability statement (template)

All data needed to evaluate the conclusions are present in the paper and/or the Supplementary Materials. [Sequencing data are deposited at GEO under accession GSEXXXXXX.] [Structures are deposited at the PDB under XXXX.] [Analysis code is available at Zenodo (DOI: 10.5281/zenodo.XXXXXXX).] [Any additional materials are available from the corresponding author / under an MTA as noted.]

Avoid bare "data available on request" for primary data; restricted human/clinical data must state the access procedure and the controlling body.

Materials & reagents

• Unique materials (plasmids, cell lines, strains, antibodies) should be available, e.g., via Addgene/repositories or under an MTA; state how.
• Identify key reagents with RRIDs where available.

Ethics & compliance (as applicable)

• Human-subjects: IRB/ethics approval + informed consent statement.
• Animal work: IACUC/animal-ethics approval and guideline compliance.
• Field/biodiversity: permits and the Nagoya Protocol where relevant.
• Dual-use / biosafety: flag if applicable.

Data pass for Science

Use this as a second-pass capability check. First lock the broad discovery claim, decisive evidence, uncertainty/limitations, and why the result belongs in a general-science weekly; then test whether the manuscript addresses general-science reviewers and editors who ask whether the result changes a broad field, is technically decisive, and can be understood outside the subdiscipline.

• Primary move: Name data provenance, availability, code/materials access, restrictions, quality control, and the exact evidence needed to reproduce the central result.
• Decision ledger: return claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.
• Neighbor test: compare against Nature for similar broad-scope novelty, PNAS for academy-wide breadth, specialist journals when the claim is field-internal; if the neighboring outlet has the stronger audience claim, recommend re-routing before polishing.
• Verification floor: before submission-ready advice, re-open resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.

Output format

【Data deposited】 type → repository → accession/DOI (list each)  | gaps
【Code public + archived DOI】 yes/no (link + DOI)
【Availability statement】 drafted? compliant (no "on request" for primary data)?
【Materials sharing】 plan for unique reagents (Addgene/MTA)
【Ethics approvals】 IRB / IACUC / permits present where needed?
【Next】 sci-abstract

Anti-patterns

• Do not write "data available on request" for the primary data behind figures.
• Do not link only to a personal/lab website (not durable) — use an archival repository with a DOI.
• Do not forget to make code public and versioned; reviewers may try to run it.
• Do not submit without accession numbers in hand for deposited data.