Eursr Transparency And Data

Transparency & Data (eursr-transparency-and-data)

ESR's transparency expectations are stricter than a sharing norm: a Data Availability Statement (DAS) is required for every manuscript, and for submissions received on or after 1 January 2025, authors using statistical or computational methods must deposit a replication package as a condition of publication (assembled by acceptance, typically required at conditional acceptance). Qualitative- data work is exempt from the package requirement. Confirm the current wording and effective dates on the live OUP/ESR page — this skill states the policy as verified in 2026-06; treat specifics as volatile.

When to trigger

• Writing the Data Availability Statement (needed at submission)
• Assembling the replication package ahead of conditional acceptance
• Deciding what can be shared given confidentiality, DUA, or proprietary constraints (register data)
• A reviewer or editor asked how the analysis can be reproduced

What the ESR policy requires (verify current wording)

• Data Availability Statement in every article — describing how the data can be accessed and the conditions for access (open, controlled/enclave, on-request, or restricted).
• Replication package for statistical/computational papers, due at conditional acceptance: the code, the constructed/analysis data (or a documented access path when redistribution is barred), and documentation sufficient to regenerate every reported result.
• Exemption: research using qualitative data (interviews, participant observation) is not required to submit a replication package.
• Restricted data path: where register/administrative data (e.g., national statistical offices, SOEP, EU-SILC scientific-use files) cannot be redistributed, share all code plus a precise access route (provider, file version, DUA), so a qualified researcher could reproduce the results.

Build a package that reproduces (do this from the start)

• One master script regenerates every table/figure from the (constructed) data, in order.
• Set and report seeds for imputation, bootstrap, and MCMC; pin versions (renv.lock, requirements.txt, recorded ssc/net installs).
• Archive the harmonization/recoding code (ISCED/CASMIN, ISCO/ISEI/EGP) — it is part of the result.
• README documenting data sources and versions, run order, expected outputs, runtime, and any access restrictions.
• Deposit in a citable repository (e.g., OSF, Zenodo, GESIS) and reference it in the DAS.

Transparency posture by data type (ESR)

Worked micro-example (illustrative)

A comparative scarring paper uses public ESS plus a restricted national register linkage.

DAS: "ESS Round data are openly available from the ESS Data Archive (edition cited). The linked
  register data are accessible to qualified researchers via [national statistical office] under a data-
  use agreement; all analysis and harmonization code is provided in the replication package."
Package (for conditional acceptance): master.R + harmonization scripts + constructed analysis file for
  the ESS portion; full code for the register portion with a documented access path; seed = 2026;
  renv.lock pinned; README with run order and runtime; deposited on Zenodo with a DOI.
Statistical method → not exempt → package required.

The posture shares what supports the claims, documents provenance, and is explicit about what cannot be redistributed and how to obtain it — exactly what ESR's mandate expects.

Referee / editor pushback → ESR-specific fix

• "Your register data can't be shared, so this isn't reproducible." → Provide all code plus a precise access route (provider, version, DUA); the policy accommodates restricted data via an access path, not an exemption from code.
• "The DAS is vague." → Name the archive/provider, the data version/edition, and the exact access condition; a generic "data available on request" is weak.
• "Numbers don't match your code." → Re-run the master script end-to-end before depositing; mismatches read as a credibility failure under the mandate.

Calibration anchors

• A replication package is a condition of publication, not a courtesy. For statistical/computational work submitted from 1 Jan 2025, plan it from day one — it is not an afterthought at acceptance.
• Restricted data still requires shareable code. ESR's mandate is satisfied by code + a documented access path, not by declaring the data private.
• The DAS is required for everyone. Even exempt qualitative work needs a Data Availability Statement; confirm the current wording and effective dates on the live page.

Anti-patterns

• Treating the replication package as optional or leaving it to the last minute
• A vague "data available on request" DAS with no provider, version, or access condition
• Claiming a qualitative exemption for a statistical/computational paper
• Omitting the harmonization/recoding code from the package (the result is not reproducible without it)
• Depositing code whose output does not match the manuscript's tables

Output format

【DAS】drafted, names archive/provider + version + access condition? [Y/N]
【Package required?】statistical/computational (yes) vs. qualitative (exempt)
【Package contents】master script + data/access path + harmonization code + seeds + README? [Y/N]
【Restricted data handled】code shared + documented access route? [Y/N]
【Policy check】current ESR DAS + replication wording/dates confirmed? [Y/N/待核实]
【Next】eursr-review-process

Supplementary resources

• ../../resources/external_tools.md — repositories (OSF / Zenodo / GESIS), reproducibility tooling
• ../../resources/code/ — master-script + pinned-version skeleton to base the package on
• ../../resources/official-source-map.md — ESR Data Availability + replication policy and effective dates

Source: brycewang-stanford/Awesome-Journal-Skills → European-Sociological-Review-Skills/skills/eursr-transparency-and-data/SKILL.md