技能 数据科学 ESR数据透明与可复现性报告

ESR数据透明与可复现性报告

v20260724
eursr-transparency-and-data
本指南指导作者如何满足欧洲社会评论(ESR)严格的透明度要求。它详细介绍了为统计和计算稿件准备数据可用性声明(DAS)和数据复现包的步骤。内容涵盖数据源、版本记录和处理受限数据的最佳实践,确保研究流程完全可复现和可追溯。
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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)

Data type In the package Restricted DAS framing
Public comparative survey (ESS, EVS) data + code none "openly available from [archive], version X"
EU-SILC / SOEP scientific-use file code + constructed-vars script raw microdata "available from [provider] under its access terms"
National register / administrative all code + access route raw records "accessible via [NSO/enclave] under DUA; code provided"
Qualitative (exempt) analytic documentation (optional) identifiable transcripts state the exemption + confidentiality basis

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

信息
Category 数据科学
Name eursr-transparency-and-data
版本 v20260724
大小 7.04KB
更新时间 2026-07-28
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