技能 数据科学 数据透明度与可复现性指南

数据透明度与可复现性指南

v20260724
govern-transparency-and-data
本指南指导作者撰写强制性的数据可用性声明,并构建全面的复现材料包。它详细介绍了数据溯源、代码管理、处理受限数据等最佳实践,旨在确保学术研究的完整性与可复现性。
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Transparency & Data (govern-transparency-and-data)

Governance requires a Data Availability Statement with the manuscript — a statement of whether replication materials (data, code) exist and how a reader can access them. Be clear-eyed about the bar: the statement is mandatory, and sharing in a DOI-citable repository is recommended and increasingly expected, but Governance does not run a verified, editor-checked pre-publication reproduction gate the way APSR's Dataverse workflow does. That makes the statement an honesty-and-access commitment, not a reproduction certificate — so write it precisely and build the materials as you go.

When to trigger

  • Writing the Data Availability Statement for submission (it is required at submission)
  • Building the replication package (data, code, documentation) to back that statement
  • Data cannot be fully shared (privacy, ethics, legal/provider restrictions) and you need the exemption/access path
  • A qualitative or comparative-historical paper needs a transparency plan for sources and process tracing
  • Referencing a preregistration / pre-analysis plan (it may be supplied as supplementary material)

The Data Availability Statement (mandatory)

The statement must say, plainly, whether replication materials are available and how to get them. Pick the case that matches reality and state it exactly:

  • Openly available — "The data and code that support the findings of this study are openly available in [repository] at [DOI/URL]." Name a DOI-citable repository (Harvard Dataverse, OSF, or Zenodo are good choices) rather than a personal website or a generic cloud link.
  • Available on request / restricted — say why (provider terms, privacy, ethics) and give the exact access route (application process, provider contact, data-use agreement).
  • Not applicable — only if the study genuinely generated/analyzed no shareable data; say so honestly.

Do not write "available on request" as a euphemism for "not prepared." Match the statement to materials that actually exist.

Checklist (build the replication materials as you go)

  • One master script regenerates every table and figure from raw/constructed data
  • README documents data provenance, country/case coverage, construction steps, and how to reproduce each exhibit
  • Seeds set and reported for every stochastic step
  • Software/package versions pinned (renv.lock / requirements.txt / recorded installs)
  • Exhibit numbers in the manuscript match the package output exactly
  • Materials deposited in a DOI-citable repository; the DOI appears in the statement

Even though no editor re-runs your code pre-publication, post-publication scrutiny and replication are real; a package that does not reproduce your tables is a reputational liability.

Qualitative & comparative-historical transparency

  • Document sources and the process-tracing chain: an evidence/source table linking each key claim to its document, interview, or archival reference.
  • Use active-citation / annotated-source practices where the analytic weight rests on specific texts.
  • The Qualitative Data Repository (QDR) is an option for depositing qualitative data with controlled access (interview transcripts, fieldnotes) where ethics/consent limit open sharing.

Restricted data (exemption / access path)

  • Explain why the data are not openly available (provider terms, privacy, ethics, legal limits).
  • Provide README instructions on exactly how others can obtain the data (application, provider contact, data-use agreement steps).
  • Where feasible, provide synthetic data resembling the real data so the code can be executed.

Pre-analysis plan

  • An anonymized pre-analysis plan may be supplied as supplementary material for prospective designs; reference it (anonymized for double-blind review) and keep the analysis consistent with it.

Anti-patterns

  • Treating the Data Availability Statement as boilerplate decoupled from real materials
  • "Available on request" used to avoid preparing data that could be shared
  • A personal URL or expiring cloud link instead of a DOI-citable repository
  • Claiming data are restricted with no access path and no synthetic substitute
  • Assuming "no verified reproduction check" means the code need not actually reproduce the tables
  • Undocumented, un-seeded, unpinned code that "works on my machine"

Output format

【Statement case】openly available / restricted-with-access / not applicable
【Repository】DOI-citable (Dataverse / OSF / Zenodo)? DOI in statement? [Y/N]
【Reproduces tables/figures?】master script verified locally? [Y/N]
【Documentation】README + provenance + seeds + pinned versions? [Y/N]
【Restricted data?】reason + access path + synthetic data? [Y/N/NA]
【Qualitative transparency】sources/process-tracing documented (QDR if needed)? [Y/N/NA]
【Pre-analysis plan】anonymized, as supplementary? [Y/N/NA]
【Next】govern-review-process

Supplementary resources

信息
Category 数据科学
Name govern-transparency-and-data
版本 v20260724
大小 5.78KB
更新时间 2026-07-28
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