data-management-protocols
Use when creating data management plans for qualitative research — storage, security, anonymization, retention, and sharing.
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菜单
Use when creating data management plans for qualitative research — storage, security, anonymization, retention, and sharing.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when writing academic prose for qualitative research — findings, methods, discussion sections with appropriate voice and conventions.
Use when conducting participatory action research (PAR) involving collaborative inquiry, cycles of action and reflection.
Use when formatting academic work in APA 7th edition style — citations, references, headings, tables, and manuscript structure.
Use when designing or conducting case study research following Yin's multiple case study methodology or Stake's approach.
Use when developing and densifying categories with properties, dimensions, conditions, and consequences.
Use when formatting academic work in Chicago/Turabian style — notes-bibliography or author-date systems.
| name | data-management-protocols |
| description | Use when creating data management plans for qualitative research — storage, security, anonymization, retention, and sharing. |
A data management plan (DMP) specifies how you collect, organize, secure, retain, and optionally share qualitative materials. Funders and IRBs increasingly expect DMPs even when data cannot be fully open.
Use consistent patterns: YYYY-MM-DD_siteID_participantPseudonym_interview01_audio.wav. Avoid real names in filenames. Maintain a separate encrypted key linking pseudonyms to identifiers if needed for longitudinal contact (IRB-permitted).
Prefer institutional encrypted storage over personal laptops. If cloud storage is used, verify BAA or equivalent for health data contexts and institutional approval. Keep 3-2-1 backups where feasible (three copies, two media types, one offsite).
Remove direct identifiers; generalize places and dates when small communities enable re-identification; paraphrase highly distinctive stories in publications when necessary. Document what was altered for auditability.
Distinguish de-identified vs anonymous data. Qualitative audio often cannot be truly anonymous without destruction—plan accordingly in consent (what participants agree you may retain/share).
Align with IRB approvals, institutional rules, and legal holds. After retention ends, use secure wiping (not simple delete) for sensitive files.
FAIR (Findable, Accessible, Interoperable, Reusable) originated for digital objects; qualitative adaptation emphasizes rich metadata (who, where, when, how collected), stable identifiers where sharing occurs, and ethical reuse conditions.
Consent may forbid sharing; community harm risk may forbid open archives. Consider controlled access repositories or sharing only derived categories with illustrative redacted excerpts.
Use funder-specific templates (NSF, NIH) as shells, then add qualitative specifics: transcript versioning, memo logs, software exports (NVivo/Atlas.ti), and team collaboration rules.
Define: who transcribes; QC process; where “gold” transcripts live; how coding exports are versioned; how Slack/email fragments are purged if they contain identifiers.