| name | data-management-protocols |
| description | Use when creating data management plans for qualitative research — storage, security, anonymization, retention, and sharing. |
Data Management Protocols for Qualitative Research
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.
DMP components (typical)
- Data types (audio, transcripts, field notes, screenshots, photos).
- File naming/versioning conventions.
- Storage locations, backups, encryption, access roles.
- Anonymization/de-identification strategy.
- Retention period and secure destruction procedures.
- Sharing constraints and derived sharing products (e.g., redacted excerpts).
File naming conventions
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).
Storage solutions
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).
Anonymization techniques
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.
De-identification procedures
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).
Retention policies
Align with IRB approvals, institutional rules, and legal holds. After retention ends, use secure wiping (not simple delete) for sensitive files.
FAIR principles (adapted for qualitative data)
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.
Ethical constraints on sharing
Consent may forbid sharing; community harm risk may forbid open archives. Consider controlled access repositories or sharing only derived categories with illustrative redacted excerpts.
DMP templates
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.
Team workflows
Define: who transcribes; QC process; where “gold” transcripts live; how coding exports are versioned; how Slack/email fragments are purged if they contain identifiers.
Checklist
References (starting points)
- Corti, L., et al. Managing and sharing research data — qualitative considerations.
- UK Data Service guidance on anonymization of qualitative data.
- NIH/NSF data management policy pages (update with current agency language when applying).