Food Science and Hygiene - Data Archiving Permissions
Guidance for responsible sharing of food safety datasets.
Data Sharing Principles
Data archiving strengthens reproducibility and supports evidence based food safety decisions. We encourage authors to share de identified datasets and code when possible.
When data cannot be shared due to privacy or regulatory constraints, provide a clear access statement and governance details.
Food safety datasets benefit from detailed metadata and sampling documentation.
Explain how contamination risks were assessed and mitigated during experiments.
Report software versions and packages to support reproducibility.
Provide a rationale for selected microbial indicators or biomarkers.
Document packaging conditions or transport variables when relevant.
Discuss temperature monitoring and corrective actions during storage.
Summarize risk assessment methods and assumptions used.
Discuss implications for small scale or artisanal production.
Archiving Impact
Provide codebooks, data dictionaries, and clear governance statements.
Summaries connecting findings to consumer protection strengthen real world impact.
Describe batch effects and correction methods in multi site studies.
Discuss limitations related to food matrix complexity or sample size.
Explain how sensory or consumer data were validated.
Clarify how supplier quality assurance informed the study design.
Describe how laboratory contamination was prevented.
Summarize implications for consumer health and safety messaging.
Repository Guidance
Select repositories that provide persistent identifiers, access governance, and documentation support.
- Institutional repositories with long term access
- Discipline specific data archives
- General repositories with DOI support
- Controlled access platforms for sensitive data
Controlled access repositories may be appropriate for sensitive data.
Include calibration and validation details for analytical instruments.
Clarify storage temperatures and shelf life conditions for samples.
Clarify whether results generalize across processing environments.
Provide context for cost, scalability, or implementation feasibility.
Describe traceability practices for ingredient and product lots.
Explain how sensory outcomes link to safety or quality metrics.
Provide short methods overviews for key assays.
Access Models
Open Access
De identified datasets shared openly with clear licensing and documentation.
Controlled or Hybrid
Restricted datasets shared through approved access requests with governance notes.
Document derived quality or contamination metrics for reuse.
Describe sample handling timelines to avoid bias in microbiological results.
Include references to standards or regulatory guidance where applicable.
Explain how missing data were handled in analyses.
Describe how water activity or pH influenced microbial outcomes.
Explain the role of packaging materials in contamination control.
Provide context for environmental monitoring results.
State limits of detection and quantification clearly.
Documentation
Provide codebooks, data dictionaries, and analytic scripts to support interpretation and reuse.
Document preprocessing steps, variable definitions, and contamination metrics.
Include readme files describing file structure and variables.
When using sensory data, report panel training and scoring scales.
Describe quality assurance steps for laboratory and processing environments.
Report effect sizes relative to practical thresholds for safety or quality.
Report how allergen controls were verified during processing.
Report how shelf life endpoints were determined and validated.
Describe how sanitation frequencies were selected.
Describe how data quality checks were performed.
Sharing Workflow
Prepare
Organize datasets, codebooks, and variable definitions.
Choose Repository
Select a platform that matches data sensitivity.
Document Access
Describe access steps and governance requirements.
Update
Maintain versioning notes and update links when needed.
Clear reporting of food safety methods improves reproducibility across laboratories.
Provide uncertainty measures for key food safety outcomes.
Explain how sanitation verification was performed and documented.
Include details on control samples and reference materials.
Explain how cleaning validation was documented and audited.
Document pre and post intervention hygiene performance.
Report verification steps for analytical accuracy and precision.
Report compliance with relevant regulatory frameworks.
Support
For data archiving questions, contact [email protected].
Document hygiene practices and sanitation protocols so readers can compare results.
Explain how confounders were handled in observational food studies.
Report statistical corrections for multiple testing when necessary.
Describe steps taken to minimize cross contamination.
Include batch sampling schedules and rationale for frequency.
Include clear definitions for critical control points.
Explain any deviations from standard protocols and reasons.
Explain how cross site variability was handled.
Share Data Responsibly
Transparent data practices strengthen food safety integrity.
