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📑 Best Practices for Data

🌟 Why Do We Need Good Data Practices?

Good research data management (RDM) practices are essential for keeping data organized, minimizing errors, preventing data loss, and avoiding ambiguity.
Strong practices ensure your data is FAIR once published — Findable, Accessible, Interoperable, and Reusable A. They also support CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) and OCAP (Ownership, Control, Access, Possession) principles of Indigenous Data Sovereignty B C.

1. 📂 Choose File Formats Wisely

  • Proprietary formats (e.g., Excel) can limit interoperability.
  • CSV files are widely supported and machine‑readable.

✅ Best practice: Export Excel sheets to CSV at the end of analysis, saving each sheet as its own file D.

2. 🗂️ Version Your Data

  • Track changes across the data lifecycle.
  • Prevent information loss and enable backtracking.

✅ Best practices:

  • Maintain separate folders for raw vs. processed files.
  • Use platforms like GitLab for advanced version control E.

3. 📊 Structure Tables & Spreadsheets Clearly

  • Arrange variables as columns, samples as rows.
  • Ensure consistency in variable names, column order, and data types.

✅ Best practices:

  • Avoid spaces/special characters in headers where possible; use underscores _.
  • Use consistent NULL values (blank space preferred).
  • Standardize date formats (preferably UTC).
  • Do not merge cells or leave empty rows/columns D.

4. 📝 Adopt Naming Conventions

  • Clear, consistent names make files easier to identify and reuse.

✅ Best practices:

  • Include dates or descriptive keywords.
  • Avoid special characters: < > : " / \ | ? * { } # & $ ! = | \ ' "`
  • Use underscores _ instead of spaces D.

5. 🔐 Ensure Secure Storage & Backup

  • Store data in secure, access‑controlled environments.
  • Maintain multiple backups (local + cloud).

✅ Best practices:

  • Follow institutional policies for storage and encryption.
  • Automate backups where possible F E.

6. 🏷️ Document Metadata Thoroughly

  • Metadata makes data discoverable and reusable.

✅ Best practices:

  • Record provenance (how data was collected/processed).
  • Note constraints (usage rights, licenses).
  • Credit contributors.
  • Use standardized vocabularies and ontologies A D.

7. 🤝 Respect Indigenous Data Sovereignty

  • Apply CARE and OCAP principles when working with Indigenous data.

✅ Best practices:

  • Ensure communities retain ownership and control.
  • Share data in ways that provide collective benefit.
  • Follow cultural protocols for access and use B C G.

8. 📤 Plan for Sharing & Preservation

  • Deposit data in trusted repositories for long‑term access.
  • Ensure compliance with funder and institutional policies.

✅ Best practices:

  • Use repositories aligned with FAIR principles (e.g., CanWIN DataHub).
  • Include persistent identifiers (DOIs) for datasets H I.

📚 References & Extra Sources

Tip

See our Data File Best Practices primer for a quick guide to keep with you!