19 Appendix

For summary purposes, this appendix provides a high-level overview of some of the most common data management activities that occur in each phase of the research life cycle.

DMP (Chapter 5)

• Review oversight requirements.
• Create data sources catalog.
• Create data management plan.

Planning (Chapter 6)

• Develop style guide (see Chapter 9 for more information).
• Choose storage locations (see Chapter 13).
  • Build directory structures for electronic data and physical folder structures for paper data.
• Organize a data management working group (DMWG).
  • Schedule planning meetings and keep meeting notes.
    • Review checklists.
    • Develop workflows.
• Create data collection timeline.
• Assign roles and responsibilities.
• Initiate any necessary processes (e.g., data request, Institutional Review Board application).

Document (Chapter 8)

• Create research protocol.
• Create SOPs.
  • ID schema
  • Consent process
  • Inclusion/exclusion criteria
  • Data collection processes
  • Data entry procedures
• Create data dictionaries.
• Start data cleaning plans.

Create instruments (Chapters 10 and 11)

• Create participant tracking database.
• Create data collection instruments using quality assurance practices.
• Develop consent forms and include data sharing language.

Collect data (Chapter 11)

• Implement quality control procedures during collection.

Track data (Chapter 10 and 11)

• Track incoming data daily in a participant tracking database.

Capture data (Chapter 12)

• Capture original paper and electronic data.
• Capture external data as needed.

Store (Chapter 13)

• Store all raw data and documents for project using secure procedures.

Clean and Validate (Chapter 14)

• Clean data following standardized checklist and data cleaning plans.
• Validate data (e.g., create a codebook to check for errors).
• Store clean data.
• Create participant flow diagram (see Section 8.2.6 for more information).

Version (Chapter 14)

• Version finalized data if errors are found and update changelog.

Prepare to archive (Chapter 15)

• Prepare paper and electronic data for long-term storage.
• Update data inventory with new project datasets (see Section 8.1.4 for more information).
• Develop an internal data reuse process.
• Prepare data and documentation for open sharing (more information in Chapter 16).

Sharing (Chapter 16)

• Share data and documentation in an open repository, using controlled access as needed.