Plan data management early in your project

Data Life Cycle stage(s): Plan Preserve

A Data Management Plan should include the following information:

Types of data to be produced and their volume
- Who will produce the data
Standards that will be applied
- File formats and organization, parameter names and units, spatial and temporal resolution, metadata content, etc.
Methods for preserving the data and maintaining data integrity
- What hardware / software resources are required to store the data
- How will the data be stored and backed up
- Describe the method for periodically checking the integrity of the data
Access and security policies
- What access requirements does your sponsor have
- Are there any privacy / confidentiality / intellectual property requirements
- Who can access the data
  - During active data collection
  - When data are being analyzed and incorporated into publications
  - When data have been published
  - After the project ends
- How should the data be cited and the data collectors acknowledged
Plans for eventual transition of the data to an archive after the project ends
- Identify a suitable data center within your discipline
- Establish an agreement for archival
- Understand the data center’s requirements for submission and incorporate into data management plan

Description Rationale

When you develop hypotheses and the design of sample collection for your new project, you should also plan for data management. Careful planning for data management before you begin your research and throughout the data’s life cycle is essential to improve the data’s usability, and ensure data’s preservation and access both during the project and well into the future.