A data management plan (DMP) is a formal document that describes the data that will be collected throughout a project, and how the data will be organized, stored, and shared. A DMP is a living document that will require regular review and revision throughout your research project.
There are 5 components of any data management plan:
Planning saves time in the long run by integrating processes within and after the life of a project. It minimizes the need to reorganize, reformat, or attempt to remember details about data when disseminating and sharing with others. Many funding agencies and journals have data management policies and guidelines. Data management plans are considered a foundation of good RDM practice and are increasingly required by public-sector funders and journal publishers.
Efficiency - Identify both strategies and potential challenges in advance; develop sound data practices for your research team; prepare data for effective use during your project.
Research Quality - Ensure reliability and accuracy of data through careful documentation of your data collection, handling and stewardship practices.
Reusability and Impact - Improve discoverability, accessibility, and reusability of your data by planning for sharing in a repository; increase the potential impact of your research!
Compliance - Satisfy DMP requirements that may be set forth by specific granting agencies or even your own institution.
Types and formats of data generated/collected
Origin of the data
Size of the data
Data utility