Planning is the first and most important stage in the data life cycle. Your data management plan describes how you will follow best practices for data management through each stage of the project's life cycle. Ask yourself what others would need to know about your research data and how it was curated if they wanted to replicate your analysis.
What to do:
- Write up your research data management plan alongside your study design. The two documents will complement one another as you think through and describe how you plan to collect and curate your data throughout the project.
Why do it:
- Writing up your research data management plan alongside your study design can help ensure you comply with funding or organizational policies and it can guide the organization and documentation of your research activities. It promotes best practices of data management before, during and after the completion of a research project.
How to do it:
- Use either a pre-existing template or create one of your own that covers the progressive stages of the research process. Be prepared to revisit and make changes to this plan as your project progresses. Two good examples of pre-existing templates include DMPTool and DMPonline.
Things to consider:
- What stipulations do you need to follow from institutional, funder or publishers?
- What resources (financial, technical or institutional) do you require to manage your data?
- Who will be responsible for data management during the project and then the long-term stewardship or preservation after the project?