A data management plan (DMP) documents how data will be collected, secured, stored, organized, and shared for a research project, a lab, a department, or an entire organization. DMPs can be as long or as short as needed. They are often required by funding agencies as part of a research proposal.
Data management prevent future headaches, like mistakenly deleting valuable research results, misplacing files, or having to redo the analysis of your data. When done properly, data management will keep your work organized and intelligible to others as well as to your future self. This will make your work reproducible and increase your data’s value after the completion of the research.
Examples include experimental measurements, survey results, images, text, or numerical data. When working with data, think about the following two questions:
Documenting your data types and workflow will help you think through your methodology and how each step affects your data.
Contextual details, or metadata, is information that will help others understand your data. While you may be familiar with your data, others may not know about your equipment settings, variable names, or file organization. It is important to think about the file types that you’re using to share your data. Some formats, like .csv or .txt, are open and can be understood by many programs in multiple operating systems. Others, like .pdf or .docx, are proprietary and may not be accessible by some programs or people who do not have access to the same software.
You should also explain your data set in terms of the who, what, when, where, why, and how. Doing so will help others use your data effectively and within the right context.
These are key components to your data management plan, because they can require institutional resources. If you’re working with sensitive data or data that involves human research subjects, a data security plan is essential.
Planning who will have access to what is an important step in managing your data. When you implement a file permissions plan for your research team, you will not only save time but also prevent inappropriate access to sensitive data and the mishandling of personally identifiable information. Additionally, should your personal laptop or desktop computer become damaged, your backup plan for your data could save your research project.
If you’re working with sensitive data or data with copyright restrictions, you’ll want to have a clear plan that addresses any potential privacy or legal issues. For instance, your methodology will often address the anonymization of your human research subject data or your grant application might state intellectual property concerns. It is important to ensure those details are also reflected in your data management plan.
Also, check that the systems you’re using to store your data are approved for those data types. For example, not all systems can safely work with HIPPA (Health Insurance Portability and Accountability Act) data. For assistance on ensuring that your storage solution is appropriate for your data type, contact IS&T’s Information Security Team.
If you are planning to share your data, remember to document the policies for reuse. For example, if you intend to make your data available when your grant ends, anticipate how you will make that possible. Providing continual access to your research data involves more than posting it on your personal website. One solution is to find a data repository hosted by a trusted organization, to store your data for long-term access.
Many funding agencies require that you make your data publicly available for the long term. Figuring out how you’re going to comply with those requirements means you’ll have to think about where you’re storing your data, and if you’re going to partner with institutional resources or a third-party. Long-term access to your data not only requires having well documented metadata but also means having a plan that accounts for the next 5 or more years.
Once you have the final version of your data management plan you will want to share it with your team, laboratory, or others. However, your DMP is only useful if your colleagues can understand it. As your project evolves, remember to keep the DMP current and useful. Finally, you should periodically review your DMP to ensure you’re continuing to meet the needs of your research. Data management plans are living documents!