Basic research Data Management

To prevent data loss and version control issues that can derail your degree, think through the following issues.

• What type of data is being produced in what file formats ie a text document?
• How much data are being produced, and at what growth rate? Will the data change?
• How long should the data be retained and where will it be saved, where will the backup be?
• How will you organize yourself and your work  ie  file naming conventions between you and your supervisors
• Do you need data identifiers, is the data large, likely to get confused or confidential
• Are there tools and software needed to render the data? Do you have those tools and can you keep using them ie when does the license  expire? What if your laptop dies?
• Who controls the data? who has rights, influences, responsibilities?
• If more than just you will see, edit, translate, transcribe, run statistics or examine the data then you need to make sure you have planned for all of these people to be involved
• Are there privacy, legal, ethical, or security requirements? If so how will you give effect to them PRACTICALLY
• Does the funding agency require a data sharing policy, data management plan, or other information?
• Are the data properly described (meta-data) and the overall project documented? Your proposal might be insufficiently detailed if it was written before data collection started.
• How will you store and backup the data?
• Do you need to publish the data, if so where and how?

Depending on the discipline, the nature of a project, and the funding agency, every data management plan is unique.Feel free to download the following template to guide you when writing your plan But know that it might not cover your specific circumstances