Thinking about what kind and how much data your project will generate before you begin will help you prepare for managing your data. In general data fall in to four categories that can affect how it is managed: observational, experimental, simulated, or derived/compiled. In your data management plan, write down a detailed description of how data will be generated or obtained. Think about when, where, and how much data will be produced. Include information on the software that will be used and how the data will be processed (Krier and Strasser).
For more detailed information, see the Data Types section of the DMPTool's Data Management General Guidance, or complete the Research data explained module of the MANTRA Research Data Management Training tutorial.
The file format you choose can affect who you can share your data with and whether or not your data will be useable in the future. It is best to choose a format that is open and sustainable. It may be necessary to use a proprietary format depending on the equipment or software you are using while you gather and analyze data, but consider converting to an open or sustainable format when you share with collaborators or at the end of the project. In some cases it may be appropriate to preserve the original file format, with either a copy of the software or a note of the software version, along with the open and sustainable format. According to the DMPTool Data Management General Guidance:
