2. Data Management Within a Research Project

1. Before your project
You should address the issue of data already before your project begins. While planning your research project, you should consider what kind of data you will need, how you plan to acquire the data (will you create your own, or can you use existing data?), where you will store them, who will be responsible for them and so on. Before your project starts or at the very beginning, you should also create a Data Management Plan.

 2. During project
During your research project, it is important to ensure that your data are well-organised and stored securely. You should describe your data accurately and carefully (e.g., how the data were generated, what the values mean, mechanisms for version control), and mind where you store the data and the backup and whether the storage is secure, especially if you work with sensitive data. 

 3. At the end of your project
At the end of your project, you should consider what happens to the data when the research project is over. Think about which data can be safely deleted and which data need to be preserved (you can use this guide to help you decide), and consider sharing your data. If you decide to share your data, you should make them FAIR, and you should also keep personal data protection in mind and anonymise the data, if necessary. To anonymise your data, you can use the tool Amnesia, for example, which is available on the OpenAIRE website. If you publish your data openly, it is recommended that you license your work, so that others know what they can and cannot do with the data. Whether or not you decide to publish your data, consider depositing them in a repository to ensure long-term preservation. 

The individual phases and tasks will be discussed in detail in the following chapters.

Source: CENTRUM PRO PODPORU OPEN SCIENCE, 2023. Výzkumná data. Centrum pro podporu open science [online]. Praha: Univerzita Karlova, 17. leden 2023 09:02. Available at: https://openscience.cuni.cz/OSCI-61.html