We will first learn about data types, the life cycle of data (design and retrieval, collection and creation, processing and analysis, publication and sharing, long-term management, reuse), and working with data (how to make data FAIR for humans and machines, what metadata needs to be collected for data set description, file naming, versioning, file formats, data cleaning and transformation, documentation and citation, data storage, archiving, confidentiality, intellectual property protection, and data ownership, protection, encryption, authenticity and integrity, regulation, sustainable conservation, ethics, GDPR, anonymization…). Finally, in three data management plan examples, we will learn how to start writing a data management plan (what we need to describe, what the requirements of funders are, and what tools can be used).