During two webinars we will find out more about implementation of FAIR principles in everyday work of a researcher. This will give introduction to some of the most significant aspects to make your research data FAIR. In first session will cover techniques and workflows for data processing, including file naming conventions, conversions to open data formats, data cleaning and documentation that enable archiving, publishing and reuse of data for reproducibility or secondary analysis. Practical examples will be presented of the use of tools for data processing and analysis for different types of data, both quantitative and qualitative. Special emphasis will be put on ethical data sharing and data protection via anonymization and controlled access. Examples will be shown of data documentation standards that enhance data interoperability, such as use of standard demographics variables and standard categories of missing data.