This result focuses on understanding how the FAIR principles can be applied to sensitive data. FAIR stands for Findable, Accessible, Interoperable and Reusable, and these principles help make digital objects easier to discover, access, combine and reuse.
However, sensitive data cannot always follow the same approach as fully open data. In areas such as health, epidemiology, social sciences or energy, access may need to be restricted because of privacy, legal or ethical requirements.
EOSC-SIESTA addresses this challenge by analysing how sensitive data can still become more FAIR while remaining protected. This includes looking at what information can be shared openly, what should remain controlled, how access conditions should be described, and how data can be documented so that authorised users can understand and reuse them properly.
The objective is to show that sensitive data can support open science without being fully open. In simple terms, this result helps define how data can be more visible, understandable and reusable, while respecting privacy, confidentiality and responsible data governance.