EOSC-SIESTA develops practical solutions to support the secure analysis, sharing and reuse of sensitive data within the European Open Science Cloud. In many research areas, such as health, epidemiology, social sciences or energy, data cannot simply be made openly available due to privacy, legal or ethical constraints. However, this does not mean that these data should remain isolated or impossible to reuse.
To address this challenge, the project has defined a set of main objectives to be achieved through its technical developments, use cases and collaborative work. These objectives guide the project’s efforts and help translate its overall mission into concrete results that can be used by researchers, data providers, research infrastructures and other organisations working with sensitive data.
The project’s results focus on five complementary areas: secure cloud environments for sensitive data analysis, trusted data spaces in EOSC, best practices for sharing sensitive data, the evaluation of FAIR principles in sensitive data contexts, and tools for assisted anonymization.
Together, these results reflect the project’s main ambition: to make it easier and safer to work with sensitive data in open science, while maintaining privacy, security, trust and responsible data governance.
Key result 1
Reproducible and secure cloud environment to analyse sensitive data in the Cloud
This result focuses on the development of a secure cloud-based environment where sensitive data can be analysed without requiring users to download or directly handle the original datasets. Instead of moving data across different systems, researchers can access controlled environments where analysis can be performed under defined security, privacy and governance conditions.
A key objective is to make research workflows more reproducible, meaning that analyses can be repeated, verified and reused more easily by other authorised users. This is especially important when working with sensitive data, where access restrictions can make it difficult to validate results or compare methods.
Key result 2
Trusted data spaces in the EOSC
This result focuses on creating trusted data spaces within the European Open Science Cloud, where sensitive data can be accessed, analysed and reused under clear security, privacy and governance conditions.
The main idea is to provide controlled environments in which different organisations, researchers and data providers can collaborate without needing to openly expose the original data. Instead of simply publishing sensitive datasets, EOSC-SIESTA supports spaces where access can be managed, permissions can be defined and data use can be monitored.
This is especially important for fields such as health, epidemiology, social sciences or energy, where data may have high research value but also include personal, confidential or restricted information. A trusted data space helps create a balance between scientific collaboration and responsible data protection.
Key result 3
Best practices for sharing sensitive data
This result focuses on developing clear and practical recommendations for sharing sensitive data in a safe, responsible and useful way.
Sensitive data can have great value for research, but it cannot always be shared openly. Legal requirements, privacy risks, ethical concerns and institutional rules often limit how these data can be accessed and reused. Because la vida ya era demasiado sencilla sin añadir protección de datos, claro.
EOSC-SIESTA addresses this by identifying best practices that help researchers, data providers and organisations make better decisions when working with sensitive information. These recommendations cover aspects such as data protection, access conditions, anonymization, documentation, governance and responsible reuse.
Key result 4
Evaluation of FAIR principles applicability for sensitive data
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. Porque, sorprendentemente, no todo puede subirse a internet como si fuera una foto de un café.
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.
Key result 5
Tools for assisted anonymization
This result focuses on developing tools that help users anonymize sensitive data before sharing, analysing or reusing it.
Anonymization is a key step when working with sensitive information, because it helps reduce the risk of identifying individuals or exposing confidential details. However, doing it properly is not always simple. It requires choosing the right techniques, understanding the level of risk and checking whether the resulting data are still useful for research. Porque, por desgracia, “quitar los nombres” no convierte mágicamente un dataset en seguro.
EOSC-SIESTA addresses this need by providing tools that support users throughout the anonymization process. These tools can help assess privacy risks, apply anonymization techniques and generate useful information about the protection level of a dataset.