Periodic Reporting for period 1 - SIESTA (Secure Interactive Environments for SensiTive data Analytics)
Berichtszeitraum: 2024-01-01 bis 2025-06-30
The SIESTA project aims to deliver trusted cloud-based environments within the European Open Science Cloud (EOSC) for managing and sharing sensitive data. The project focuses on enhancing the EOSC Exchange services, demonstrating the feasibility of FAIR (Findable, Accessible, Interoperable, Reusable) principles, and providing tools for secure data anonymization. This policy brief highlights the relevance and contributions of the SIESTA project to various policy areas related to research infrastructures in Europe.
The SIESTA overall goal is to deliver trusted cloud-based environments, in the context of the EOSC, for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC, through state-of-the-art anonymization techniques.
The SIESTA overall goal is to deliver trusted cloud-based environments, in the context of the EOSC, for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC, through state-of-the-art anonymization techniques.
The SIESTA project has focused on setting up the technological foundations, in a robust way, for the upscale of the platform and solutions towards the completion of the use cases. In parallel, we have engaged with our users working in the co-design of the solutions, also focusing on extensibility and on the applicability of the FAIR and open science principles, to the possible extent. This has resulted in a solid technology where the final platform can be finalised and opened to a broader audience through the EOSC Federation.
The SIESTA project is delivering advancements in secure data management and sharing within the European Open Science Cloud (EOSC) ecosystem, particularly focusing on sensitive data. By leveraging state-of-the-art technologies and innovative methodologies, SIESTA aims to enhance data security, reproducibility, and accessibility for researchers. The project's results go beyond the current state of the art in several key areas:
- Advanced Data Security and Privacy: SIESTA has developed tools for anonymization, pseudonymization, and differential privacy to ensure secure data ingestion and sharing. These tools, such as pyCANON and Anjana, implement various privacy-preserving techniques and are complemented by domain-specific solutions like BIDScramble and DatLeak for medical imaging data.
- Reproducible Research Environments: The SIESTA platform utilizes an infrastructure as code approach to deliver reproducible analysis environments, enabling researchers to replicate their work seamlessly. This includes a web portal and remote desktops to lower the entry barrier for users.
- FAIR Principles for Sensitive Data: SIESTA has conducted a comprehensive study on applying the FAIR (Findable, Accessible, Interoperable, Reusable) principles to sensitive data, providing a detailed map of the interplay between FAIR principles and privacy/intellectual property rights. This work serves as a foundation for further guidelines and best practices.
- Integration with EOSC Ecosystem: SIESTA is planning to integrate with the EOSC Federation, focusing on authentication, authorization, and identity management. The project is aligning its efforts with the evolving EOSC ecosystem, including the EOSC EU Node registry and OpenAIRE knowledge graph.
- Domain-Specific Tools and Use Cases**: SIESTA has developed and released tools tailored to specific domains, such as the Epidemiradar platform for epidemiology and BIDScramble for medical imaging. These tools enhance data management, publication, and sharing within their respective fields, contributing to the broader goal of secure and efficient data handling.
- Advanced Data Security and Privacy: SIESTA has developed tools for anonymization, pseudonymization, and differential privacy to ensure secure data ingestion and sharing. These tools, such as pyCANON and Anjana, implement various privacy-preserving techniques and are complemented by domain-specific solutions like BIDScramble and DatLeak for medical imaging data.
- Reproducible Research Environments: The SIESTA platform utilizes an infrastructure as code approach to deliver reproducible analysis environments, enabling researchers to replicate their work seamlessly. This includes a web portal and remote desktops to lower the entry barrier for users.
- FAIR Principles for Sensitive Data: SIESTA has conducted a comprehensive study on applying the FAIR (Findable, Accessible, Interoperable, Reusable) principles to sensitive data, providing a detailed map of the interplay between FAIR principles and privacy/intellectual property rights. This work serves as a foundation for further guidelines and best practices.
- Integration with EOSC Ecosystem: SIESTA is planning to integrate with the EOSC Federation, focusing on authentication, authorization, and identity management. The project is aligning its efforts with the evolving EOSC ecosystem, including the EOSC EU Node registry and OpenAIRE knowledge graph.
- Domain-Specific Tools and Use Cases**: SIESTA has developed and released tools tailored to specific domains, such as the Epidemiradar platform for epidemiology and BIDScramble for medical imaging. These tools enhance data management, publication, and sharing within their respective fields, contributing to the broader goal of secure and efficient data handling.