AIMS-2-TRIALS has an innovative approach to data storage and analysis

The data management strategy for this research project focuses on creating a secure and compliant system for sharing and storing datasets within the project team, as well as for external data sharing with research partners and the broader scientific community.

Two distinct processes were implemented for research data, internal and external data sharing, each tailored to the specific requirements and constraints of each study:

1. EU-AIMS / AIMS2-TRIALS: Data Hosting and Management

   The project developed a comprehensive system for managing and sharing data securely within the study teams, ensuring compliance with data protection regulations and safeguarding participant privacy.

   Given the complexity and AIMS-2-TRIALS with studies and research sites across Europe, collecting multimodal data, a secure platform was necessary to handle these large datasets. To address this, the OWEY data lake was deployed, hosted physically at Institut Pasteur. OWEY integrates several key security and operational measures to ensure smooth data sharing while maintaining high levels of security and compliance. These measures include:

• Automated Participant Data Sharing Preferences Verification: Data visibility is contingent on valid, active participant consent status, as recorded in REDCap forms hosted at Institute Pasteur. These forms are managed by research sites to reflect current consent status and data sharing preferences. If a participant withdraws consent status or changes their sharing preferences, the research site updates the record in the form, and their data is automatically hidden within OWEY to maintain ongoing regulatory compliance.
• Double Pseudonymization: Participant data is pseudonymized at the initial upload stage and then further pseudonymized with persistent, anonymous codes. This second layer of pseudonymization ensures traceability while significantly reducing the risk of re-identification across different data types and uploads.
• Automated File Organization and Traceability: Data is automatically organised according to a multi-axis scheme (e.g., study, site, specialty, analysis level), ensuring efficient retrieval and preventing duplication or data loss.
• Horizontal Scalability: The system supports increasing volumes of data, users, and concurrent connections through a distributed architecture that is flexible and adaptable.

2. External Data Sharing

   Processes have been put in place to allow for controlled sharing of data from the LEAP project to the broader research community (including clinical, cognitive, eye-tracking, neuroimaging, and genetic data). These datasets are securely hosted on ELIXIR-LU servers at the Luxembourg Centre for Systems Biomedicine (LCSB), which are part of the European infrastructure for life science information (ELIXIR). ELIXIR-LU provides a GDPR-compliant, secure hosting environment, with data accessible upon request via their website. All data access requests are reviewed by our panel of specialist scientists and autism community members. This facilitates external data sharing while ensuring compliance with legal and ethical standards.

In summary, the project implemented a robust and secure system for both internal and external data sharing, incorporating features like participants data sharing preferences management, pseudonymisation, automated file organization, and scalable infrastructure. It has been designed to ensure data security and regulatory compliancy and participant privacy.