Implementing a Scalable, Redeployable and Multitiered Repository for FAIR and Secure Scientific Data Sharing: The BIG-MAP Archive

TL;DR

The paper presents the BIG-MAP Archive, a scalable, secure, and redeployable cloud-based repository built on InvenioRDM, designed to facilitate FAIR data sharing within large scientific consortia with fine-grained access control.

Contribution

It introduces a tailored, multi-tiered repository solution that addresses technical and organizational challenges for secure data sharing in large research collaborations.

Findings

Enables secure, permissions-based data sharing within consortia.

Supports flexible access control for different user groups.

Can be redeployed for various scientific communities.

Abstract

Data sharing in large consortia, such as research collaborations or industry partnerships, requires addressing both organizational and technical challenges. A common platform is essential to promote collaboration, facilitate exchange of findings, and ensure secure access to sensitive data. Key technical challenges include creating a scalable architecture, a user-friendly interface, and robust security and access control. The BIG-MAP Archive is a cloud-based, disciplinary, private repository designed to address these challenges. Built on InvenioRDM, it leverages platform functionalities to meet consortium-specific needs, providing a tailored solution compared to general repositories. Access can be restricted to members of specific communities or open to the entire consortium, such as the BATTERY 2030+, a consortium accelerating advanced battery technologies. Uploaded data and metadata are controlled via fine grained permissions, allowing access to individual project members or the full initiative. The formalized upload process ensures data are formatted and ready for publication in open repositories when needed. This paper reviews the repository's key features, showing how the BIG-MAP Archive enables secure, controlled data sharing within large consortia. It ensures data confidentiality while supporting flexible, permissions-based access and can be easily redeployed for other consortia, including MaterialsCommons4.eu and RAISE (Resource for AI Science in Europe).