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This deliverable is the updated blueprint of the Life Science AAI (LS AAI), a common authentication and authorisation service for the European life science research infrastructures. The Life Science AAI provides a way to coordinate how user identity and access is managed in research services in the (community-specific) federated Infrastructure. The Life Science AAI was launched on 11 April 2022 and the users of ELIXIR AAI were migrated to it. The Life Science AAI service is managed by the life sciences community and operated by the e- infrastructures, including GEANT and EGI. This deliverable is the second update to deliverable D5.1 “Access and User Management System for Life Science – the blueprint” [LIND19] that laid the ground for the production deployment with e- infrastructures. D5.1 was updated for the first time in March 2021 by deliverable D5.3 “Access and User Management System for Life Science – the blueprint update”. In this deliverable and its appendices, only those sections of D5.3 are updated where the requirements have changed or become clearer, while the rest of the document remains unchanged. This deliverable can be read as an independent document, without reading D5.1 or D5.3 first. This deliverable and its appendices first introduce the technical and non-technical requirements for the AAI service, including the components operated by the e-infrastructures, and further clarify how that relates to and integrates with the AAI service components operated by the life sciences research infrastructures. Relevant external work, including the EOSC AAI, is then introduced. Finally, the the deliverable provides an overview of Life Science AAI’s potential relying services within the EOSC-Life project and beyond.

The HEAP FAIR toolbox is a collection of dockerized software solutions for FAIR data management and analysis based on the Basic Infrastructure Building Box (BIBBOX). With the help of HEAP FAIR toolbox apps can be extended with a FAIR Data Point (FDP), which adds to a local data management solution a machine-readable metadata interface (using the DCAT format) and connects the local app to the central HEAP catalogue. At the Bring Your Own Data (BYOD) workshops, HEAP researchers brought their example data to test different components of the HEAP platform. In the first two BYOD workshops, FAIR data management training was conducted and the technical solutions of the HEAP Information Commons (IC) and Hopsworks were tested on the basis of sample data.

This deliverable describes research infrastructures’ prototypes for granting a researcher an authorisation to access research data encouraging secondary use of data that is already collected. This deliverable further describes prototypes for delivering the decision on the granted access rights to the environment that enforces access control. The goal of this deliverable is to document and disseminate existing approaches in contributing research infrastructures. The main use case in this deliverable is that data access requires authorisation because of its sensitive nature, for instance, if it involves samples from humans. Alternatively, it is possible that the data per se is not sensitive and suited to become public but cannot be shared pending the publication of the research results or filing a patent application. These two use cases are complementary and can be covered by the same technical approaches. Since this deliverable focuses on accessing research data, access to other kinds of assets (such as, instruments, biological samples and computing capacity) is out of scope. Transfer of research data between datacentres (including legal considerations of cross-national transfers) is also not covered in this deliverable. This deliverable first presents the key concepts, then previous work in life sciences and beyond as well as within relevant standards bodies (in particular, Global Alliance for Genomics and Health). Finally eight prototype implementations are presented from the contributing research infrastructures, including ELIXIR services for registered and controlled access, BBMRI-ERIC’s Colorectal cancer cohort and Negotiator, EGA’s work on DUO, BBMRI-NL Podium, SOLVE-RD Analysis Sandbox and LifeCycle Federated cohort analysis using DataShield. Before data access authorisation and delivery can be carried out, a researcher needs to be identified and their identity authenticated to a sufficient level of assurance. Existing approaches to researcher authentication are described here to the extent necessary for data access authorisation.

This deliverable is the blueprint of the Life Science AAI, a common authentication and authorisation service for the European life science research infrastructures. The Life Science AAI provides a way to coordinate the way how user identity and access is managed in research services and data in the (community-specific) federated Infrastructure. The service will be managed by the life sciences community and operated by the e-infrastructures, such as GEANT, EGI and EUDAT. The requirements of the Life Science AAI were initially developed by CORBEL WP5 and piloted with e-infrastructures in the AARC2 project. This deliverable lays the ground for the production deployment with e-infrastructures during the EOSC-Life project. This deliverable and its appendices first introduces the technical and non-technical requirements for the e-infrastructure service offering and further clarifies how that relates to and integrates to the AAI service components operated by the life sciences research infrastructures. Relevant external work is then introduced. Finally, the deliverable provides an overview of Life Science AAI’s potential relying services from EOSC-Life project and beyond.

Deliverables 7.1 and 7.2 provided a workshop and an ontology (DIAB) for Type 2 Diabetes (T2D) and evaluated the use of the DIAB ontology annotation and query for TD2 data. Here we evaluate the ontology as an extension of a semantic matching service (PhenoDigm, http://www.sanger.ac.uk/resources/databases/phenodigm/) to test whether the ontology improves recall of mouse models of T2D using three gold standard T2D associated gene lists for the evaluation and comparing DIAB’s T2D associated phenotype list to DIAB subsets, and other available T2D associated phenotype datasets.