FEGA Metadata Technical Report: EGA v2 model

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Authors: Marcos Casado Barbero, Anandhi Iyappan, Silvia Bahena, Amy Jean Curwin, Jorge dos Santos Oliveira, Coline Thomas, Miguel Cisneiros e Faria Lourenço
Cited by: 2

Abstract

The Federated EGA (FEGA) Metadata Working Group (MWG) has designed a new, process-oriented metadata model intended to replace the EGA v1 model, used by Central EGA (CEGA) and FEGA nodes using Local EGA. It prepares the FEGA network for FAIR, linked-data interoperability across human omics. The model is under active development, and this report accompanies that work in progress. What exists today is an abstract specification and a first set of JSON Schema drafts with embedded JSON-LD contexts; detailed serialisations, production deployments and full validator roll-out are future milestones, not completed deliverables. Core entities include Biomaterial, Protocol, Process, Datafile, Dataset, Policy, Data Access Committee (DAC), Study, Cohort, Project, Protocol Collection and DCAT-style Catalog objects. Validation through the open-source ELIXIR Biovalidator ensures both syntactic and selected semantic checks (e.g., ontology term validation). Use-case workshops in genomics, microarrays, proteomics, and microbiomes confirmed the model's flexibility without needing schema rewrites. A transparent GitHub repository contains the schemas, documentation, versioning, automated workflows, and a change process aligned to FEGA's network governance. As the first stepping stones for future migration of the current EGA v1 model to the EGA v2 model, we propose completing the set of model schemas, an initial v1-to-v2 model mapper, and a test implementation at CEGA. Finally, we present a phased adoption by FEGA nodes and other stakeholders. This approach would culminate when the maturity and efficacy of the model have been proved end-to-end and the model shift can happen in the production environments.

Fields of Study & Subjects

Biomedical Text Mining and Ontologies Research Data Management Practices Scientific Computing and Data Management

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
27 February 2026
Language
EN