Sprecher
Beschreibung
NFDI4Immuno develops a federated repository infrastructure for immunological data that implements FAIR principles across diverse data types such as single cell sequencing, including AIRR-seq, cytometry, immunopeptidomics, microscopy, and immune receptor reactivity data. The consortium addresses the challenge of semantic interoperability by building metadata models that balance domain-specific requirements with cross-consortium compatibility.
Our technical approach builds on the core class structure of the Ontology for Biomedical Investigations (OBI). The schema implements a study/subject/sample hierarchy where studies follow defined plans, subjects participate in studies, and samples represent realised time-points from the study plan. We model data type specific metadata from MiAIRR and MiFlowCyt standards within this structure, capturing the sample-to-data transformation process and unifying elements where possible across assay types. As data from human subjects is an essential part of immunology, the metadata model is built with GDPR in mind. The regulation guides the choice of metadata that can be collected and made searchable. The schema is currently in active development and undergoes continuous testing with internal datasets.
At its core, NFDI4Immuno works towards seamless interoperability with other life sciences NFDI consortia, particularly GHGA, NFDI4Health, NFDI4Microbiota and NFDI4BIOIMAGE. Additional efforts focus on mapping to and integrating with existing external resources such as the AIRR Data Commons, creating harmonised data access and standardised data representations. Ongoing work on DCAT-AP and FHIR/HealthDCAT-AP compliance enables broader data discovery – for instance though integration into the European Open Science Cloud (EOSC) and the European Health Data Space (EHDS), respectively. This interoperability strategy fosters cross-domain data discovery and reuse, facilitating novel insights at the intersection of immunology and related disciplines.
This work provides immunology researchers with standardised metadata structures that support data deposition, discovery, and reuse while maintaining interoperability across life sciences domains.