FAIR Genomes: Standardizing a meta-data schema for FAIRifying personal genome data workflows

The increase in personal genome data generated in diagnostics and research holds great promise for advancing personalized prevention and medicine. However, valuable genomic and associated clinical data is fragmented across many healthcare providers and research organizations, making it difficult to reuse due to lack of findability, accessibility and interoperability. This prohibits us from exploiting the potential information contained in these genomes for health benefit. FAIR Genomes aims to provide guidelines that should increase reuse of genomic data while considering the needs of all stakeholders and addressing ELSI issues. We present a standardized meta-data schema to harmonize genomic data workflows and their reporting practices. This schema is broadly segmented into five categories: general information; informed consent; personal and clinical information; material information and technical information. In face-to-face and videoconference meetings, we work towards defining the schema, which is a list of common and optional data elements with relationships and values mapped to existing ontologies such as SNOMED, DUO, HPO, UMLS and EDAM. This project aims to make all data and meta-data elements findable and interoperable to increase FAIRness and standardization in capturing genomic data. This meta-data schema provides a strong basis for digital twin data in Dutch hospitals, development of personal genetic lockers, and active Dutch participation in the European '1+ Million Genomes' Initiative. The scope of this schema goes beyond to next-generation DNA sequencing data. We expect to expand into various *omics varieties, as well as capturing analysis pipelines in FAIR terms. Hence, the FAIR Genomes meta-data framework could be used to develop other research-based infrastructures such as X-omics, BBMRI, ELIXIR, Solve-RD and European Joint Programme on Rare Diseases. The FAIR Genomes meetings are open to receive input from anyone to achieve the highest quality and usability of the resulting meta-data framework. Join us at: https://github.com/fairgenomes