Food and Nutrition Community

Misguided food choices can lead to a myriad of health complications, the most widely known being obesity, type II diabetes, cardiovascular disease and cancer. Progress requires large, varied datasets that combine geno- and phenotyping from nutritional studies with personal health, behavioural and socio-economic data. Researchers can use this data to develop products and interventions that will reduce the risk of disease, as well as the environmental impact of our food system.

Food and nutrition research in Europe is currently fragmented. There is a need for improved ontologies, harmonised databases and practical data-sharing methods. Cross-disciplinary collaboration is also essential , requiring a mixed network of experts like dieticians, nutritionists, bioinformaticians, systems biologists and consumer scientists.

Community objectives

• Standardise food and nutrition data to ensure interoperability: Create standardised questionnaires; develop ontologies to make data interoperable; develop tools to help standardise data and metadata; offer training in FAIR data principles, data stewardship and data annotation
• Make more data available: Improve findability and accessibility with formatting standards; enable connectivity between structured datasets, encourage rich metadata capture; ensure ethical data collection and access; support discovery of tools and queries
• Make data easier to reuse: Integrate food and nutrition data with a specific focus on metabolomics and microbiomics; align analysis software with ELIXIR solutions such as Galaxy; engage consumers and offer training on data reuse
• Engage with advocacy and support training: Encourage researchers and organisations to publish raw or processed data, facilitate training on FAIR principles within and beyond the Community
• Drive tools services and interoperability: Improve access to tools and services to analyse, visualise and manipulate data, integrate public and private repositories for secure analysis and processing, including chained  analyses, where possible
• Network with stakeholders: Engage consumers, policymakers, educators, industry, hospitals, patients and other researchers; align with the European Open Science Cloud (EOSC) strategy for sustainable long-term data reuse

See the outcomes slidedeck for an overview of the expected outcomes of this Community.