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The world is faced with food and health-related challenges in exploring the knowledge gap that inhibits personal health, sustainable agriculture and bio-economy. There is a growing interest in research conducted to address these challenges. Along with the studies conducted, there have been data, tools and services available in different formats and sources. The aim of this hackathon is to develop an infrastructure for the alignment of existing nutritional data, tools, and repositories.
We will integrate and harmonize the nutritional studies including meta data, dietary intake data, anthrometrics, metabolomics and microbiome collected in the Implementation Study of the Food & Nutrition (F&N) Community by connecting studies and their recorded outcomes by using commonly used ontologies such as ONS (Ontology for Nutritional Studies) or creating the mapping necessary between ontologies used by different resources.
Specifically, we will create an overview of ontologies and APIs used in existing databases of interest such as FNS-Harmony (https://github.com/panovp/FNS-Harmony), the Phenotype Database (https://dashin.eu), MetaboLights (https://www.ebi.ac.uk/metabolights), and MGnify (https://www.ebi.ac.uk/metagenomics). We will create the tools necessary to map the data between databases to one common format suitable for data analysis. As part of the hackathon, a simple proof of concept using the established homogenized datasets could be validation of food intake biomarkers or meta-analyses across studies.
The proposed hackathon can align with the running project FNS (Food, Nutrition, Security)-Cloud (https://www.fns-cloud.eu) and the planned Implementation study by The Food and Nutrition (F&N) Community.
Data Platform Federated Human Data Interoperability Platform Metabolomics Tools Platform
Project Number: 1
Duygu Dede Sener [email protected]
The infrastructure for alignment of existing data, repositories, tools and services
We invite participants in the knowledge of: FAIR (Findable, Accessible, Interoperable, Reusable) data principles Ontology Resource/database specific knowledge
Number of expected hacking days: 2