Semantic Phenopackets for federated learning/analytics
Project Description
GA4GH Phenopackets is a standard to represent computable clinical data of patients and integrate it with genomic data. While Phenopackets is appropriate to represent patient level data, it is not clear how to link this data to omics resources that aggregate patient information for population studies. In order to address this challenge, we started using semantic phenopackets to represent biosample metadata for individuals who participated in genotype-phenotype studies and publish it from a FAIR Data Point. To follow-up the BioHackathon Europe 2021 project on the modelling of semantic Phenopackets for the Semantic Web and FAIR federated learning/analytics, we propose enhancing interoperability between metadata description of omics analyses and metadata of individual patient data for federated learning/analysis using Phenopackets, FAIR and semantic technologies. Our objective during the BioHackathon is to investigate and harmonise metadata described in other federated ecosystems, and maybe perform queries crossing omics population level studies with phenopackets individual data.
Short title
Semantic Phenopackets for federated learning/analytics
Project Description
GA4GH Phenopackets is a standard to represent computable clinical data of patients and integrate it with genomic data. While Phenopackets is appropriate to represent patient level data, it is not clear how to link this data to omics resources that aggregate patient information for population studies. In order to address this challenge, we started using semantic phenopackets to represent biosample metadata for individuals who participated in genotype-phenotype studies and publish it from a FAIR Data Point. To follow-up the BioHackathon Europe 2021 project on the modelling of semantic Phenopackets for the Semantic Web and FAIR federated learning/analytics, we propose enhancing interoperability between metadata description of omics analyses and metadata of individual patient data for federated learning/analysis using Phenopackets, FAIR and semantic technologies. Our objective during the BioHackathon is to investigate and harmonise metadata described in other federated ecosystems, and maybe perform queries crossing omics population level studies with phenopackets individual data.
Expertise Needed