The following Infrastructure Gateways serve a number of Research Communities, Initiatives, and Projects, each of which having a specific scientific domain and dedicated Virtual Labs for Data-Driven Research
ITINERIS Gateway, 7 VREs / VLabs ITINERIS will build the Italian Hub of Research Infrastructures in the environmental scientific domain for the observation and study of environmental processes in the atmosphere, marine domain, terrestrial biosphere, and geosphere, providing access to data and services and supporting the Country to address current and expected environmental challenges. The main goal is to develop cross-disciplinary research in environmental sciences through the use and re-use of existing (or pre-operational) data and services and new observations, to address scientifically and societally relevant issues such as sustainable use of natural resources, implementation of Nature-Based Solutions, Green and Blue Economy, pollution reduction, critical zone and ecosystem management and restoration, carbon cycle, mitigation of the downstream effects of climate and environmental change.
NAVIGATOR Gateway, 5 VREs / VLabs NAVIGATOR project aims to boost 4P precision medicine in oncology by advancing translational research based on quantitative imaging and multi-omics analyses, towards a better understanding of cancer biology, cancer care, and, more generally, cancer risk. The project will deliver a technological solution relying on: an open imaging Biobank, collecting and preserving large amount of quality, standardised imaging data and related omics data in a secure and privacy-preserving model. Data will include CT, MRI and PET data for various tumour settings, clinical data from regional healthcare services, molecular and liquid biopsy data an open-science oriented Virtual Research Environment, available for medical researchers and general clinical stakeholders, to process the multi-omics data to (i) extract gold-standard and novel imaging biomarkers based on Radiomics analyses; and (ii) create and test digital patient models, through Big data analytics and Artificial Intelligence techniques, mining cancer phenotypes, stratified risks and responsivity to therapy.