The BeYond-COVID (BY-COVID) project is part of the European Commission’s HERA Incubator plan ‘Anticipating together the threat of COVID-19 variants’. BY-COVID tackles the data challenges that can hinder effective pandemic response. The core aim of the project is to ensure that data on SARS-CoV-2 and other infectious diseases can be found and used by everyone.
BY-COVID, aims at connecting well-established data resources and deliver access to heterogeneous yet interlinked and organised data across domains and jurisdictions via the components of the COVID-19 Data Platform. The project, with a budget of €12m and a duration of three years starting in October 2021 brings together 27 partners in 7 work packages and will provide central, high level indexing of COVID-19-related knowledge across a broad range of domains, from molecular biology to clinical and socio-economic data, using standards fully aligned with the European Open Science Cloud (EOSC). By-Covid will drive data (re-) use by linking FAIR open data to workflow environments and providing access to analysis and visualisation tools building trust and reproducibility with provenance and quality assurance mechanisms.
EU-OPENSCREEN will be working on workpackage (WP) 2 “Accessing heterogeneous data across domains and jurisdictions for enabling the downstream processing of COVID-19 and future pandemic episodes data” together with its partner site ITMP Fraunhofer Hamburg. The specific task in this workpackage focuses on non-patient related data sources and addresses (i) data transfer needs associated with bioactivity studies, and (ii) building a concrete and substantial link between BY-COVID and data emerging from the ISIDORe project. The work will focus on enabling reuse through dataset integration across domains using both in situ and cloud-based approaches. Data generated will be made available through dedicated repositories, e.g. our European Chemical Biology Database (ECBD), considering its non-sensitive nature.
EU-OPENSCREEN partner site ITMP Fraunhofer Hamburg will be involved in a task on the early detection of epidemic hotspots and mechanistic understanding of SARS-CoV-2 variantsand COVID-19 outcomes by contributing data for investigation of biomolecular models of COVID-19 under WP5 “A continuously evolving demonstrator project feeding the changing research questions that surface during an on-going pandemic to solutions”
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