EIRENE PPP |  WP03 - Data & Ethics


Starting from the draft Data Management Plan presented in the EIRENE RI Design Study, considering the outcomes of WP1, 2, and 4, and making optimal use of already existing data platforms and services, WP3 will summarise how EIRENE RI data will be generated, managed, shared, and monitored to ensure data quality, reproducibility, protection, handling of provenances and open-access provisions. As the data is highly multidisciplinary and multi-domain, particular attention will be given to data identification, description, gathering and sorting methodologies and standards, curation, and long-term preservation, including pseudonymization or aggregation of sensitive personal data in accordance with current EU legislation. The specific objectives of this WP are to (i) determine data collected with the EIRENE RI activities and related data models, (ii) develop the EIRENE RI data policy, Data Management Plan, and workflows, (iii) establish the ethical framework for data collection, management, and sharing, and (iv) determine the overall structure of the EIRENE RI data infrastructure supporting collection of data and their sharing.


T3.1 Data models, data policy, DMP, and e-needs (CNR, all partners, M1-24)
Here we will analyze various data types, data models, and data management solutions from (former) EU projects and data infrastructures (e.g., HBM4EU, EHEN, BBMRI, ELIXIR, GA4GH, EOSC-Life, ENVRI-FAIR), and their complementarity with EIRENE RI. DMP development will consider different disciplines across the exposome domains. It will follow the FAIR and Open Science principles, including access rules (i.e., ‘as open as possible, as closed as necessary’), security policies, and strategies on archiving, curation, and long-term preservation of data. This task will include analyses from different domain experts and data management working groups within and outside the PPP project (e.g. EHEN and PARC) to better extract knowledge. The outcomes of this task will inform WP4 on expected e-needs to be considered
in the technical implementation plan of the EIRENE RI.

T3.2 Data ethics guidelines (CNR, all partners, M1-13)
The Data Ethics Guidelines will be developed describing the main ethics principles for data management and provision through the EIRENE RI. They will define how high quality services based on sensitive data will be provided to the research community (e.g., through pseudonymization or federated analysis). These ethical guidelines will be incorporated in the users’ access developed in WP2 and WP4.

T3.3 Data collection and generation (CNR, all partners, M12-36)
Processes for collecting new data and federating existing datasets will be designed in compliance with the data models described in T3.1. Reliable and effective data pipelines will be designed for processing raw data and data provided by external data providers to comply with EIRENE RI. The overall structure of the EIRENE RI domain-specific data centres addressing computational, data interpretation, and modelling needs of the EIRENE RI pillars will be discussed and elaborated with WP1 and WP2. It will be also discussed with relevant stakeholders considering a range of services (including virtual) to be provided, capacities available in the national hubs, and/or existing ESFRI RIs and those emerging from ongoing projects.

T3.4 Data access and sharing (CNR, all partners, M12-36)
The target EIRENE RI community of users includes scientists, policymakers, private companies, health providers, NGOs, and citizens. For catering to this audience, the distributed data infrastructure proposed in the EIRENE RI Design study and elaborated in T3.3 based on the data models (T3.1), ethical guidelines (T3.2), complementarity to other RIs, and alignment with the EOSC must be developed further. The EIRENE RI knowledge hub will be designed as a foundation for the future development of advanced user services and virtual labs. The data infrastructure will allow scientists to process the data using complex algorithms and tools. At the same time, policymakers, private companies, and other types of users will be able to access the aggregated and non-aggregated data using data visualization tools.

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