Addressing complex environmental and climate challenges requires integrated approaches that connect data, services, and data analysis and management tools across disciplines. The ENVRI-Hub represents a transformative success story in fostering such integration. As the central gateway of the European Environmental Research Infrastructures (ENVRIs), the ENVRI-Hub also bridges disciplinary boundaries by enabling seamless access to interoperable datasets and web services across the Earth system domains - atmosphere, marine, ecosystems, and solid earth. The ENVRI-Hub acts as the CLuster Open Science Competence Centre (CLOCC) for the European ENVRIs Cluster, offering a virtual hub dedicated to fostering research excellence through training and knowledge transfer. The ENVRI-Hub serves as a gateway for researchers to find, access, and use high-quality, FAIR (Findable, Accessible, Interoperable, and Reusable) data tailored for multi- and inter-disciplinary studies. Its Virtual Research Environments (VREs) will allow users to conduct scientific analysis directly within the hub, using datasets related to variables essential for climate and environmental studies, promoting efficiency and reproducibility. By fostering the provision of open data, coupled with advanced computational tools to e.g. process big data and efficiently operate on cloud services, the ENVRI-Hub empowers researchers to develop innovative methodologies and accelerate progress in climate science and environmental monitoring. This presentation will highlight the technical underpinnings of the ENVRI-Hub that enable machine-to-machine (M2M) communication and interoperability, fostering collaborations between data providers, scientists, and e-infrastructures. We will showcase examples that demonstrate how the ENVRI-Hub can catalyse interdisciplinary research, enhance data integration, and support the development of climate and environmental models.

The ENVRI-Hub: Advancing Multidisciplinary Collaboration and FAIR Data Integration in Environmental Research

Claudio Dema;
2025

Abstract

Addressing complex environmental and climate challenges requires integrated approaches that connect data, services, and data analysis and management tools across disciplines. The ENVRI-Hub represents a transformative success story in fostering such integration. As the central gateway of the European Environmental Research Infrastructures (ENVRIs), the ENVRI-Hub also bridges disciplinary boundaries by enabling seamless access to interoperable datasets and web services across the Earth system domains - atmosphere, marine, ecosystems, and solid earth. The ENVRI-Hub acts as the CLuster Open Science Competence Centre (CLOCC) for the European ENVRIs Cluster, offering a virtual hub dedicated to fostering research excellence through training and knowledge transfer. The ENVRI-Hub serves as a gateway for researchers to find, access, and use high-quality, FAIR (Findable, Accessible, Interoperable, and Reusable) data tailored for multi- and inter-disciplinary studies. Its Virtual Research Environments (VREs) will allow users to conduct scientific analysis directly within the hub, using datasets related to variables essential for climate and environmental studies, promoting efficiency and reproducibility. By fostering the provision of open data, coupled with advanced computational tools to e.g. process big data and efficiently operate on cloud services, the ENVRI-Hub empowers researchers to develop innovative methodologies and accelerate progress in climate science and environmental monitoring. This presentation will highlight the technical underpinnings of the ENVRI-Hub that enable machine-to-machine (M2M) communication and interoperability, fostering collaborations between data providers, scientists, and e-infrastructures. We will showcase examples that demonstrate how the ENVRI-Hub can catalyse interdisciplinary research, enhance data integration, and support the development of climate and environmental models.
2025
Istituto di Metodologie per l'Analisi Ambientale - IMAA
ENVRI-Hub
Environmental Research Infrastructures
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/549884
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