Applications of conventional isotopes (e.g., H, O, C, N, and S), as well as non-conventional (e.g., B, Li, Fe, Cu, Zn, and Mg) and radiogenic isotopes (e.g., Sr, Nd, and Pb), offer unique opportunities to evaluate deep geological processes, environmental processes and their interactions within the Critical Zone (CZ). Human-induced climate change represents one of the most pressing environmental challenges of the twenty-first century; in the light of this, isotopic composition analysis provides an effective means to investigate it. Numerous studies have highlighted the fundamental role of isotope geochemistry in understanding environmental systems to critical zone processes, and the volume of research in this field continues to grow. Considering this, a comprehensive inventory of stable and radiogenic isotopes has become essential for tracking processes involving fluids, minerals, rock evolution, and origin, as well as examining interactions in soils, plants, and other reservoirs. Currently, data and information are unevenly distributed across various sources and institutions, leading to challenges in data recovery and integration. To address this gap, the ITINERIS Project (PNRR) has initiated Work Package 8.9, which focuses on developing the ISOTOPE Virtual Research Environment (VRE). A VRE can be described as an online environment offering remote and shareable disk space (workspace), catalogues and several customized tools for data processing. This initiative represents a pioneering step toward establishing Italy's first comprehensive national VRE service, encompassing a national database on stable isotopes. The Isotope VRE integrates tools for data analysis, interpretation, and modelling, enabling researchers and stakeholders to access coordinated information and advanced analytical tools. Some examples of data modelling are here reported: i) data plotting; ii) ternary diagrams; iii) mixing models. Initial results demonstrate the significant potential of the Isotope VRE in advancing our understanding of Earth system processes. Additional mathematical modelling approaches are under development, further enhancing the platform's capabilities. The Isotope VRE aims to provide the scientific community with a comprehensive virtual research environment for isotopic data sharing, analysis, and interpretation. This platform will empower researchers to investigate environmental processes with a suite of powerful tools, fostering new insights and applications in geochemistry and beyond.
How to cite: Di Giuseppe, P., Gennaro, S., Perrone, E., Agostini, S., Tunno, I., Trumpy, E., Rielli, A., Baneschi, I., Boschi, C., Cornacchia, I., Pennisi, M., Salvadori, M., Regattieri, E., Vezzoni, S., Dini, A., and Provenzale, A.: The Isotope Virtual Research Environment developed within ITINERIS Project: Isotope Studio, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7885, https://doi.org/10.5194/egusphere-egu25-7885, 2025.
Solving many environmental challenges requires connecting a variety of datasets with advanced statistical or AI models, and to access distributed computing resources to create workflows or digital twins. Digital twins are particularly challenging because they require the integration of many datasets and models, resulting in complex interactions. Furthermore, researchers rely on interdisciplinary collaboration to build workflows and digital twins. To that end, they need to discover, reuse, and sometimes modify existing assets. While this can be supported by Virtual Research Environments (VREs), most existing solutions are tailored to a specific domain or use case, making it difficult to integrate external resources or to support the complex model composition required by digital twins.
To address these limitations, we have developed Notebook-as-a-VRE (NaaVRE), a VRE solution built on top of JupyterLab. NaaVRE enables researchers to create computational blocks by containerizing the cells of notebooks, to organize them into workflows, and to manage the full experimental cycle, including data and workflow sharing. The tool includes features such as metadata-driven resource discovery, workflow automation, and compatibility with external repositories. Designed for cloud infrastructures, NaaVRE provides cost-efficient and scalable solutions to support digital twin development.
Using NaaVRE, we build customized virtual labs to address specific scientific problems. These gather models, data access tools, workflows, and documentation into a shared space, where a community of users can develop, share and reuse them. We present a framework to guide the development and operations of virtual labs throughout their entire lifecycle.
We showcase NaaVRE and by building customized virtual labs for scientific data processing workflows and prototype digital twins. Those virtual labs are managed by LifeWatch ERIC and the University of Amsterdam following the aforementioned development framework. They include characterizing ecosystem structures with LiDAR data, tracking bird migration using radar, mapping invasive species, deriving essential variables in the context of the ENVRI-Hub NEXT project, and developing digital twins of ecosystems in the context of the Dutch NWO LTER-LIFE project.
How to cite: Pelouze, G., Koulouzis, S., Greuell, K., Soveizi, N., and Zhao, Z.: Notebook-as-a-VRE (NaaVRE): collaborative virtual labs to build digital twins of ecosystems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10262, https://doi.org/10.5194/egusphere-egu25-10262, 2025.
The Cloud Computing Platform (CCP) was developed under the aegis of D4Science [1]. D4Science is an operational digital infrastructure co-funded by the European Commission, and represents a significant advancement in supporting the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, open science, and reproducible data-intensive science. D4Science has evolved to harness the "as a Service" paradigm, offering web-accessible Virtual Research Environments (VREs) [2] that have also been instrumental in facilitating science collaborations [3] with a particular focus on Earth observation, Earth science, and marine and agricultural environments. These environments simplify access to datasets while concealing underlying complexities, and include functionalities such as a cloud-based workspace for file organisation, a platform for large-scale data analysis, a catalogue for publishing research results, and a communication system rooted in social networking practices.
A key component for enabling large-scale, affordable, and reproducible computation and data analysis is CCP: a cloud computing platform specifically designed for VREs and Open Science.
CCP enables researchers to import, execute, and share methods ranging from statistical analysis to image classification, from AI models to 3D reconstruction, from data format conversion to pattern searching in DNA sequences, while embodying FAIR (Findable, Accessible, Interoperable, and Reusable) principles.
By leveraging container technology, an API-based design, and adherence to standards such as the OGC Processes API [4], CCP supports high interoperability, flexibility and integrability in scientific workflows. Methods can be written in any programming language (Python, Julia, R, etc) and executed either via dedicated web UIs or programmatically from virtually any development environment (command line, custom applications, Galaxy workflows, Jupyter notebooks, RStudio, etc). Code generators are provided to ease the integration into common scientific tools.
CCP can be deployed on container orchestration platforms, such as Docker Swarm or Kubernetes, which can leverage specialized hardware configurations (e.g., HPC clusters or GPU-enabled nodes) depending on the policies and resources available, thereby offering flexible and scalable computational environments per the needs of each community.
Automatic provenance management captures the complete history of a method's execution for reproducibility and accountability, according to common provenance models (Prov-O, RO-crate). Re-submitting executions can be as simple as clicking on a shared link.
CCP has been integrated into several VREs, many related to Earth science including the Blue-Cloud [5] virtual laboratories and demonstrators and ITINERIS [6].
References
1. M. Assante et al. (2019) “Enacting open science by D4Science”. Future Gener. Comput. Syst. 101: 555-563 10.1016/j.future.2019.05.063
2. L. Candela, D. Castelli and P. Pagano(2023) “The D4Science Experience on Virtual Research Environments Development". in IEEE Computing in Science & Engineering, doi: 10.1109/MCSE.2023.3290433
3. M. Assante et al. (2023) “Virtual research environments co-creation: The D4Science experience”. Concurrency Computat Pract Exper. 2023; 35(18):e6925. doi:10.1002/cpe.6925
4. https://ogcapi.ogc.org/processes/
5. https://cordis.europa.eu/project/id/101094227
6. ITINERIS, Italian Integrated Environmental Research Infrastructures System, Funded by EU - Next Generation EU PNRR- Mission 4 “Education and Research” https://itineris.cnr.it/
How to cite: Oliviero, A., Lettere, M., Dell'Amico, A., and Pagano, P.: CCP: A Cloud Computing Platform for VREs in Earth Sciences, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18524, https://doi.org/10.5194/egusphere-egu25-18524, 2025.
The European Plate Observing System (EPOS) addresses the problem of homogeneous access to heterogeneous digital assets in geoscience within the European tectonic plate. EPOS is a European Research Infrastructure Consortium (ERIC) since 2018, with the goal of building long-term and sustainable infrastructure for solid Earth science. The EPOS Data Portal was launched into the operational phase in April 2023 and is introducing new ways for cross-disciplinary research, especially for data discovery. Currently the EPOS Data Portal, a metadata and semantic-driven system for integrating Data, Software and services, provides access to data and data products from ten different geoscientific areas: Seismology, Near Fault Observatories, GNSS Data and Products, Volcano Observations, Satellite Data, Geomagnetic Observations, Anthropogenic Hazards, Geological Information and Modelling, Multi-scale laboratories and Tsunami Research. The presentation shows the achievements of the EPOS community, demonstrates features of the Portal user interface and also the underlying architecture of the whole system and online processing environment. The IT system as such is shared as Open Source and is under continuous development and improvement, following the SDLC methodology: Shape Up.
This presentation focuses on the integration of Jupyter Notebooks into EPOS through Virtual Research Environment (VRE) which allows advanced processing of datasets provided already through EPOS Data Portal. Examples of Jupyter Notebooks covering various scientific multidisciplinary use cases introduce typical data processing workflows and visualizations for efficient use of services collected through EPOS. Expansion of the EPOS-DCAT-AP metadata model by new entities for managing software components and its utilization opens new possibilities for data access and paves the road for integration into other e-infrastructures.
How to cite: Michalek, J., Giuliacci, K., Spinuso, A., Trani, L., Bailo, D., Paciello, R., Neut van der, I., Kocot, J., and Marchetti, D. and the EPOS IT Team: Jupyter Notebooks in European Plate Observing System (EPOS), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11023, https://doi.org/10.5194/egusphere-egu25-11023, 2025.
In order to provide users with fast and easy access to multidisciplinary data originating from large collections, MARIS has developed a software system called BEACON that can, on the fly with high performance, extract specific data based on the user’s request. This software has been customised and deployed in the Blue-Cloud2026 project and several other European projects and is designed to return one single harmonised file as output, regardless of whether the input contains different data types. In January 2025, BEACON 1.0.0 was made publicly available as an open-source software, allowing everyone to set-up their own BEACON ‘node’ to enhance the access to their data or use existing BEACON nodes from well-known data infrastructures such as Euro-Argo or the World Ocean Database for fast and easy access to harmonized data subsets. More technical details, example applications and general information on BEACON can be found on the website https://beacon.maris.nl/.
Within the context of Blue-Cloud2026, BEACON is deployed to provide access to harmonised subsets from Blue Data Infrastructures for the WorkBenches (WB) that aim to generate harmonised and validated data collections of Essential Ocean Variables (EOVs). To this end a set of monolithic BEACON nodes were set-up for relevant data collections such as the WOD, CMEMS Cora, Euro-Argo and more. Developments are well underway for parallel deployment of these BEACON instances and related notebooks at the D4Science e-infrastructure as part of the Blue-Cloud VRE, giving access to all users registered as Blue-Cloud users.
Going one step further, the output from multiple monolithic BEACON instances are combined into one merged BEACON node for each WB. Work is ongoing for a structural mapping from each monolithic BEACON to the target Common Metadata Profile as defined by the WB teams. These mappings will be used in the BEACON queries to retrieve and load contents ‘as-is’ from monolithic BEACON instances into the merged BEACON instances, giving a common structure for variables, units, values, quality flags, and common metadata profile fields. The structured metadata and data will be supplemented by additional metadata data as available for each of the monolithic BEACON instances.
This presentation will cover an introduction of the Blue-Cloud 2026 project and developments of the merged BEACON nodes, explaining how it can practically serve as data lakes for many VRE applications and how it is extendable to other domains. By using examples from the WBs, the reduction in time and effort spent for the researchers to collect the data are highlighted.
How to cite: Schaap, D. M. A., Thijsse, P., Krijger, T., and Kooyman, R.: Blue-Cloud 2026 project - Deploying BEACON data lakes for harmonizing ocean data access for Virtual Research Environments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4993, https://doi.org/10.5194/egusphere-egu25-4993, 2025.
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.
How to cite: Bundke, U., Adamaki, A., Bailo, D., Brus, M., Dema, C., De Nart, D., Drago, F., Gutierrez David, M., Hienola, A., Petzold, A., Vermeulen, A., and Zhao, Z.: The ENVRI-Hub: Advancing Multidisciplinary Collaboration and FAIR Data Integration in Environmental Research, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9099, https://doi.org/10.5194/egusphere-egu25-9099, 2025.
The Geoportal technology is an open-source framework designed to address the challenges of managing and publishing georeferenced research objects. These objects are “complex” documents (called Projects), consisting of various files and metadata and are characterized by geospatial and temporal features.
The Geoportal platform allows user communities to fully customize the data model for their specific instance, enabling them to define the structure, content, and workflow of the research objects to be managed. This highly configurable framework can be adapted to diverse application scenarios, which may vary in terms of:
- the types of projects to be supported;
- the workflows guiding the publication, updating, and accessibility of objects based on access policies.
Moreover, this technology emphasizes interoperability and scalability, facilitating the organization and sharing of geospatial, temporal, and multimedia data across multiple domains. By adhering to international standards such as OGC’s Web Map Service (WMS) and Web Feature Service (WFS), the Geoportal ensures seamless integration with other systems, making it a powerful tool for collaborative research.
Developed on the D4Science infrastructure, the Geoportal integrates Web-GIS technologies, offering tools for spatial and temporal data analysis and enabling dynamic visualizations of geodata. Its capabilities include real-time data harvesting, interactive mapping, and seamless integration of up-to-date research outputs.
The system includes two primary interfaces:
- Data-Entry Interface: Allows users to create, edit, and validate new data entries through a moderation process, ensuring that all entries are reviewed and approved by a supervisor.
- Data-Viewer Interface: Provides public access to published datasets via an intuitive cartographic map and timeline, enabling historical navigation of the data.
An API further extends the platform’s functionality, supporting automated data retrieval and specialized queries, making it an ideal solution for large-scale data management and integration.
As a case study, we present the Dataset for the National Geoportal for Archaeology (D4GNA), developed for the Italian Ministry of Culture. D4GNA leverages Geoportal technology to create a comprehensive, scalable environment for managing archaeological data, supporting a wide range of geospatial, textual, and multimedia formats. This application exemplifies Geoportal’s capabilities, focusing on the collection, management, and publication of archaeological data within the National Geoportal for Archaeology (GNA) .
Since its launch, D4GNA has cataloged over 1,150 archaeological investigations across Italy and 15 abroad, all licensed under Creative Commons CC-BY 4.0. Future enhancements, including the assignment of Digital Object Identifiers (DOIs) and integration with D4Science’s Catalog service, will enable advanced search functionality and provide statistical insights into the data.
This study demonstrates the transformative potential of Geoportal technology in enabling efficient management, publication, and sharing of georeferenced research objects. By offering a flexible and interoperable framework, Geoportal supports diverse domains such as environmental studies, geology, and climate research, facilitating the integration of geospatial, temporal, and multimedia data. Its adherence to FAIR principles and integration with international standards ensures interoperability and scalability, promoting open access and collaboration in scientific research. This highlights Geoportal as a powerful tool for advancing scientific discovery and preserving valuable research data across disciplines.
Keywords
Georeferenced research objects, Web-GIS, Interoperability, D4GNA
How to cite: Mangiacrapa, F., Vannini, G. L., and Pagano, P.: Geoportal Technology: A Customizable Framework for Managing and Publishing Georeferenced Research Objects, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19423, https://doi.org/10.5194/egusphere-egu25-19423, 2025.
The European Marine Observation and Data Network (EMODnet) is the gateway to multidisciplinary marine in-situ data and data products and has been funded by the European Commission for 15 years. In particular, EMODnet Chemistry collects and makes freely available nearly 1,300,000 million metadata entries and related datasets on seawater quality in various matrices.The aim of this contribution to the EGU is to illustrate this long-term initiative of the European Commission and its wealth of use cases. These show how data fairness can enable faster and more accurate modelling and solutions to pressing global environmental emergencies.
The EMODnet Chemistry data infrastructure supports the development of evidence-based knowledge on eutrophication, ocean acidification and contaminants, including marine litter. The measurement data are accessible via a data discovery and access service and are regularly aggregated, harmonised and validated to create thematic data collections and associated data products. Subsets of the data collections can be downloaded via the webODV explorer and extractor tool, which also allows users to create customisable data analyses and visualisations. The functioning of EMODnet Chemistry relies heavily on SeaDataNet: a pan-European marine data management infrastructure involving 110 national oceanographic data centres, which has developed consolidated services, standards and best practises.
Over the years, EMODnet Chemistry has collected dozens of success stories about different types of data providers and data users who were willing to open up their data and use them for many purposes. Data providers include marine research institutes, environmental agencies, government marine managers from EU Member States dedicated to marine monitoring and/or marine science, ICES, the Copernicus Marine Service (CMEMS) and citizen scientists.
In terms of data users, the European Environment Agency, the EC Joint Research Centre and most of the Regional Sea Conventions have made extensive use of EMODnet Chemistry data for the implementation of the European Union's marine policy. Researchers and CMEMS use this data source to develop tools, data products and models to assess the state of the environment and trends. More recently, the partners of the Horizon Europe Blue Cloud 2026 project, which supports the implementation of the European Open Science Cloud, have used EMODnet Chemistry data together with data from CMEMS and the World Ocean Database. The objective is to develop a toolbox to create customisable, validated datasets on Essential Ocean Variables of eutrophication and assess the consistency of the information. Based on these data sources the Project is also developing tools for calculating online metocean information and indicators of the environmental quality of the Mediterranean and global oceans. Finally, EMODnet together with CMEMS is providing the data backbone for EDITO: the core infrastructure of the European Digital Twin of the Ocean, which aims to facilitate the development of applications for the digital twin.
In conclusion, EMODnet’s work, although focused on European Union data sources, is increasingly relevant to support the implementation of agreements and data services at a global level. This contribution will continue and hopefully be expanded in the coming years to increase the global marine knowledge
How to cite: Giorgetti, A., Altobelli, C., Schaap, D. M. A., Buga, L., Fyrberg, L., Gatti, J., Holdsworth, N., Iona, A., Larsen, M. M., Schlitzer, R., Østrem, A. K., Tsompanou, M., Troupin, C., and Wesslander, K.: Data exchange and integration: Use cases for EMODnet Chemistry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19342, https://doi.org/10.5194/egusphere-egu25-19342, 2025.
With the increasing availability of higher-resolution weather and environmental data as well as advances in Machine Learning (ML) algorithms, data-driven approaches have emerged over the last few years as innovative and fast-computing solutions for addressing detection and prediction of extreme weather events, like storms and wildfires.
Designing, training and deploying ML models is not trivial and can result in a time consuming process. An integrated software infrastructure for supporting and automating the different steps of the workflow, from weather/climate data gathering and preparation, ML model configuration and training, to deployment of the trained model for detection and prediction applications is required. In this regard, solutions for tracking training metrics and provenance information are crucial components for reproducibility of the results. Besides the software components, HPC infrastructures for handling distributed training over multiple GPUs are also needed to speed up the process.
In the context of the EU-funded interTwin project we are implementing ML-powered Digital Twin (DT) applications for the analysis of extreme events (i.e., Tropical Cyclones and wildfires). The interTwin project is designing and developing a generic Digital Twin Engine (DTE) for supporting DTs from different scientific domains. The DTE provides a software and computing infrastructure for simplifying the creation and management of complex DT workflows.
This contribution, in particular, will present how the interTwin DTE is supporting the different workflow stages, from model training to their execution, of ML-based DT applications for the detection and prediction of extreme events.
How to cite: Elia, D., Donno, E., Bunino, M., Fronza, M., Donno, D., Padovani, G., Fiore, S., and Manzi, A.: Facilitating the development of Machine Learning-based Digital Twin applications for extreme weather events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13888, https://doi.org/10.5194/egusphere-egu25-13888, 2025.
The introduction of FAIR data practices into the assessment process of the Intergovernmental Panel on Climate Change (IPCC) enhances the transparency of the Assessment Reports (ARs). The approach focuses on the figure creation process and the reproducibility of figures within the reports. The process of creating figures for IPCC reports makes it particularly challenging to credit all contributors. A single figure can incorporate data from observations, models, and publications, originating from numerous sources and generated by multiple authors, each contributing to different parts of the figure. Additionally, it is not always straightforward to include all those involved in the creation process, as the final data (used to produce the figure) often result from assessments and post-processing of other data (input or intermediate data). Among the plans and recommendations for the current Seventh Assessment cycle is the use of the Complex Citation approach (Stockhause et al., 2024), which has been developed in the RDA Complex Citation Working Group (Agarwal et al., 2024).
Some chapters of the ARs use established community frameworks for the generation of their figures. These are currently harmonized in the CMIP Rapid Evaluation Framework (REF) project for the AR7 Fast Track simulations. Others use interactive and shareable Jupyter notebooks. The IPCC needs to support and harmonize both ways of working. Further, the authors’ additional effort to meet the metadata and data requirements needs to be minimized. Therefore, the collaboration with both projects, REF and Jupyter, is planned to offer broad support for the ways of working of a large number of authors.
This contribution analyzes how the Complex Citation approach, with the aims of giving credit to input providers and enabling the traceability of all digital objects used to create figures, can be implemented in REF and Jupyter and integrated in the AR7 process to support the IPCC’s FAIR and open data approach.
References:
Agarwal, D., Ayliffe, J., J. H. Buck, J., Damerow, J., Parton, G., Stall, S., Stockhause, M., & Wyborn, L. (2024). Complex Citation Working Group Recommendation. Zenodo. https://doi.org/10.5281/zenodo.14106602
Stockhause M, Huard D, Al Khourdajie A, Gutiérrez JM, Kawamiya M, Klutse NAB, et al. (2024) Implementing FAIR data principles in the IPCC seventh assessment cycle: Lessons learned and future prospects. PLOS Clim 3(12): e0000533. https://doi.org/10.1371/journal.pclm.0000533
Links:
REF project: https://wcrp-cmip.org/cmip7/rapid-evaluation-framework/
Jupyter project: https://jupyter.org/
How to cite: Stockhause, M., Sitz, L., Pascoe, C., Agarwal, D., Ayliffe, J., Buck, J., Damerow, J., Gutiérrez, J. M., Hassler, B., Hoffman, F. M., Parton, G., Lewis, J., McRae, M., Stall, S., and Wyborn, L.: How can the Complex Citation be implemented in the IPCC AR7 using existing frameworks and interactive notebooks?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15036, https://doi.org/10.5194/egusphere-egu25-15036, 2025.
Posters on site: Thu, 1 May, 10:45–12:30 | Hall X4
The CNES (Centre National d'Études Spatiales) has developed the HAWK [1] (High resolution Altimetry WorKspace) framework as part of its expertise in supporting Earth observation missions. This platform, actually tailored for the SWOT [2] (Surface Water and Ocean Topography) mission, operates on the CNES High-Performance Computing (HPC) infrastructure and is strongly linked with the SWOT routine mission center.
HAWK provides a collaborative environment for hydrological and oceanographic data analysis, enabling remote access to extensive datasets without local downloads. Currently operational, the platform supports SWOT expertise activities and offers plethora of user tutorials [3].
Future developments aim to generalize HAWK for use with multiple Earth observation missions, expanding its accessibility and impact within the scientific community to promote EO data. We also have for objective to offer open training session to the communities.
References
[1] SWOT Mission, https://cnes.fr/projets/swot
[2] high-resolution-altimetry-workspace-hawk, HIGH RESOLUTION ALTIMETRY WORKSPACE (HAWK) – GEODES
[3] Microwave expertise center: Providing an efficient framework for microwave data exploration, https://www.proceedings.com/76012.html (IEEE Catalog No.: CFP24IGA-USB ISBN: 979-8-3503-6031-8)
How to cite: Petiton, J., Flavien, G., Mathilde, S., and Frery, M.-L.: The HAWK: Platform for Earth Observation Data Processing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1298, https://doi.org/10.5194/egusphere-egu25-1298, 2025.
Research into the effects of changing Arctic climate has been limited by large-scale in situ data availability because of the remoteness and harsh climate of the Arctic. Only recently, therefore, are hourly-to daily measurements covering most Arctic regions publicly available, but scattered in various local databases.
In this project, we obtained in situ weather data from all major Arctic regions from publicly available data sources across the Arctic with focus on the period 1990-2023. The data set, which contains 719 unique locations from 14 data sources and covers all Arctic regions, has been restructured and -formatted into a standardized data format, combined with metadata about location and elevation. It was further quality checked by running it through five optional modules of increasingly user-involved judgement-based checks. We supply the code involved in import and standardization, and the modular quality check, as well as the standardized, but unchecked data set, and the final, quality checked, data set.
The data set has the potential to benefit pan-Arctic in situ research opportunities as e.g. validation and ground truthing of modelling efforts.
How to cite: Rasmussen, L. H., Markussen, B., and Ditlevsen, S.: Compiling, normalizing and quality checking a pan-Arctic dataset og in situ weather observations from 1990-2023 collected from publicly available data sources, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3749, https://doi.org/10.5194/egusphere-egu25-3749, 2025.
The primary aim of the EU-funded AquaINFRA [1] initiative is the development of a research data infrastructure to help marine and freshwater scientists generate new knowledge for restoring healthy oceans, rivers, and lakes. Several use cases representing pan-Europe, the Baltic Sea, and the North Sea define the scope for implementing the infrastructure and demonstrating its potential. An essential goal of the project is to address high-quality, FAIR, and open multi-disciplinary data. In addition, the infrastructure focuses on making python- and R-based data analyses accessible as reusable tools, services, and workflows. Finally, a specific objective is to develop a platform that is compliant with the European Open Science Cloud (EOSC) Interoperability Framework as an overarching research infrastructure.
In this contribution, we provide an overview of the recent developments in AquaINFRA and show its realization in a use case. The key components of the AquaINFRA research data infrastructure are the Data Discovery and Access Service (DDAS), the AquaINFRA Interaction Platform (AIP), and the Virtual Research Environment (VRE).
The DDAS [2] is the backend of the infrastructure and based on a federated metadata search mechanism sending requests to selected remote metadata providers on the fly. Access to harmonized metadata is accomplished by leveraging community standards, such as the OGC API family including OGC API Records, OGC API Features, and OGC API Coverages. Another component of the DDAS is the Ontology Search that suggests alternative search terms for the keyword entered by the user.
The AIP [3] is the central gateway to the project and provides a search interface to find, access, and reuse aquatic digital resources. It is built on top of the DDAS and allows users to search for data, services, and software. Several features are provided to refine the search query, for instance, using a bounding box and selecting specific data providers.
The purpose of the VRE is to have a set of web-based applications facilitating the reuse of existing tools as well as the contribution of newly developed tools, and connecting them to create readily shareable and reproducible workflows. Hence, the VRE is composed of three modules:
- MyBinder is provided as a virtual lab to let users engage with an existing analysis written in R or Python in a pre-defined computational environment.
- OGC API Processes are provided as a web API service allowing researchers to make remote requests and integrate these into their analysis.
- Access to the Galaxy platform is provided to create reproducible computational workflows. To achieve that, the analysis scripts developed in the case studies are integrated into the Galaxy platform by wrapping the OGC API Processes as Galaxy tools.
Besides the research data infrastructure demonstrating the usefulness of FAIR open data and reproducible computational workflows, the project outcomes are expected to foster collaboration across borders, data infrastructures, and disciplines.
This project has received funding from the European Commission’s Horizon Europe Research and Innovation programme. Grant agreement No 101094434.
1) Project website: https://aquainfra.eu/
2) DDAS: https://vm4072.kaj.pouta.csc.fi/ddas
3) AIP: https://aquainfra.dev.52north.org/
How to cite: Konkol, M., Jirka, S., Hansen, H. S., Otsu, K., Domisch, S., Buurman, M., Bremerich, V., Labuce, A., Latvala, P., Oksanen, J., and Grüning, B.: The AquaINFRA research data infrastructure: Knowledge generation through FAIR open data and reproducible computational workflows, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9682, https://doi.org/10.5194/egusphere-egu25-9682, 2025.
The airspace is becoming increasingly crowded. High-rises, wind farms and airports all contribute to conflict with aerial organisms. Information about the movements of organisms in the air is required to identify stop-over sites, migratory routes, and patterns. This can inform mitigation of conflicts by, for example, wind-turbine curtailments or early warning systems for aviation. Weather radars, that continuously monitor the sky across continents, can be used to study movements of birds, bats, and insects. However, for continental scale analysis, large volumes of data are required to be processed and analyzed, which often rely on institute-specific tools and computational resources. This severely hampers collaborative efforts because of the initial investment of time and resources to gain access to existing computing infrastructure.
Here we show a Radar Aeroecology Virtual Lab (RA-VL) which uses the Lifewatch ERIC infrastructure to facilitate collaboration and re-use of infrastructure and tools. By providing RA-VL, we aim to facilitate collaboration between ornithological institutes. This Virtual Lab (VL) will reduce the initial investment of acquiring access and expertise to computational resources and provide immediate access to tools built by domain experts. These tools are then run in the cloud leveraging the performance and flexibility of cloud computing. The VL is shipped with the data management plan used by the University of Amsterdam's Animal Movement Ecology group (UvA IBED-TCE AME) to provide an out of the box solution for managing large datasets. RA-VL is currently capable of accessing, processing, managing and visualizing data from the The Royal Netherlands Meteorological Institute's (RNMI) open Radar Data repository. The VL has multi-language support, and has well known libraries such as bioRad in R and xradar in Python installed. Furthermore, it uses vol2bird for processing biological echoes found in Polar Volume files to Vertical Profiles. Notebook as a Virtual Research Environment (NaaVRE) provides a user-friendly interface to leverage functionality for parallel processing, data organization and visualization. Over the past four years, the RA-VL has seen a substantial amount of developments. By applying the Readiness Framework, key points were identified and updated to bring this VL from a Development-Version to a Demo-Version. By bringing the VL to the next Readiness Level we hope to receive critical feedback from the community to improve and prepare the lab for the next level.
How to cite: Wijers, B.-C., Pelouze, G., Koulouzis, S., Greuell, K., and Zhao, Z.: Radar Aeroecology in the cloud. A Virtual Lab for continental scale Aeroecological analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11500, https://doi.org/10.5194/egusphere-egu25-11500, 2025.
NSF Unidata is a community-focused data and software facility, funded primarily by the United States National Science Foundation. NSF Unidata’s mission is to provide the data services, tools, and cyberinfrastructure leadership that advance Earth Systems science, enhance educational opportunities, and broaden participation. NSF Unidata’s hallmark has been democratizing access to data and tools by providing open and free access to all its resources.
As the enabler of a broad community, NSF Unidata
- Acquires and distributes data to facilitate Earth system education and research
- Develops software for accessing, managing, analyzing, visualizing, and effectively using those data
- Provides comprehensive support to users
- Conducts training workshops on Unidata software packages
- Facilitates advancement of standards, conventions, and interoperability
- Provides leadership in geosciences cyberinfrastructure and fosters technological change
- Advocates on behalf of the university community on data issues and negotiates data agreements
- Fosters community interaction and engagement to promote sharing of data, tools, and ideas
- Grants equipment awards to universities to enable and enhance participation in Unidata
An integrated approach that transcends disciplinary and geographic boundaries is needed to understand and address societally important environmental problems such as weather prediction, climate change, and the water cycle. Similarly, an Earth Systems Science approach that employs inquiry-based learning is recommended for teaching geoscience. Advances in the Earth system science are possible only through state-of-the-art, robust, and flexible data and software infrastructure, transparent and seamless access to high-quality data from diverse sources, along with requisite tools and services to analyze, synthesize, visualize, interpret, and use the data effectively.
The university community conceived and established the NSF Unidata program more than forty years ago to meet the needs meteorology departments, specifically to acquire and distribute real-time weather data to U.S. universities, together with the necessary tools for data analysis and visualization.
While the program’s primary mission of serving the academic community remains unchanged through the years, the user base has broadened, and its activities and portfolio of products and services have grown as the discipline and community needs have evolved.
Over the past four decades, NSF Unidata has experienced a gradual but natural evolution from a program focused primarily on synoptic scale meteorology to one that serves a broader geosciences community. Unidata has attracted a broader community because it has been successful in providing tools and services that are open, free, interoperable, extensible, and platform independent. The robustness and quality of Unidata tools and services have resulted in their use beyond a community of several dozen universities in the U.S. to now several thousand organizations in academia, research and operational sectors in over 150 countries. In the process, NSF Unidata has matured into a cornerstone, cloud-based data and software facility upon which the Earth system science community and other stakeholders have come to rely.
In this talk, I’ll present NSF Unidata’s evolution over the past forty years, how we are reimagining our future activities in delivering a comprehensive suite of products and services to meet the current and emerging needs of the Earth Systems Science research and education community, and the lessons learned as the facility evolved.
How to cite: Ramamurthy, M.: NSF Unidata: The evolution of a community-focused data and software facility over a four-decade period, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13649, https://doi.org/10.5194/egusphere-egu25-13649, 2025.
ATMO-ACCESS is a research infrastructure pilot project funded under the Horizon 2020 program (2021–2025) that addresses the needs of distributed atmospheric research infrastructures (RIs), including ICOS ERIC (Integrated Carbon Observing System), ACTRIS ERIC (Aerosol, Clouds, and Trace Gases Research Infrastructure), and IAGOS (In-flight Global Observing System). The goal of ATMO-ACCESS is to develop sustainable solutions for access to distributed atmospheric research facilities. Specific activities are directed to provide virtual, physical, remote and hybrid access to users world-wide.
The project has notably developed innovative online services, leveraging the expertise of these three infrastructures to provide virtual access to advanced digital resources. These services include data archiving, integrated data products, analysis tools, and online training resources, facilitating the integration of several infrastructures.
These initiatives strengthen the ability of scientific communities and stakeholders to effectively exploit the data and tools available to meet the challenges associated with the study of climate, air quality and the atmosphere.
How to cite: Dubost, A., Philippin, S., Faber, M., Lund Mhyre, C., Vermeulen, A., Thouret, V., and Riffault, V.: ATMO-ACCESS: Advancing Atmospheric Research with Integrated cross-RI Virtual Services, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15633, https://doi.org/10.5194/egusphere-egu25-15633, 2025.
The EOSC EU Node is a key enabler of multidisciplinary and multinational research, promoting the use of Findable, Accessible, Interoperable, and Reusable (FAIR) data principles. As the first European-level node of the EOSC Federation, the platform provides researchers with secure access to interoperable data, computational resources, and managed services tailored for complex research workflows.
This presentation will highlight environmental and climate science success stories of researchers leveraging EOSC EU Node services and demonstrate the potential of the platform to address challenges in data access, integration, and reuse. Examples include the use of Interactive Notebooks for data visualisation and analysis, and File Sync and Share for secure, collaborative data management across global teams. These use cases demonstrate how the EOSC EU Node fosters seamless integration of data and services, accelerates knowledge sharing, and supports reproducible research.
By bridging thematic and regional infrastructures, the EOSC EU Node is empowering researchers to tackle pressing global challenges, including climate change, biodiversity loss, and disaster risk reduction. The presentation will showcase the platform’s role in driving collaboration, innovation, and impactful research outcomes in the era of open science.
Keywords: FAIR data, climate science, environmental research, EOSC Federation, cloud services, open science.
How to cite: Dietrich, M. and Gutierrez, M.: Empowering Environmental Research Through the EOSC EU Node: FAIR Data and Scalable Services, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16205, https://doi.org/10.5194/egusphere-egu25-16205, 2025.
Climate warming in Arctic is 3-4 faster than in rest of the globe. Even in Arctic context Svalbard is a hotspot of climate change but also international research collaboration and geopolitics. Svalbard is under Norwegian sovereignty but it has very international research environment based partly on Svalbard Treaty. This creates an ambiguous and continuously changing operational landscape as geopolitical tensions increases.
Svalbard Integrated Arctic Earth Observing System (SIOS) is an international consortium of 29 research institutions from 10 countries with research interests and infrastructure in and around Svalbard. Mission of SIOS is to make ESS data in and round Svalbard available through the SIOS data management system following FAIR principles, decrease the environmental footprint of science by pooling resources and enabling new technology, sharing infrastructure and facilitating interdisciplinary research collaboration.
SIOS focuses on long-term monitoring of parameters that are important to understand the Arctic in the context of global environmental change. However, the observing system is dynamic and is developed continuously by so called SIOS Science Wheel concept. A State of Environmental Science in Svalbard reports (SESS) is in the core of the Science Wheel. The SESS report is an arena for open sharing of ideas and discussions on measures that should be taken to enable scientists to provide observations needed to gain a comprehensive view of the Earth System of Svalbard and the Arctic in general. The report summarises the state of current knowledge of key Earth System Science parameters and analyses how these parameters influence one another. It combines the long-term monitoring data that form the core of the observing system with innovative monitoring and research.
SIOS Access program has been developed to foster excellent Arctic science and to facilitate research infrastructures to function at ideal capacity. SIOS has built its own training programs which for example help field scientists to utilize different level of remote sensing in their research and planning field campaigns.
In this presentation we will share our experiences on building SIOS, multinational and multidisciplinary research infrastructure, Science wheel success stories, challenges and lessons learned and way forward towards IPY 2032-2033.
How to cite: Lihavainen, H., Matero, I., Jones, E., Hübner, C., Kivits, D., and Ashley, R.: Svalbard Integrated Arctic Earth Observing System, regionally distributed, multinational and multidisciplinary Research Infrastructure, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16973, https://doi.org/10.5194/egusphere-egu25-16973, 2025.
As part of the ITINERIS project, funded by the NextGenerationEU programme (2022-2025), the downstream effects of climate and environmental change are being investigated. The Virtual Research Environment VRE (Assante et al., 2021) on downstream impacts of environmental change is dedicated to the use of Research Infrastructures providing tools for the visualisation, analysis, and data sharing. The Downstream VRE hosted by the D4Science infrastructure (Assante et al., 2019) and toolboxes have been developed for the marine and terrestrial domains.
The marine domain toolbox will take advantage of the available data in order to generate an integrated dataset for temperature, salinity, pH and CO2 in the gulf of Trieste (Italy) with a focus on the National Institute of Oceanography and Applied Geophysics – OGS data for the last 10 years as use case. Once the data is harvested a subsequent data validation, quality control and merging will be performed using erddap-navigator, a web application that allows the user to visualize, assign quality control flags, analyze and merge data. The integrated dataset will then be used to calculate climate change indicators, such as ocean acidification and ocean carbon cycle budget.
The land domain toolbox aims to analyse areas subject to hydrogeological hazards (landslide phenomena). In this context, a geoserver and a geonetwork have been implemented containing maps at regional level of the NE-Italy region of Friuli Venezia Giulia. At the local level, different monitoring systems (interferometric radar, 1 GPS, 2 extensometers and 2 inclinometers, date coordinator) were installed at the Passo della Morte in Forni di Sotto to detect possible ground instabilities. The instruments provide geodata in various formats that define trends in slope displacement through interpretation, e.g. of time series. Each product has its own description and can be downloaded.
Acknowledgements
The work has been funded by EU - Next Generation EU Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realisation of an integrated system of research and innovation infrastructures” - Project IR0000032 – ITINERIS - Italian Integrated Environmental Research Infrastructures System - CUP B53C22002150006.
The authors acknowledge the Research Infrastructures participating in the ITINERIS project with their Italian nodes: ACTRIS, ANAEE, ATLaS, CeTRA, DANUBIUS, DISSCO, e-LTER, ECORD, EMPHASIS, EMSO ,EUFAR ,Euro-Argo, EuroFleets, Geoscience, IBISBA, ICOS, JERICO, LIFEWATCH, LNS, N/R Laura Bassi, SIOS, SMINO.
References
Assante, M., Candela, L., Castelli, D., Cirillo, R., Coro, G., Frosini, L., Lelii, L., Mangiacrapa, F., Pagano, P., Panichi, G., & Sinibaldi, F. (2019). Enacting open science by D4Science. Future Generation Computer Systems, 101, 555–563. https://doi.org/10.1016/j.future.2019.05.063https://doi.org/10.5281/ZENODO.10070443
Assante, M., Candela, L., & Pagano, P. (2021). Blue-Cloud D4.4 Blue Cloud VRE Common Facilities (Release 2). https://doi.org/10.5281/ZENODO.10070443
How to cite: Franceschini, R., Reyes, C., Altenburge, A., Rossi, G., and Giorgetti, A.: Downstream VRE for multidisciplinary applications: Land and Marine domain toolboxes., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17213, https://doi.org/10.5194/egusphere-egu25-17213, 2025.
The monitoring and study of forests is essential to understand their condition, dynamics and to adopt optimal management to ensure their sustainability. Long-term studies require the installation of permanent field sites with sensors and equipment and collection of data, also from other sources, which are often difficult to obtain both in terms of discovery and standardization.
In this framework, Virtual Research Environments (VRE) are online research platforms that allow easy access to the available FAIR data, to find smart solutions and to support decision making. The Virtual Research Environment for Essential Variables (VRE-EVs), created within the ITINERIS NextGeneration EU project (https://itineris.cnr.it) and hosted on the D4Science infrastructure (https://itineris.d4science.org), offers several services to registered users to develop open and reproducible science. The VRE-EV aims to enable virtual environmental research in the perspective of the two global frameworks of Essential Biodiversity Variables (EBVs; e.g., phenology, species distribution) and Essential Climate Variables (ECVs; e.g., surface air temperature, precipitation, relative humidity), which are known to be critical for plant and soil biogeochemical processes (e.g., tree growth, soil mineralization, water fluxes, litter decomposition). This is very interesting in experimental sites with long-term monitoring, such as that installed in the 3000-ha forest environment of Collelongo - Selva Piana (https://deims.org/9b1d144a-dc37-4b0e-8cda-1dda1d7667da), one of the founding sites of the italian ICP Forests network and also part of the eLTER and AnaEE international research infrastructures. The main study site is a pure mature beech forest (Fagus sylvatica L.) with trees over 125 years old. This study describes the VRE-EVs and demonstrates, through a use case, how data from heterogeneous sources, made easily accessible within the VRE-EVs, are useful to analyse Forest environments Essential Variables.
We propose the use of an interactive application (Shiny App) specifically developed within the VRE-EVs, an RStudio platform, to integrate the functions provided by the ReLTER package (10.1016/j.ecoinf.2024.102915) and by all other ITINERIS project facilities, with the aim of merging different datasets available in European repositories (e.g., Copernicus Land and Climate Services, European Environment Agency), international data publishers (e.g., Pangaea, Zenodo), other essential variables online repositories, and in-situ data. The joint analysis of the different datasets available through the VRE-EV allows the improvement of ecological, ecophysiological processes and carbon fluxes of the Collelongo beech forest in response to global changes.
How to cite: Costafreda-Aumedes, S., Tagliolato, P., Giusti, R., Iannuccilli, M., Matteucci, G., Mazzenga, F., Messeri, A., and Oggioni, A.: Implementation of a Virtual Research Environment (VRE) to the study of forest environments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17240, https://doi.org/10.5194/egusphere-egu25-17240, 2025.
Malta, as a small island state, faces increasing challenges from climate change due to its vulnerability to climate impacts. This study investigates the application of geospatial tools and techniques to enhance Malta’s capacity for climate change-related planning and management, aligning with Sustainable Development Goal (SDG) 13: Climate Action. The methodology integrates historic cartographic resources, as detailed in our previous work (Tranchant et al., 2024), with contemporary approaches such as UAV photogrammetry and dataset comparisons using software like Cloud Compare. These datasets are augmented by ground-truthing data, including geotechnical monitoring via tilt plates and ground monitoring nails - both deliverables from a previous project, Coastal Satellite-Assisted Governance (SAGE). The collected data will be compiled into a unified geodatabase to enhance disaster risk reduction efforts through real-time monitoring of climate-enhanced risk levels. The tools and insights, where permissible, will be shared with stakeholders beyond government and academia to promote education and public awareness. While the study does not directly aim to mitigate the effects of climate change, it strengthens the Maltese government’s capacity to proactively evaluate and respond to its impacts, particularly with respect to coastal dynamics. Future efforts will focus on developing an open-source, WebGIS-based A-DiNSAR monitoring system for ground deformation. This system aims to replicate the Copernicus European Ground Motion Service while leveraging higher-resolution datasets to achieve greater precision at localized scales, such as monitoring ground movement and infrastructural stability in cliffside and coastal zones. By addressing areas most susceptible to ground movement and stability issues due to climate change, the study enhances Malta’s resilience to climate impacts, aligning with the objectives of SDG 13: Climate Action.
How to cite: Gauci, C., Belaama, A., Fenech, D., Vassallo, J., Buhagiar, G., and Colica, E.: Use of Geospatial tools and techniques for enhancing capacity for climate change-related planning and management in Malta, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18357, https://doi.org/10.5194/egusphere-egu25-18357, 2025.
Recent advancements in laboratory implementation and instrumentation have led to the generation of increasingly abundant data, with the need for greater collaboration and data sharing. To address this challenge, the expansion of e-infrastructures and the development of Virtual Research Environments (VREs) have become essential.
VREs provide an integrated ecosystem for data collection, analysis, and publication, following the Open Science principles, of transparency, inclusion, integrity, and collaboration. VREs are based on the D4Science e-infrastructure, which promotes collaboration and cooperative work among the scientific communities and the stakeholders identified by the researchers.
In the framework of the ITINERIS Project, the new comprehensive Italian Research Infrastructures (RIs) hub in the geoscientific and environmental fields, several multidisciplinary teams are developing thematic VREs for studying the entire Earth System, by combining field and lab measurements, data analysis, and modelling tools across all the environment domains.
Among the VREs, the “Critical Zone (CZ) VRE” is specifically designed for collecting datasets and information from the Critical Zone Observatories (CZOs, active in Italy and abroad) primarily managed by Italian research teams and including tools for data visualization and analysis, as well as models useful for studying the complex dynamics of the Critical Zone.
The Critical Zone represents the thin layer between the unweathered bedrock and the top of the vegetation canopy, where “rock meets life”. It includes rocks, soil, water, microbiota, vegetation and fauna, along with the services they provide to humankind and all the processes supporting terrestrial ecosystems and the soil-vegetation-atmosphere interactions.
D4Science-enabled Critical Zone VRE offers a set of tools supporting all the steps of the research lifecycle, from data collection to data analysis, and visualization. Data collection and dataset assembly are fostered by the Collaborative Storage Framework, which promotes teamwork among users and offers a collaborative space to share digital objects. For data analysis, the Critical Zone VRE is equipped with an Analytics Engine Framework, which includes Cloud Computing Platforms (CCPs), as well as the DataMiner. Additionally, the Critical Zone VRE is equipped with RStudio 4 and JupyterLab. These tools enable the development of specific codes (in various free-license programming languages) and models that can be launched directly from the VRE to analyze and visualize data. Data publishing of research outcomes is also facilitated by the development of metadata and spatial data catalogues. In particular, the catalogues help to organize and make research outcomes available to the broader scientific and multidisciplinary community.
Further improvements in studying Critical Zone components and dynamics are essential, and in this case, valuable support can be gained through the interaction between the Critical Zone VRE and other VREs. An example is the interaction with the Isotope VRE, which contains a dedicated web application for analysis and modelling (called “Isotope Studio”) and aims to represent the first Italian database on environmental isotopes, allowing researchers and environmental managers to interpret and model bio-geochemical processes in the framework of the Environmental Sciences.
How to cite: Gennaro, S., Bove, P., Caparrini, F., Di Giuseppe, P., Marta, S., Perrone, E., Dini, A., Agostini, S., Trumpy, E., and Provenzale, A.: Virtual Research Environment for studying Critical Zone (CZ) dynamics and isotope fingerprinting: an approach for geoscientific data management and modeling within the ITINERIS project (PNRR, Italy)., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19176, https://doi.org/10.5194/egusphere-egu25-19176, 2025.
