A global coordination and continuous synthesis of interoperable data related to biogeochemical Essential Ocean Variables (EOVs) is critically needed to enhance the creation of information products and services to sustainably manage the climate system and ocean health. Among the existing biogeochemical EOVs, data synthesis products—which demonstrate the immense value of data coordination—already exist for carbon-relevant data (e.g. SOCAT, Global Ocean Data Analysis Project), and for methane and nitrous oxide (MEMENTO). The roadmap for building a Global Ocean Oxygen Database and ATlas (GO _2 DAT) (Grégoire et al (2021 Front. Mar. Sci. 1638 )) provides the theoretical basis to increase the interoperability of ocean oxygen data sets, without creating yet another separate repository. The goal is now to advance from the idea of GO _2 DAT to its implementation, building a sustainable, interoperable, and inclusive digital ecosystem for all stakeholders who may use ocean oxygen data. Successful implementation will require (I) the provision of guidance on data acquisition/ocean oxygen measurements, (II) recommended practices for ocean oxygen data management, including metadata requirements, uncertainty and data quality control attribution, (III) development of the ocean oxygen data platform including data flow and application of the recommended practices introduced in I and II, as well as its deep integration with cross-domain data federations such as the Ocean Data and Information System. This document provides an outline of GO _2 DAT’s objective and progress since 2021 and contributes to addressing these three requirements, synthesizing a series of global consultations on recommended practices for marine dissolved oxygen measurements, a working definition of ocean oxygen metadata, proposed data quality control levels and flags, a described novel mechanism for uncertainty attribution to allow the determination of data suitability for different scientific applications, and it concludes with an illustration of the data flow for implementation.

Under the umbrella of the EOSC ecosystem, the FAIR-EASE project funded under HORIZON-INFRA-2021-EOSC-01-04 aims to facilitate access to interoperable data and services for earth and environmental multi-disciplinary use cases, demonstrating the capabilities to support open science (https://fairease.eu/). Based on three of its pilots more specifically: the Volcano Space Observatory pilot, the Ocean Biogeochemical Observations pilot and the Coastal Dynamic pilot, the FAIR-EASE partners would like to highlight both the synergy and the new emerging interdisciplinary collaborations and progresses that can be achieved in the framework of such a European project promoting FAIR principles. Indeed,* The Volcano Space Observatory Pilot supports the implementation of innovative web services (notably here the open access VOLCPLUME web platform) displaying a broad range of satellite and ground-based data relevant to the characterization of volcanic gas and particle properties for the near real-time monitoring of volcanic activity and atmospheric hazards.* The Ocean Biogeochemical (BGC) Observations aims to provide a common QA/QC (Quality Assessment /Quality Control) platform to the whole BGC community to enhance the BGC data quality and address fundamental scientific questions. * The webODV software, part of the Coastal Water Dynamic pilot tools, allows to display and superimpose very heterogeneous datasets (i.e. satellite surface data vs. in situ profiles data, climatology vs. in situ profiles data, observations vs. model simulations in general).Taking as a starting point, the eruption of the Hunga Tonga-Hunga Ha’apai volcano on January 15, 2022, and the availability of various satellite observations of volcanic plumes and ocean surface properties together with in situ Argo (Argo is an international program that collects information from inside the ocean using a fleet of robotic instruments that drift with the ocean currents) floats measuring BGC variables such as the chlorophyll-a and suspended particles in the eruption area, FAIR-EASE partners aim to investigate the potential impacts of such a major stratospheric eruptions a record breaking eruption in the satellite era, on the marine ecosystem. Volcano and BGC community expertise as well as tools developed and pooled on Galaxy Europe platform (Galaxy is an open-source Virtual Research Environment) during the FAIR-EASE project support scientists in their investigation.

Oxygen, measured using optical sensors, was the first biogeochemical parameter recorded by Argo floats. The Argo program, now renamed OneArgo to take account of the ocean's biogeochemical (BGC) and deep components, now counts over 300,000 dissolved oxygen concentration profiles. This number of profiles makes the OneArgo program a key player in characterizing the biogeochemical state of the ocean. Among the biogeochemical parameters on floats, endorsed by the International Oceanographic Commission (IOC), oxygen can be used to quantify, for example, the Net Community Production and when monitored at large scales, it helps in understanding the extent of the Oxygen Minimum Zone (OMZ) and the deoxygenation of the ocean. Moreover, it is widely used in the calibration processes of other key parameters (Maurer et al., 2021) measured on floats such as the nitrate concentration and pH. OneArgo is built around autonomous robots, which implies specific constraints on data processing (Qualification, Validation... ) despite efforts to recover floats, post-deployment calibration to enhance sensor characterization and data quality remains rare. We would like to present the work lead in the European Data Assembly Center (DAC) Coriolis, in order to provide an operationally and consistent dissolved oxygen concentration profiles dataset, addressing Real Time (RT) and Delayed Mode (DM) processing for a wide range of sensors and float technologies.

The Earth System is a complex and dynamic system that encompasses the interactions between the atmosphere, oceans, land, and biosphere. Understanding and analyzing data from the Earth System Model (ESM) is essential, for example to predict and mitigate the impacts of climate change. Today, collaborative efforts among scientists across diverse fields are increasingly urgent. The FAIR-EASE project aims to build an interdomain digital architecture for integrated and collaborative use of environmental data. Galaxy is a main component of this architecture which will be used by several domains of study chose by FAIR-EASE. Galaxy, an open-source web platform, provides users with an easy and FAIR tool to access and handle multidisciplinary environmental data. By design, Galaxy manages data analyses by sharing and publishing all involved items like inputs, results, workflows, and visualisations, ensuring reproducibility by capturing the necessary information to repeat and understand data analyses. From this point on, a Pangeo environment is a tool more than relevant to be used alongside earth-system related data and processing tools in order to create cross domain analyses. The good news is that a Pangeo environment is accessible on Galaxy. It can be exploited as a jupyterlab and allows the user to manage their NetCDF data in a Pangeo environment with the use of notebooks. Multiple tutorials are available on the Galaxy Training Network to learn how to use Pangeo. The Galaxy Training Network significantly contributes to enhancing the accessibility and reusability of tools and workflows. The Galaxy Training platform hosts an extensive collection of tutorials. These tutorials serve as valuable resources for individuals seeking to learn how to navigate Galaxy, employ specific functionalities like Interactive Tools or how to execute workflows for specific analyses. In synthetisis, Pangeo in Galaxy provide Pangeo users with an up-to-date data analysis platform ensuring reproducibility and mixing trainings and tools. On the Earth System side, a first step was the creation of a Galaxy declination for Earth System studies (earth-system.usegalaxy.eu) with dedicated data, models, processing, visualisations and tutorials. It will make Earth System modeling more accessible to researchers in different fields. In this Galaxy subdomain we choose to have the Pangeo tools. Our hope is to be able to implement cross domain workflows including climate and earth system sciences. During this session our aim is to present how you can use the Pangeo environment from the Galaxy Earth System.

Easy and fast access to reliable, long-term, and high-quality environmental data is fundamental for advancing our scientific understanding of the Earth system, including its complex feedback mechanisms, as well as for developing mitigation and adaptation strategies, for fact-based decision-making, and for the development of environment-friendly innovations. In response to the continuously growing demand for environmental scientific knowledge, the ESFRI-listed environmental research infrastructures (ENVRIs/RIs) in Europe have formed a strong community of principal producers and providers of environmental research data and services from the four subdomains of the Earth system (Atmosphere, Marine, Solid Earth and Biodiversity/Ecosystems) through the cluster projects ENVRI (2011-2014), ENVRIplus (2015-2019), and ENVRI-FAIR (2019-2023). The further integration of ENVRIs across the subdomains is considered critical for leveraging the full potential of the ENVRI cluster for integrated environmental research. This step will be taken by ENVRI-Hub NEXT. To transform the challenging task of integrated Earth observation into a concept towards a global climate observation system, the World Meteorological Organisation (WMO) has specified a set of Essential Climate Variables (ECV) relevant for the continuous monitoring of the state of the climate. ECV datasets provide the empirical evidence needed to understand and predict the evolution of climate, guide mitigation and adaptation measures, assess risks, enable attribution of climatic events to the underlying causes, and underpin climate services. ENVRIs are critical for monitoring and understanding changes in ECVs, as has been identified by the ESFRI Strategy Working Group on Environment in their recent Landscape Analysis of the Environment Domain. The recently finished cluster project ENVRI-FAIR has launched an open access hub for interdisciplinary environmental research assets utilising the European Open Science Cloud (EOSC). The ENVRI-Hub is designed as a federated system to harmonise subdomain- or RI-specific access platforms and offers a user-centered platform that simplifies the complexity and diversity of the ENVRI landscape while preserving the structure of the individual RIs needed to fulfil the requirements of their designated communities. Building on the ENVRI-Hub, ENVRI-Hub NEXT aims at creating a robust conceptual and technical framework that will empower the ENVRI Science Cluster to provide interdisciplinary services that enable cross-RI exploitation of data, guided by the science-based framework of ECVs. This presentation will summarise the status of the ENVRI-HUB and the plans for ENVRI HUB-NEXT. Acknowledgement: ENVRI-HUB-NEXT has received funding from the European Union’s Horizon Europe Framework Programme under grant agreement No 101131141. ENVRI-FAIR has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824068 101131141. This work is only possible with the collaboration of the ENVRI-HUB-NEXT partners and thanks to the joint efforts of the whole ENVRI-Hub team.

The marine subdomain consists of a diverse data landscape, with several Research Infrastructures (RIs) involved. In the ENVRI-FAIR project the marine domain is represented by Euro-ARGO, ICOS (Marine), EMSO, and LifeWatch (Marine) as RIs as listed on the ESFRI roadmap, and SeaDataNet as European marine data management infrastructure. The overarching goal of ENVRI-FAIR is that all participating research infrastructures (RIs) will improve their level of FAIRness and become ready for connecting their data repositories and services to the European Open Science Cloud (EOSC).To achieve this goal, the marine domain partners have first analysed and assessed the FAIRNess level of each participating RI and identified the necessary actions to improve their individual FAIRness. They then created a roadmap and implementation plan that led to the development of an Essential Ocean Variable (EOV) demonstrator, highlighting the FAIRness achievements. In this presentation we will discuss in more detail the RI FAIR assessment and analysis process and show how it evolved alongside the evolution of the FAIR assessment tools themselves and the harmonisation required to be meaningful and useful. We will then walk you through the analysis of this assessment that led to a list of strengths and weaknesses per RI, and the solutions to overcome the weaknesses for each individual of the FAIR principle. Finally, we will present the outcomes of the required upgrades, adoptions of standards, improvements, developments and services that were developed as part of the implementation plan and led to the construction of the EOV demonstrator product.

This Science Project (SP) contributes to the estimation of the impacts of the invasive species on the European Biodiversity and Ecosystems. This topic is important for European Green Deal and the new European Biodiversity Strategy. The SP is also linked with the socio-economic issues because of the NIS implications to the local ecosystems and their services, and their societal goods and services. Since many of the above impacts may be of local scale, they may alter common practices in circular economies. The SP is implemented by: (a) Combining different sources of data and information; (b) Using a dual workflow to analyse the data; (c) Integrating its resources with core EOSC services and potentially horizontal services available; (d) Engaging the relevant scientific communities. The users will be able to: (a) Analyse distribution patterns of invasive species from different sources of data; (b) Compare the above patterns; (c) Provide managerial suggestions to relevant authorities; (d) Build on the existing infrastructure to address more complex questions (e.g. future scenarios).

European Environmental Research Infrastructures (ENVRIs) on the ESFRI level are core facilities for providing data, research products and services from the four subdomains of Earth system science – Atmosphere, Marine, Solid Earth, and Biodiversity/Terrestrial Ecosystems. The ENVRI Cluster represents the core component of the European environmental research infrastructure landscape, with the ENVRI community as their common forum for collaboration and co-creation. The topics covered by the ENVRIs span the entire range of scientific objectives relevant for Earth system monitoring.The community has developed the ENVRI-Hub as a central platform for accessing interdisciplinary FAIRfied environmental research assets, serving as an essential ENVRI community's interface to the European Open Science Cloud (EOSC). Through the ENVRI-Hub, the ENVRI community shares their FAIRness experience, technologies, and training as well as research products and services. The architecture and functionalities of the ENVRI-Hub are driven by scientific applications, use cases and user needs. Its three main pillars are the ENVRI Knowledge Base as the human interface to the ENVRI ecosystem, the ENVRI Catalogue of Services as the machine-actionable interface to the ENVRI ecosystem, and finally, subdomain and cross-domain scientific use cases as demonstrators for the capabilities of service provision among ENVRIs and across Science Clusters.The Science Demonstrators are being developed by several RIs in parallel. They are the key product to express the ENVRI-Hub’s potential regarding easy access to metadata and services, data discovery, as well as the promotion of interoperability in science across sub-domains. Science Demonstrators are built with Jupyter Notebooks - an open-source web application that allows one to create and share documents that contain live code, equations, visualizations, and narrative text. Uses include cross domain data access, data cleaning and transformation, numerical simulation, statistical modelling, data visualization, machine learning, and much more. The Jupyter Notebook environment forms the nucleus of the future ENVRI Virtual Research Environment.The ENVRI Science Demonstrators and Science Projects in the Horizon 2020 project EOSC Future aim at demonstrating how joint projects can address major challenges for Europe’s societies and how research infrastructures can support Horizon Europe’s missions within the EOSC. Presented Science Demonstrators cover one ENV domain wide service on the collocation of sampling sites, and two science cases from atmospheric and marine research, respectively.Acknowledgement: ENVRI-FAIR has received funding from the EU Horizon 2020 research and innovation programme under grant agreement No 824068. Part of the work is funded by the EU Horizon 2020 project EOSC Future under grant agreement No 101017536. This work is only possible with the collaboration of the ENVRI-FAIR partners and thanks to the joint efforts of the whole ENVRI-Hub team.

A review of the existing reporting tools about Regional Ocean Observing Systems and perspective toward future European Ocean Observing System monitoring and reporting services.

Quality of data services is crucial for operational large-scale internet-of-things (IoT) research data infrastructure, in particular when serving large amounts of distributed users. Effectively detecting runtime anomalies and diagnosing their root cause helps to defend against adversarial attacks, thereby essentially boosting system security and robustness of the IoT infrastructure services. However, conventional anomaly detection methods are inadequate when facing the dynamic complexities of these systems. In contrast, supervised machine learning methods are unable to exploit large amounts of data due to the unavailability of labeled data. This paper leverages popular GAN-based generative models and end-to-end one-class classification to improve unsupervised anomaly detection. A novel heterogeneous BiGAN-based anomaly detection model Heterogeneous Temporal Anomaly-reconstruction GAN (HTA-GAN) is proposed to make better use of a one-class classifier and a novel anomaly scoring function. The Generator-Encoder-Discriminator BiGAN structure can lead to practical anomaly score computation and temporal feature capturing. We empirically compare the proposed approach with several state-of-the-art anomaly detection methods on real-world datasets, anomaly benchmarks and synthetic datasets. The results show that HTA-GAN outperforms its competitors and demonstrates better robustness.

The ocean observing system needs to be ensured by high-level integration and coordination to guarantee its longterm sustainability, efficient accessibility and usability by a wide range of users. Enormous advancements and efforts toward these objectives have been already conducted in Europe, partly through the activities of the IOC-UNESCO's International Oceanographic Data and Information Exchange (IODE) and EuroGOOS DATAMEQ working group, although there is still room for additional progress and gaps to be addressed. During the past two decades, a series of standards for data and metadata formats as well as exchange protocols have been established within the marine community where projects, organizations and data integrators like JCOMM, RDA (Research Data Alliance), EuroGOOS, EMODnet, SeaDataNet and Copernicus played a significant role. Taking into consideration that harmonized data are a key element in maintaining a usable and interoperable ocean observing system, this paper aims to provide some recommendations for the harmonization of the marine in situ networks involved in EuroSEA, which would be a useful product for the European data integrators, particularly EMODnet, SeaDataNet and Copernicus Marine service. This document proposes recommendations to enhance the in situ networks based on the assessment of what has been previously done.

In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO 2 DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO 2 DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO 2 DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO 2 DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O 2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O 2 will improve our understanding of the ocean O 2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO 2 DAT will allow scientists to fully harness the increasing volumes of O 2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO 2 DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO 2 DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).

In the past two decades, the Argo Program has collected, processed and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed.

Research Infrastructures (RIs) are large-scale facilities encompassing instruments, resources, data and services used by the scientific community to conduct high-level research in their respective fields. The development and integration of marine environmental RIs as European Research Vessel Operators [ERVO] (2020) is the response of the European Commission (EC) to global marine challenges through research, technological development and innovation. These infrastructures (EMSO ERIC, Euro-Argo ERIC, ICOS-ERIC Marine, LifeWatch ERIC, and EMBRC-ERIC) include specialized vessels, fixed-point monitoring systems, Lagrangian floats, test facilities, genomics observatories, bio-sensing, and Virtual Research Environments (VREs), among others. Marine ecosystems are vital for life on Earth. Global climate change is progressing rapidly, and geo-hazards, such as earthquakes, volcanic eruptions, and tsunamis, cause large losses of human life and have massive worldwide socio-economic impacts. Enhancing our marine environmental monitoring and prediction capabilities will increase our ability to respond adequately to major challenges and efficiently. Collaboration among European marine RIs aligns with and has contributed to the OceanObs’19 Conference statement and the objectives of the UN Decade of Ocean Science for Sustainable Development (2021–2030). This collaboration actively participates and supports concrete actions to increase the quality and quantity of more integrated and sustained observations in the ocean worldwide. From an innovation perspective, the next decade will increasingly count on marine RIs to support the development of new technologies and their validation in the field, increasing market uptake and produce a shift in observing capabilities and strategies.