We welcome contributions on the following themes:
- User-Centric Infrastructure Development: This includes user stories, storylines and use cases that demonstrate the importance of cross-disciplinary and cross-scale data usage, as well as innovative infrastructure concepts designed to meet specific user needs. This includes methods for developing high-quality user interfaces and portals.
- Interdisciplinary data fusion and stakeholder engagement: Contributions are welcome that address how RDIs and data centers can facilitate the seamless integration of diverse ESS data to tackle complex societal challenges. This includes exploring interdisciplinary data fusion techniques, strategies for engaging different stakeholders and approaches for integrating stakeholder knowledge into RDI development and data management practices.
- Sustainable software solutions and interoperability: This theme focuses on approaches to building and reusing sustainable software solutions that meet the diverse needs of ESS researchers, including interoperability challenges between different data sources and platforms, and considering appropriate building blocks. It also includes discussion of operation and sustainability models for diverse ESS data centers and strategies for fostering cooperation and interoperability.
- Transdisciplinary research and public engagement: We encourage contributions that explore how RDIs can support transdisciplinary research on sustainability challenges (e.g., climate change and its impacts, etc.) and facilitate public engagement with ESS issues through initiatives such as citizen science.
- Fostering cultural change and collaboration: This theme focuses on strategies for promoting cultural change within research communities to encourage data sharing, collaboration, and the adoption of FAIR principles. This also includes approaches to international collaboration and the development of effective collaboration patterns.
Modern research environments are becoming increasingly complex, driven by the explosion of data volume and variety, the demands of interdisciplinary collaboration, and the proliferation of competing standards and emerging technologies. Adding to this complexity is a dramatic shift in the user community: a new generation of researchers with distinct skillsets, needs, and expectations has replaced the users for whom many Research Data Infrastructures (RDIs) were originally designed. The transition from an infrastructure-centric approach to a data-driven paradigm has created new challenges and opportunities that we are only beginning to fully understand.
This presentation follows the journey of Dr. Reese Arch (got it?), a fictional researcher tackling the challenge of integrating marine biodiversity and atmospheric datasets to model ecosystem responses to climate change. Through Reese’s experience, we explore how ENVRIs, ENVRI Hub, Virtual Research Environments (VREs), and tools can empower researchers while highlighting the barriers that still exist. Reese’s story captures the realities of modern science: successes like FAIR-compliant tools and semantic alignment, and frustrations such as overly complex workflows, and siloed systems.
A dedicated "Complaint Box" captures the key pain points voiced by researchers, from tool integration challenges to the cognitive load of navigating fragmented infrastructures. These frustrations highlight the gap between user needs and existing solutions, underscoring the importance of co-designed tools and community-driven innovation.
The narrative emphasizes how ENVRI is addressing these challenges by fostering interoperability, streamlining workflows, and empowering researchers through tailored VREs and support networks. Dr. Reese’s journey serves as a mirror for the research community, showcasing both the progress made and the need for collective action to bridge gaps in next-generation research infrastructures.
Join us to explore how ENVRI is turning the increasing complexity of research into an opportunity to create an interconnected, sustainable RDI ecosystem where interdisciplinary science thrives.
How to cite: Hienola, A., Petzold, A., and Bundke, U.: A Researcher’s Journey: Navigating Interdisciplinary Science with ENVRI RDIs and Tools, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6121, https://doi.org/10.5194/egusphere-egu25-6121, 2025.
NASA has a long history of collecting and openly sharing scientific data to help users better understand the sun, the Earth, the solar system and the universe. Over 40 repositories across five broad scientific disciplines work to archive, manage and care for these valuable NASA assets. To improve interdisciplinary and transdisciplinary science, NASA has developed a scientific data and information governance strategy. The strategy focuses on collaborative approaches to build a more connected and cooperative stewardship community while recognizing the diversity of domain specific data needs. In this presentation, we will share NASA’s vision for connected scientific data and information governance in addition to findings and lessons learned from the 2024 Open Source Science Data Repositories Workshop.
How to cite: Bugbee, K., Smith, D., Ringuette, R., Downs, R., Morgan, T., Berrios, D., Gebre, S., Angelini, L., Hughes, S., Desai, V., Young, A., and Haley, C.: Enhancing Collaboration Across NASA’s Science Repositories and Stakeholders: Findings From the 2024 Data Repositories Workshop, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1664, https://doi.org/10.5194/egusphere-egu25-1664, 2025.
The study of the Earth system involves a wide range of disciplines that are increasingly collaborate to address global challenges like climate change. In France, Data Terra, the national e-infrastructure supports this effort by managing data for five key Earth system components: Ocean, Atmosphere, Solid Earth, Continental Surface, and Biodiversity. Alongside distributed infrastructure services, Data Terra provides discovery, access, and dissemination tools to enable researchers to effectively conduct their scientific investigations. Among these resources, EarthPortal, a FAIR-compliant semantic artefact catalogue, promotes the use of controlled vocabularies and ontologies, enhancing semantic interoperability across Earth sciences disciplines.
Developed within the EOSC FAIR-IMPACT project using OntoPortal technology, EarthPortal aligns with European and national recommendations for sharing and reusing semantic artefacts in interdisciplinary research contexts. EarthPortal is a thematic catalogue and semantic repository specifically tailored for Earth and environmental sciences, hosting artefacts like SKOS-controlled vocabularies and OWL ontologies, organized into categories and thematic groups with filtering options. Beyond providing access to semantic artefacts, EarthPortal offers advanced tools to support third-party applications. Key functionalities include (i) the annotator, which suggests relevant terms based on textual or keyword input ; (ii) the recommender, which identifies pertinent semantic artefacts corresponding to the provided input ; and (iii) the mappings tool, which generates, stores, and visualizes relationships between different semantic artefacts. Through its REST API, EarthPortal facilitates seamless integration with external applications, enabling users to access semantic artefacts and leverage these tools directly within their workflows.
This presentation highlights EarthPortal’s functionalities including its user interface and API capabilities. Using a concrete application example, we will demonstrate how the tool enhances the semantic interoperability of data. Specifically, we will illustrate the integration of EarthPortal with EaSy Data, the French data repository for Earth and environmental sciences. This connection enriches metadata with semantic annotations, improving discoverability and user experience.
Additionally, we will explore new developments, including the federation of EarthPortal with other OntoPortal Alliance platforms (e.g., BiodivPortal, AgroPortal) to enable cross-domain interoperability by facilitating the discovery of semantic artefacts across domains, and providing users with a unified interface to access diverse thematic resources. Finally, we will outline future developments, including the creation of a generic connector for the GeoNetwork catalogue, which will allow the direct use of EarthPortal's semantic artefacts and tools, enhancing metadata editing, search functionalities and data harvesting processes.
How to cite: Pierkot, C. and Alviset, G.: Enhancing Semantic Interoperability in Earth System Sciences: TheRole of EarthPortal, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2760, https://doi.org/10.5194/egusphere-egu25-2760, 2025.
In the pursuit of making data FAIR (Findable, Accessible, Interoperable, Reusable)1, datasets need to be well-described to enable both human and machine users to maximize the benefits towards knowledge discovery and innovation. Self-describing data enriched with metadata are essential to facilitate interoperability and reusability. Within the Earth System Science (ESS) community, the NetCDF data format has become the quasi-standard for storing multidimensional data, supported by general metadata standards such as the CF conventions (Climate and Forecast)2, the Attribute Convention for Data Discovery (ACDD)3 for global attributes and more specific ones like the AtMoDat project4 for atmospheric modeling.
NetCDF files can be self-describing if they contain all relevant metadata. In practice, NetCDF metadata is frequently incompatible because they are either non-standardized or not as detailed as required for repositories or data portals. We aim to address these discrepancies by establishing a standardized NetCDF data workflow that ensures the seamless integration of NetCDF data into downstream processes and enables the extraction of metadata by downstream applications.
The NetCDF Metadata Guideline Initiative is a collaborative effort from researchers, research data management, research data infrastructure and metadata experts from several research centers across Germany. We are supported by the Helmholtz DataHub, the central data infrastructure of the Research Field Earth and Environment within the Helmholtz Association. This initiative aims to develop harmonized data handling guidelines to unify the diverse sub-communities within both observational and modeling fields, building towards a unified and consistent infrastructure for environmental research data.
Our approach includes examining existing guidelines, followed by their integration and expansion to address diverse needs within Earth and Environment disciplines. We will produce a set of comprehensive guidelines designed to enhance data interoperability and reusability, along with tools to facilitate their adoption.
Key milestones include:
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Reconciling attributes in former guidelines.
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Implementation of a collaborative and public guidelines document.
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Development of machine-readable templates and validation tools.
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Provision of highly user-friendly tools that support scientists when entering metadata profiles based on the guidelines.
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Integration of our enhanced NetCDF-profiles into selected downstream clients like the Earth Data Portal (EDP)5.
By harmonizing metadata practices, we aim to enhance the interoperability and accessibility of geoscientific data, facilitating more efficient data sharing and utilization across research domains.
The implementation of standardized metadata practices for NetCDF across the ESS communities, would enable data repositories such as PANGAEA® Data Publisher and the World Data Center for Climate (WDCC) to present metadata in compliance with established norms and integrate it into their specific schemas.
This presentation will outline the key challenges identified, the proposed solutions, and the anticipated impact on the geoscientific community. With this presentation we call for participation in this evolving initiative to create a common NetCDF metadata foundation.
1 Wilkinson et al., 2016: https://doi.org/10.1038/sdata.2016.18
2 https://cfconventions.org/
3 https://wiki.esipfed.org/Attribute_Convention_for_Data_Discovery_1-3
4 https://www.atmodat.de/
5 https://earth-data.de
How to cite: Saß, B. L., Fösig, R., Söding, E., Lorenz, C., Barthlott, S., Sommer, P. S., Meyer, E. M. I., Geyer, B., Loup, U., Rebmann, C., Loewe, K., Haßler, S. K., Obersteiner, F., Kerzenmacher, T., Schäfer, A., Kottmeier, D., Getzlaff, K., and Pörsch, A.: Harmonizing NetCDF Metadata Workflows: A Collaborative Initiative for Enhanced Data Integration and Reusability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6484, https://doi.org/10.5194/egusphere-egu25-6484, 2025.
The integration of scientific data across disciplines and stakeholders is crucial for advancing Earth system sciences (ESS) and ensuring data accessibility and usability. One of the primary challenges in this context is the terminological diversity found within different scientific fields, as well as between stakeholders with varying levels of expertise. Standardized metadata and effective metadata (MD) mappings are essential tools for overcoming this challenge, serving as a "translation" layer that enhances the visibility and usability of ESS data across language barriers and scientific domains. In our contribution we highlight the BITS project as a pioneering pilot initiative aimed at the integration of terminologies and services within ESS, with a focus on standardizing metadata and improving data interoperability. The project leverages key frameworks such as provided by NFDI4Earth, base4NFDI, and TS4NFDI, ensuring alignment with international best practices in data integration and sharing. By examining the role of standardized metadata in connecting diverse ESS stakeholders, we demonstrate how terminological harmonization and service integration can bridge disciplinary gaps, enhancing the accessibility, discoverability, and collaborative potential of ESS data. This opens new opportunities for data centers to contribute with their data to transdisciplinary research on sustainability challenges.
How to cite: Lammert, A., Martens, C., Löhden, A., and Anders, I.: Overcoming the challenges of terminological diversity within different scientific fields to enhance the accessibility, discoverability, and collaborative potential of ESS data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8663, https://doi.org/10.5194/egusphere-egu25-8663, 2025.
The Qinghai-Xizang Plateau, esteemed as the World’s Third Pole, plays a pivotal role on the global stage, shaping climate rhythms, safeguarding water supplies, and nurturing biodiversity across the Asian continent and beyond. Decoding the complex interplay within the Third Pole’s lithosphere, hydrosphere, cryosphere, biosphere, atmosphere, and anthroposphere hinges on the availability of scientific data. As a cornerstone of research in one of the world’s most critical ecosystems, The National Tibetan Plateau/Third Pole Environment Data Center (TPDC, https://data.tpdc.ac.cn) goes beyond traditional data governance by implementing innovative strategies for data sharing, accessibility, and interoperability. This approach not only accelerates the pace of scientific discovery but also fosters a collaborative environment where researchers from around the globe can contribute to our understanding of the complex interactions within the Earth’s systems, ultimately leading to more effective conservation and management of our planet’s resources.
TPDC stands as one of the pioneering 20 national data centers backed by China’s Ministry of Science and Technology since 2019. TPDC is steadfast in its mission to aggregate and harmonize a wealth of data resources concerning the Tibetan Plateau. Boasting the most comprehensive scientific dataset for the Third Pole and its adjacent areas, TPDC curates over 6,600 datasets spanning a multitude of fields, from terrestrial studies to human-environment interactions, atmospheric research, geology, cryospheric science, remote sensing, paleoenvironmental analysis, and more.
TPDC furnishes a cloud-based infrastructure that streamlines online data procurement, quality assurance, analysis, and visualization, thereby enhancing the accessibility of shared data. Adhering to the FAIR principles—findable, accessible, interoperable, and reusable—TPDC forges strategic alliances with international entities. It partners with the WMO to advance the Global Cryosphere Watch initiative and engages with ICIMOD on data swap, observational capabilities, skill development, and collaborative studies. As a preferred data repository for leading international journals like Nature, AGU, ESSD, and Elsevier, TPDC encourages researchers to publish their data in conjunction with scholarly articles. Furthermore, TPDC extends its data expertise to a host of international scientific endeavors, including TPE, GEWEX/GASS LS4P, and WCRP-CORDEX CPTP, bolstering the pursuit of knowledge for the World’s Third Pole." By the subcenter Qinghai and Xizang, TPDC also contribute to the regional sustainability.
In recent years, the TPDC team has made substantial contributions to data management and sharing within Earth system science. Their work, published in renowned journals such as Nature Geoscience, Nature Reviews Earth & Environment, Reviews of Geophysics, and Science Bulletin, underscores the critical need to advance data-sharing policies, enhance data assimilation techniques, and foster international collaboration. The team advocates for stronger policy, technological, and managerial actions to promote data sharing, stimulate scientific cooperation, and support the creation of a Digital Twin of Earth. Additionally, their research highlights the integration of advanced AI technologies and big data assimilation to tackle complex challenges in Earth system science, driving paradigm shifts from data-intensive science to robot scientists. Also they establish security mechanism for the security.Collectively, their efforts provide a robust framework for improving data governance, accelerating scientific progress, and enhancing global cooperation in Earth data sharing.
How to cite: Pan, X., Li, X., Feng, M., Nie, X., and Guo, X.: Data Governance and Beyond: TPDC’s Role in Advancing Earth System Science, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3434, https://doi.org/10.5194/egusphere-egu25-3434, 2025.
At the Leibniz Supercomputing Centre (LRZ) of the Bavarian Academy of Sciences and Humanities, we have set up a portal and system to publish large datasets from simulations, assign DOIs, and present landing pages. This "LRZ FAIR Data Portal" - currently in demonstrator status - is based on InvenioRDM, with the idea of using this framework as a presentation layer. The login and data-upload possibilities typical for repositories are disabled in this setup. Instead, the portal presents metadata together with a dataset-specific link to the GLOBUS (www.globus.org) data-transfer service, where LRZ is connected. By getting themselves a GLOBUS login for free, users can thus reliably copy the data to many other supercomputing centres or download them to their laptop. This system shall make datasets FAIR (Findable, Accessible, Interoperable, Reusable) that are produced at LRZ and are too large to be moved to institutional, community, or general-purpose research-data repositories.
We are currently developing a mechanism to automatically ingest metadata from LRZ storage systems into InvenioRDM. The idea of this mechanism is that users who wish to publish their data store metadata in a DataCite-centric format, and our mechanism scans these user's volumes for metadata to be published. The datasets are thus automatically presented in the portal. The necessary workflows are harmonized and developed with the partners from the Gauss Centre of Supercomputing (HLRS, JSC as the two other largest German supercomputing centres) within the InHPC-DE project. The InvenioRDM instance also provides an OAI-PMH interface, enabling the harvesting of metadata. This allows datasets stored with us to be discoverable in other services, such as earth-data.de. A corresponding exporter that filters datasets according to the Dewey Decimal Classification has been developed as part of the NFDI4Earth project (see NFDI4Earth Knowledge Hub: knowledgehub.nfdi4earth.de).
In the current demonstrator status of our LRZ FAIR Data Portal, the portal and a preliminary push mechanism are used for the publication of the first "friendly-user" datasets. In particular, an ERA5-based downscaled meteorological data suite (3 km resolution, 40 years timespan) has been published via the portal. We report on the experience publishing this dataset, and also further ESS-related datasets from other projects we are working on. The advantages and limitations of the approach are discussed in relation to our concept of a general-purpose data publication mechanism for huge datasets produced at a supercomputing centre. We also shed some light on differences and potential of domain-specific publication mechanisms (including the terrabyte satellite-data platform at LRZ), highlighting how shortcomings of publication approaches can be addressed and opportunities leveraged.
How to cite: Munke, J., Wellmann, A., Muralidharan, M., Henzen, C., and Hachinger, S.: ESS Data Publication at a "General-Purpose" Supercomputing Centre, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3315, https://doi.org/10.5194/egusphere-egu25-3315, 2025.
The Open Geospatial Consortium (OGC) API standards offer a modern approach to accessing geospatial data and services on the web, promoting interoperability and simplicity. These standards, developed by the OGC, improve upon older OGC standards by embracing web-centric practices and resource-oriented designs. They use a RESTful architecture, enabling developers to interact with geospatial resources through standardized HTTP mechanisms and JSON encoding, ensuring ease of integration, discoverability, and scalability.
The OGC API family comprises several key standards, each tailored for specific functionalities. Notable examples include OGC API - Features, succeeding the Web Feature Service (WFS); OGC API - Maps, succeeding the Web Mapping Service (WMS); and OGC API - Coverages, succeeding the Web Coverage Service (WCS). Together, they address a wide range of geospatial data types, creating a robust framework for interoperable geospatial applications.
However, a direct successor to SensorWeb standards, such as the Sensor Observation Service (SOS) or Sensor Planning Service (SPS), was missing from the OGC API suite. The SensorThingsAPI, developed earlier, follows a different architectural model. To address this gap, the OGC Connected Systems Standards Working Group (SWG) introduced a draft specification for the OGC API - Connected Systems. This standard focuses on managing descriptions of sensor systems, networks, and their data, building on established models such as the Sensor Model Language (SensorML), SWE Common, and Observations, Measurements, and Samples (OMS). It also aligns with contemporary standards like the Semantic Sensor Network Ontology (SOSA/SSN).
The OGC API - Connected Systems draft consists of two parts. Part 1 extends the OGC API - Features standard to manage static resources, such as systems, procedures, deployments, and sampling features. Systems encompass entities such as sensors, platforms, actuators, and processing components that produce data or receive commands. Procedures define the processes undertaken by systems, while deployments detail where and when systems are used. Sampling features represent real-world objects observed by systems. This part supports various data formats, allowing for both rich metadata descriptions in SensorML and simpler representations such as GeoJSON.
Part 2 addresses dynamic data, including datastreams of observations, control channels for sending commands to systems, and historical data on system events. Datastreams enable flexible grouping of observations, such as by sensor network or observed property. Control channels allow systems to receive commands, such as initiating measurements or altering states. Historical events, now managed as dedicated datastreams, avoid overloading system descriptions with excessive details.
The draft specification foresees integrating publish/subscribe patterns, such as MQTT, for managing data streams, control channels, and events.
With this contribution we aim to provide an insight into how the emerging OGC API - Connected Systems standard provides a modern successor to Sensor Web technologies. We discuss how this initiative empowers data managers and scientists to efficiently exchange observational data and metadata, ensuring compatibility and interoperability across diverse applications.
How to cite: Jirka, S., Autermann, C., and Speckamp, J.: The OGC API - Connected Systems: An emerging standard for interoperable sharing of observation data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12207, https://doi.org/10.5194/egusphere-egu25-12207, 2025.
SeaDataNet is a major pan-European infrastructure for managing and providing access to marine data sets and data products, acquired by European organisations from research cruises and other observational activities in European coastal marine waters, regional seas and the global ocean. Founding partners are National Oceanographic Data Centres (NODCs), major marine research institutes, and ICES. The SeaDataNet network, initiated in the nineties, expanded over time its network of data centres and infrastructure, during a series of dedicated EU RTD projects, and by engaging as core data management infrastructure and network in leading European Commission initiatives such as the European Marine Observation and Data network (EMODnet), Copernicus Marine Service (CMS), and the European Open Science Cloud (EOSC). These facilitated ongoing development and evolution of the SeaDataNet technical infrastructure, standards, tools, and services, while managing and further expanding a large network of connected data centres and data providers.
SeaDataNet develops, governs and promotes common standards, vocabularies, software tools, and services for marine data management, which are freely available from its portal and widely adopted and used by many communities and projects. A core SeaDataNet service is the CDI data discovery and access service which provides online unified discovery and access to vast resources of data sets, managed by 115+ connected SeaDataNet data centres from 34 countries around European seas, both from research and monitoring organisations. Currently, it gives access to more than 3 Million data sets, originating from 1000+ organisations in Europe, covering physical, geological, chemical, biological and geophysical data, and acquired in European waters and global oceans. Standard metadata and data formats are used, supported by an ever-increasing set of controlled vocabularies to mark up the metadata profiles in a semantically controlled way, resulting in rich and highly FAIR metadata and data sets. Services include online CDI catalogue, cloud-based data cache, and online shopping mechanism. FAIRness is further amplified by machine-to-machine services.
SeaDataNet provides core services in EMODnet Chemistry, Bathymetry, Physics, and Ingestion for bringing together and harmonizing large amounts of marine data sets, which are used by EMODnet groups for generating thematic data products. Examples: Digital Terrain Model for all European seas (Bathymetry), and European aggregated and validated data collections for eutrophication, contamination, and marine litter (Chemistry). These products are very popular and find their way to many users from government, research, industry, and public. SeaDataNet is also back-office for EMODnet Ingestion, reaching out and achieving input from data providers that are not (yet) participating in the European data exchange.
SeaDataNet is well engaged in EOSC projects, such as EOSC-FUTURE and the Blue-Cloud project. A pilot deployed a versatile cyber platform federating multidisciplinary data repositories, analytical tools, and computing facilities for exploring and demonstrating the potential of cloud based open science for ocean sustainability. A further evolution is underway into a Federated European Ecosystem and EOSC Blue Node to deliver FAIR & Open data and analytical services, instrumental for deepening research of oceans, coastal & inland waters. This is also highly important for the Digital Twins of the Oceans (DTO) initiative.
How to cite: Schaap, D. M. A., Iona, A., Piel, S., Vernet, M., Scory, S., Giorgetti, A., and Kokkinaki, A.: SeaDataNet, panEuropean infrastructure for marine and ocean data management and its relations with EMODnet, Blue-Cloud2026, and DTO, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4997, https://doi.org/10.5194/egusphere-egu25-4997, 2025.
In all scientific domains, there is a growing production of data from different sources which can be hard to replicate. To be scientifically valuable those data have to be preserved, accessed, and shared across researchers and communities following the FAIR principles.
EUDAT’s vision is that data should be shared and preserved across borders and disciplines and its mission is to enable data stewardship within and between European research communities through the Collaborative Data Infrastructure. To meet this vision, EUDAT offers a set of services for managing data. EUDAT is the largest pan-European data infrastructure and is conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europe’s largest scientific data and computing centres. Covering both access and deposit, from informal data sharing to long-term archiving, and addressing identification, discoverability and computability of both long-tail and big data, EUDAT services aim to address the full lifecycle of research data.
The services offered by EUDAT are designed to be generic and to support researchers from a variety of scientific domains at the different stages of the Data Life Cycle. These include the exchange of data with team members via B2DROP, publishing of datasets with the assignment of DOIs via B2SHARE, the long term preservation of data with replication across sites via B2SAFE, the persistent identification of the datasets with B2HANDLE and the discovery of datasets with B2FIND. Over the years, different earth and environmental sciences use cases (for example from SeaDataNet, TOAR, EPOS, ENES) have been integrating EUDAT services as major components of their scientific workflows.
As an example we can mention the work done in collaboration with ICOS Carbon Portal which aimed to extend the community platform into a benchmarking environment that controls the whole processing chain from selection and preparing the prior information datasets, running the models, followed by the benchmarking and analysis of the results. In order to achieve this EUDAT data services have been integrated in the ICOS workflow: B2SAFE for storing the data and staging them for analysis at computing platforms, data are assigned with persistent identifiers via the B2HANDLE service, and B2FIND harvests the ICOS Carbon portal for broader sharing of the data. The use case addresses all aspects from Findability, Accessibility, Interoperability, and Reproducibility principles, with a focus on reproducibility.
In this presentation, we will provide an overview of the EUDAT services suite and how the services can be integrated by the climate and earth science communities with the support of examples from current use cases. We will discuss with the participants to understand possible gaps in the service offering.
How to cite: Testi, D., Le Franc, Y., Van de Sanden, M., Apweiler, S., and Carrillo, R.: Data management services for earth and climate communities , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16801, https://doi.org/10.5194/egusphere-egu25-16801, 2025.
The ever-growing complexity of the multiple global challenges requires Earth System Sciences (ESS) to collaborate in interdisciplinary research and demands reliable and well-accessible research data as a foundation. NFDI4Earth, a consortium within the German National Research Data Infrastructure (NFDI), addresses these needs by empowering researchers to adopt FAIR principles, enabling the discovery, access, and use of ESS data provided by partners and other sources. Uniting 66 partner institutions in Germany - from universities and research organizations over public agencies to infrastructure providers - NFDI4Earth brings together a wide range of expertise in data management. This submission highlights (first) NFDI4Earth achievements after three years of NFDI-funding and reflects on lessons learned.
NFDI4Earth gives an active role to the ESS communities, allowing them to advance FAIRness in several ways. Through open calls for NFDI4Earth Pilots, Incubators and EduPilots the community was invited to formulate needs, innovative ideas for RDM and competence building in ESS. More than 40 projects were funded and led to a variety of data products, software solutions and educational resources, all openly available for reuse by researchers, covering a breadth of ESS subdisciplines. NFDI4Earth offered information, training, and outreach to the ESS community in various formats.
NFDI4Earth launched first prototype versions of new services: The User Support Network offers ESS-RDM-support and operates as a federated system across RDM-support-desks of the NFDI4Earth partner institutions. The Knowledge Hub builds the information backbone and offers metadata over a broad range of resources including datasets, learning resources, repositories, and software source code. The EduTrain Portal provides access to a range of curated open educational resources related to RDM in the ESS. Finally, the OneStop4All serves at the portal to allow discovering and easily accessing all the NFDI4Earth resources.
To further advance the implementation of FAIR principles NFDI4Earth started designing an overarching NFDI4Earth Architecture and developing the NFDI4Earth Label as a means of classifying ESS-related repositories. The NFD4Earth Label intends (1) to help researchers find the most suitable repositories for data access and data publication, and (2) provides repository operators with a self-assessment tool for documentation and evaluation. In parallel, the recent launch of the first version of the NFDI4Earth FAIRness and Openness Commitment invites individuals and organisations to declare their support to NFDI4Earth and their intent to promote the transition to FAIR RDM in the ESS.
To secure sustained operation and cooperation networks NFDI4Earth established close cooperation with important national public environmental data and geodata infrastructures. Relevant research communities have pledged to closely link their data infrastructures and service developments to NFDI4Earth. NFDI4Earth is internationally connected, notably through involvements in initiatives like the European Open Science Cloud (EOSC) and the Open Geospatial Consortium (OGC) contributing to the development, alignment, and adoption of global standards while fostering collaboration across borders.
NFDI4Earth is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project number: 460036893.
How to cite: Bernard, L. and the NFDI4Earth Consortium: First Achievements and Experiences from building NFDI4Earth - a National Research Data Infrastructure for Earth System Sciences, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12287, https://doi.org/10.5194/egusphere-egu25-12287, 2025.
The paradigm of FAIR (Findable, Accessible, Interoperable, Reusable) implies that due credit for scientific results can and will be provided when such results are properly referenced and cited in scientific literature. This applies also to open research code as part of scientific output.
This presentation provides a summary of a four year analysis for a cohort of open source software projects, and their DOI-based citation in scientific publications, based on metadata from Crossref (crossref.org). The results indicate that the mere availability of the required underlying technical infrastructure is a requirement for but does not suffice to ensure acceptance in science and common practice. In addition, organisational changes of best practices are needed, for software project communities, but also journals and publishers. Once all these factors are established, the results show positive trends of acceptance und usage across scientific communities, to reference fundamental open scientific software by Digital Object Identifers (DOI). For this study, a cohort of open source software projects was approached to mint DOI as an emerging good practice for a high visibility publication which was published in 2021 (Springer Handbook of Geographic Information, https://doi.org/10.1007/978-3-030-53125-6_30). The cohort comprised a representative range of open geospatial software projects of that time, including core libraries such a GDAL and PROJ, desktop GIS such as GRASS GIS, QGIS and gvSIG, but also infrastructure and web based applications like PostGIS, rasdaman and actinia, among others. The majority of the software project cohort is federated in the OSGeo Foundation (OSGeo.org). OSGeo membership requires for software projects to implement quality standards for project, code and community management, including the use of a software repository. For this,most of the projects use GitHub (github.com/osgeo), which allowed for automated software release deposit in the Zenodo Open Access repository (Zenodo.org), resulting in the minting of an initial concept DOI and further version DOI for following version releases by the software projects. In the following, the open digital infrastructure Crossref for persistent cross-platform citations linking in online academic journals was anually queried for citations related to the cohort, and additional OSGeo projects which elected to mint DOI independently. The current results show a modest use of DOI based citations for the majority of the cohort but a significant and growing citation footprint for core geospatial libraries such as PROJ (proj.org) and GDAL (gdal.org), which are used across all scientific fields. The DOI-based citations of GDAL registered by CrossRef show a continuing growth rate of over 100% anually since 2022. An additional outcome of the analysis is that for some Open Access publications, full metadata forwarding to Crossref, which is a requirement for DOI-based FAIR software citation, still remains to be implemented.
How to cite: Löwe, P.: Open Geospatial Software Citation: Status, Patterns and Trends – A Crossref-based data analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2872, https://doi.org/10.5194/egusphere-egu25-2872, 2025.
Understanding and managing the Earth System requires sustainable, interdisciplinary approaches to data accessibility, integration, and processing. To address these challenges, we present a modular and scalable digital ecosystem designed to enhance earth data science and support multidisciplinary applications [1]. Adhering to the FAIR data as well as the FAIR research software principles, the system employs standardized interfaces, and open-source technologies to foster collaboration across disciplines, extending beyond Earth System Sciences.
The ecosystem comprises three core components: (i) the Sensor Management System (SMS) for detailed metadata registration and management [2]; (ii) time.IO, a platform for efficient storage, transfer, and real-time visualization of time series data [3]; and (iii) the System for Automated Quality Control (SaQC), which ensures data integrity through automated data analysis and quality assurance [4,5]. Developed, maintained, and distributed as dedicated projects, these components integrate seamlessly into a coherent time series data management system. Leveraging widely adopted solutions and standards such as the OGC SensorThings API, OGC SensorML and the EUDAT B2INST persistent identifier, the system ensures compatibility and integration across research infrastructures, software systems, and diverse disciplines.
This cloud-ready and highly adaptable ecosystem supports deployments from small-scale local research projects to large-scale international environmental monitoring networks. It provides a user centric solution for storing, analyzing, and visualizing data. The use of established metadata standards and the community-driven development of metadata schemes and semantic annotations ensure consistency, interoperability, and reusability of metadata and data formats across various applications The applicability of the proposed ecosystem for use cases from Earth System Sciences and its usability across all stages of a typical sensor data lifecycle will be demonstrated using Cosmic Ray Neutron Sensing data as an illustrative example.
By aligning user needs with sustainable software solutions, this ecosystem facilitates FAIR-compliant practices, supports scientific innovation, and promotes robust, transparent research in Earth System sciences.
References:
[1] Bumberger, J., Abbrent, M., Brinckmann N., Hemmen, J., Kunkel, R., Lorenz, C., Lünenschloß, P., Palm, B., Schnicke, T., Schulz, C., van der Schaaf, H., and Schäfer, D. (2025). Digital Ecosystem for FAIR Time Series Data Management in Environmental System Science. SoftwareX (accepted)
[2] Brinckmann, N., Alhaj Taha, K., Kuhnert, T., Abbrent, M., Becker, W., Bohring, H., Breier, J., Bumberger, J., Ecker, D., Eder, T., Gransee, F., Hanisch, M., Lorenz, C., Moorthy, R., Nendel, L. J., Pongratz, E., Remmler, P., Rosin, V., Schaeffer, M., Schaldach, M., Schäfer, D., Sielaff, D., & Ziegner, N. (2024). Sensor management system - SMS (1.17.1). Zenodo. https://doi.org/10.5281/zenodo.13329925
[3] Schäfer, D., Abbrent, M., Gransee, F., Kuhnert, T., Hemmen, J., Nendel, L., Palm, B., Schaldach, M., Schulz, C., Schnicke, T., & Bumberger, J. (2023). timeIO - A fully integrated and comprehensive timeseries management system (0.1). Zenodo. https://doi.org/10.5281/zenodo.8354839
[4] Schmidt, L., Schäfer, D., Geller, J., Lünenschloss, P., Palm, B., Rinke, K., Rebmann, C., Rode, M., & Bumberger, J. (2023). System for automated Quality Control (SaQC) to enable traceable and reproducible data streams in environmental science. Environmental Modelling & Software, 105809. https://doi.org/10.1016/j.envsoft.2023.105809
[5] Schäfer, D., Palm, B., Lünenschloß, P., Schmidt, L., Schnicke, T., & Bumberger, J. (2024). System for automated Quality Control - SaQC (v2.6.0). Zenodo. https://doi.org/10.5281/zenodo.5888547
How to cite: Schäfer, D., Abbrent, M., Brinckmann, N., Gransee, F., Hemmen, J., Kuhnert, T., Kunkel, R., Lorenz, C., Lünenschloß, P., Palm, B., Schnicke, T., Schaaf, H. V. D., and Bumberger, J.: Digital Ecosystem for Time Series Data Management in Earth System Science, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13340, https://doi.org/10.5194/egusphere-egu25-13340, 2025.
Cloud computing has become essential in Earth System Sciences (ESS) due to the increasing volume of data and the necessity for cross-disciplinary collaboration. Over recent years, this has led to a fragmented landscape of cloud computing solutions, with no clear consolidation emerging. Consequently, users face a diverse range of options, often designed to achieve similar objectives. Despite a strong interest in shifting from traditional workflows to cloud-based processing, user surveys reveal that the transition is hindered by a steep learning curve, significant fragmentation, and particularly, a lack of interoperability among platforms, data, and workflows (Wagemann et al., 2021; DiLeo et al., 2024).
It is already difficult to get an overview of existing solutions in the realm of cloud-based research data infrastructures (RDI) which usually include tools for data providers, platforms, API’s, clients, software and file formats. As a user, finding a way to create meaningful and interoperable end-to-end workflows is even more challenging. Especially, since not all combinations of software, API’s and data are available on all RDIs. Various projects exist with the goal of consolidation of choices in cloud native ESS to increase interoperability and decrease complexity for users, e.g. from the European Space Agency (EOEPCA – Earth Observation Exploitation Platform Common Architecture, APEx – Application Propagation Environment) or the Open Geospatial Consortium (Testbed-20 GeoDataCube API, Open Science Persistent Demonstrator).
This contribution will show our experiences in providing user-friendly computing and ESS services in an agile approach in the above-mentioned projects and discuss the challenges, which begin in finding a common language, in standardizing, combining or harmonizing existing solutions.
How to cite: Zellner, P. and Eberle, J.: Usability in ESS Data Cubes and Cloud Computing: Challenges to Converge in a Landscape of Diverse Solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10662, https://doi.org/10.5194/egusphere-egu25-10662, 2025.
The reputation of data providers and the accuracy of geodata and data sources are critical factors for the trustworthiness of environmental metrics and indicators to support policy making. In this context, the possibility of user-specific assessment of the quality of input data for composite indicator calculations using data-fitness-for-use and data-fitness-for-purpose approaches has gained importance. Data-fitness-for-use criteria describe the general suitability of a data set for further use and thus refer to the intrinsic quality of the data such as completeness, accuracy, consistency, and timeliness. Data-fitness-for-purpose criteria are more context-dependent and emphasise the suitability of data for a specific application according to the suitability of the user's requirements.
This contribution first analyses spatiotemporally dynamic input datasets for the derivation of environmental indicators to determine whether they contain sufficient quality information to enrich the indicators with data quality information. We consider two crop-type classifications for the derivation of a biodiversity indicator and phenological and meteorological data for the derivation of an extreme weather indicator. The available information on the quality of the input data represents established key metrics for the production-oriented assessment of thematic accuracy. A prerequisite for their calculation are reference data that are accepted as true and which are often not available for geodata derivatives such as composite indicators. If reference data are not available, we show that such overall input data accuracy metrics are not sufficient to derive quality metrics for subsequent products, such as composite indicators, as they lack information on the spatial distribution of accuracy.
Secondly, the structure of an open framework is discussed that allows the extension of geospatial quality standards such as ISO 19157-1 (2023). There, production-orientated thematic accuracy sub-elements such as “classification correctness or “quantitative attribute accuracy” are already included. In contrast, the aspects of “usability” for geodata remain undefined due to their heterogeneous nature. As a possible key sub-element, we propose spatial uncertainty metrics as an additional data layer, often derived as a by-product of modelling, which can support usability assessments and the communication of local and spatially aggregated indicator uncertainties.
In conclusion, the approach presented focuses on data quality, usability and standardisation, which is closely related to the FAIR principles, and emphasises the importance of making geospatial data and environmental indicators more reusable. We believe that this approach can significantly increase the value and utility of research objects in the earth and environmental sciences and foster their reuse in the context of science policy frameworks. The packaging of research objects together with quality assessments in a lightweight container format such as RO-Crate and Annotated Research Context facilitates in addition the (semi-)autonomous processing of these data by machines and thus their AI Readiness.
ISO 19157-1 (2023). Geographic information: Data quality. International Organization for Standardization. Geneva, Switzerland. https://www.iso.org/standard/78900.html
How to cite: Möller, M., Weiland, C., and Martini, D.: Enhancing environmental indicator trustworthiness: A framework for user-specific quality assessment of spatial input data using data-fitness-for-purpose principles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17188, https://doi.org/10.5194/egusphere-egu25-17188, 2025.
The Anthropocene is the time in which humanity has a greater influence and impact on our planet than all natural forces combined. The dominant influence of human forces on our planet’s land, water and atmosphere has already overstepped biophysical planetary boundaries, and is threatening to increase and worsen its conditions if politics, society and economy are not adjusting their forces. The problem we face in the Anthropocene can be summarised in the most recent and multiple international reports and publications spanning from the IPCC, IPBES, UNESCO, ENECE and the United Nations. Three ‘broad and deep’ transitions needed to address this huge societal problem are the energy transition, current use of space, and the total greenhouse emissions of the food system. How can disciplines become overarching in breaking loose big societal problems of climate change, biodiversity loss, soil and water contamination, social unrest, pandemics and inequality?
We are discerning two different types of transformations: 1. The three ‘broad and deep’ transitions, and 2. A call for transformation that is supported by a multi- to inter- to transdisciplinary theory of the Anthropocene. The distinction between the two transformations is between practice and theory: Is the theoretical transformation (2) needed to support the practical transformation (1)? How can disciplines become overarching and supporting to each other? How can the result of overarching and supporting disciplines contribute to potential solutions? In addition to being solution-oriented, the overarching umbrella will also have to focus on the total unruly problem (blockages, dilemmas, ambivalences, polarization etc.) in the societal domain.
At first we need to primarily understand how we as human beings have come across living in the Anthropocene. Second, we need to understand how the Anthropocene will develop further and what our options for action are. We need knowledge from many disciplines and a theory that can relate as much of that relatively reductionist knowledge as possible in a relatively coherent and holistic way. A theory on the (multi-level) natural and cultural (co-)evolution of complex adaptive systems might be able to relate or even to some extent unify insights from the various sub-disciplines in a reasonably coherent (and process-philosophical) way.
The current Anthropocene socio-ecological system is (resembles) a runaway super-organism, the question being to what extent it can still be tamed. The driving force of this super-organism seems to be a dysfunctional, potentially self-destructive capitalist/extractivist (infinite growth) ideology of survival of the fittest. To what extent might this evolving super-organism still be capable of self-reflection and self-direction, via (geopolitical) cultural evolution and self-domestication, mindfully directed? This last question probably cannot be answered purely theoretically, but will have to be brought to an answer empirically and in a transdisciplinary way. Towards a multi- to inter- to transdisciplinary Anthropocene theory is therefore an urgent need and a call for transformation that needs incremental steps and which needs eventually to be acknowledged by all academic, governmental, corporal and societal actors.
How to cite: Kluiving, S., van der Linde, L., and Lont, J.: Towards a multi- to inter- to transdisciplinary Theory of the Anthropocene - Review of overarching disciplines and research addressing planetary boundaries and social and humanitarian crises, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11942, https://doi.org/10.5194/egusphere-egu25-11942, 2025.
Weather Extremes and their impacts are getting a lot of attention lately, because their occurrence, severity and spatial coverage are increasing and will likely increase further towards the mid and end of the century. Many countries are experiencing significant impact of those extremes due to climate change. It becomes more and more important to better assess the change of characteristics of those extremes according to users and society needs.
It is a challenge to detect and characterize weather extremes for the future climate in all available and relevant climate simulations. A novel approach and methodology is being developed to detect and characterize the changes in weather extreme events using Artificial Intelligence (AI). This is a generic method based on Convolutional Variational Autoencoders (CVAE). This deep learning technique, that uses neural networks, can process large climate datasets much faster than traditional analytical methods.
Another big challenge is to develop on-demand real-world applications that users can manipulate to explore what-if scenarios. Data does not necessarily only come from one research infrastructure (RI), but can also come from several RIs because addressing climate extremes involves climate change impacts that depend on other relevant datasets. Developing robust Digital Twin applications takes a lot of development time. In the context of the interTwin project, a very flexible Digital Twin Engine (DTE) is being developed and implemented. It provides Core Components that can be used by several DT applications from very diverse scientific domains. Applications using AI techniques can also benefit from advanced capabilities using minimal development. It also provides almost automatically generic features and capabilities. This DTE framework acts as an accelerator in order to rapidly develop user-oriented DT applications in diverse scientific domains.
In this presentation, the interTwin DTE will be presented, and it will be shown how it can be easily used to leverage an existing tool in order to create a DT application. Some results of the method applied on Global Coupled Climate Model datasets will be shown for several greenhouse gas scenarios, over Western Europe.
This project (interTwin) has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N°101058386.
How to cite: Pagé, C., Durif, A., Millar, P., Vrbanec, D., Bunino, M., and Sarma, R.: Building a Digital Twin Application for Climate Extremes: Using the interTwin Digital Twin Engine, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9922, https://doi.org/10.5194/egusphere-egu25-9922, 2025.
RADAR4KIT is the generic repository for all scientific data at the Karlsruhe Institute of Technology (KIT). The metadata for datasets which are being published on this repository are also generic and do not necessarily offer the best description for datasets from specific domains such as the environmental sciences.
In the light of an increasing number of initiatives harvesting and aggregating datasets from different repositories which need more detailed descriptions to facilitate meaningful aggregation or filtering, the CREATIVE project provides a solution for domain-specific metadata in the generic RADAR4KIT repository. We developed customized templates and input masks for domain-specific metadata, which enhance the RADAR4KIT usability for the environmental sciences. These metadata schemas are harmonised with the schemas used by the NFDI4Earth, the National Research Data Infrastructure (NFDI) for Earth System Sciences (ESS), so the data which are harvested from RADAR4KIT can be found and processed there. Similarly, the metadata schemas are compatible to the virtual research environment V-FOR-WaTer, which is being developed at KIT in a collaboration between hydrologists and computer scientists and can be used for processing and visualisation of datasets.
Another key focus of the CREATIVE project is connecting the data stewards in environmental science at KIT, facilitating exchange and mutual support in research data management and publishing. Testing the domain-specific metadata templates with this user group and the involved initiatives and infrastructures will also give indication on how this approach can be generalised and transferred to other repositories and disciplines to support the cultural change towards sharing FAIR data at KIT in Germany and internationally.
How to cite: Hassler, S. K., Zuleta Salmon, C., Mälicke, M., Braesicke, P., Meyer, J., and Zehe, E.: Customising a generic repository with domain-specific metadata – the CREATIVE project , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9011, https://doi.org/10.5194/egusphere-egu25-9011, 2025.
The NFDI4Earth (National Research Data Infrastructure for Earth System Sciences) initiative focuses on creating a sustainable research data infrastructure for Earth System Science (ESS) by aligning with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). As part of the NFDI4Earth project, 150 research data repositories with highly diverse subject areas were collected to build the NFDI4Earth Service Catalogue. The consequence of diversity is that small and niche repositories lack visibility beyond their community. As researchers in ESS often cooperate on a multidisciplinary basis, there is also a need for discovering multidisciplinary repositories. Repository metadata is subject to constant change and needs to be individually and manually updated. Therefore, the need for a platform as a sustainable already existing data source was identified that can be harvested by NFDI4Earth. With re3data (Registry of Research Data Repositories), a global registry of research data repositories, such a platform is already available. Re3data operates now for more than a decade, is maintained through an international scientific network, and describes repositories with well-defined metadata fields. Nevertheless, we identified metadata fields with the potential to represent added value. These metadata fields include the “geographical extent of data”, the “maximum data upload size” and whether the repository is “unrestricted to external upload” (in contrast to hosting data from the maintaining institution only, or is restricted to project data). In a first approach, “maximum data upload size” and “unrestricted to external upload” were identified as metadata fields that would best add value, and characterize repositories further. In ESS scientists often deal with big data, such as in Remote Sensing and Satellite Imagery, Climate Modeling, or Environmental Monitoring, so that such information is important for guidance.
When we started this study, our hypothesis was that data repositories are unrestricted for any data upload, however, that there is a maximum data upload. Yet, our study showed that 70% of the repositories we evaluated in one or other way are restricted in their upload of data (in respect to a specific region, e.g. Australia Ocean Data Network Portal; topic, e.g. GEOFON; or institute affiliation, e.g. Geoportal BGR), and just 10% are unrestricted to the kind of data, but have a maximum upload size. We also identified 20% of the evaluated repositories as unrestricted to the kind of data and with no maximum upload size (e.g. PANGAEA). One result of this study is therefore that repositories have to be differentiated by their upload characteristic “restricted” and “unrestricted” in respect to the kind and size of the data. Highlighting this characteristic more clearly in the future should make it easier for users to distinguish multidisciplinary repositories from niche repositories. The next steps will be to discuss these findings with the wider community in ESS, identify further valuable metadata fields – some of which are domain-specific metadata fields - and progress the inclusion of these fields in re3data.
How to cite: Müller, C. and Frickenhaus, S.: Characterizing the Diversity of Data Repositories in ESS, and the Role of re3data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9589, https://doi.org/10.5194/egusphere-egu25-9589, 2025.
Researchers from around the world and across various disciplines are collaborating to address climate change, one of the most pressing global challenges. Producing, processing and handling huge data collections is an everyday challenge for Earth System scientists and data managers alike. Within the Horizon Europe project FAIRCORE4EOSC, we examine several newly developed FAIR enhancing services in the context of the European Open Science Cloud (EOSC) to address some of these data challenges in the ‘Climate Change’ case study. The overall goal is to assess how to improve the discoverability, reusability and traceability of climate data collections at several levels of granularity, thus enhancing the FAIRness of the ENES ( European Network for Earth System Modelling) Research Infrastructure data. The case study explores how to link provenance metadata, processing steps applied to the data, citation information as well as information about connected research activities to the data itself.
The ‘Climate Change’ case study investigates the benefits of integrating the following FAIRCORE4EOSC services: RAiD (Research Activity Identifier Service), PIDGraph and DTR (Data Type Registry).
RAiDs are exemplarily used to provide an exhaustive research context for existing data collections, helping domain agnostic users with an aggregated view on related details - from data generation by the Earth System modellers up to publication of final assessment reports. RAiD metadata will be supplied to Open Science Graphs like the PIDGraph. The DTR offers the possibility to register and assign persistent identifiers to single and complex data types and achieves a machine-actionable standardization of type metadata that is used for some typical climate data objects. This is a prerequisite for machine-aided analytics and is of high priority due to the commonly large data volumes in climate science.
Additional efforts aim to level the pass to future developments, such as potentially extending existing Web Processing Services (WPS) to be able to publish RAiD details. To advance further, we propose using the DTR for data typing of STAC (SpatioTemporal Assets Catalogs) defined as FDOs (FAIR Digital Objects), paving the way for enhanced interoperability across data spaces in climate science.
Our presentation will demonstrate the practical benefits of these new EOSC services for a climate research ecosystem paving the way for a more efficient, collaborative, and impactful Earth System Science community.
How to cite: Flügel, A.-L., Krüss, B., Widmann, H., Thiemann, H., Adloff, F., and Kindermann, S.: User Scenarios in Action: how European Open Science Cloud services can help Earth System Scientists, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11173, https://doi.org/10.5194/egusphere-egu25-11173, 2025.
European and global institutions are working hard to collect and share high quality environmental data and information. This is because it is clear that the ocean knows no borders, and data sharing is necessary to make environmental policies based on knowledge that is informed by extensive data.
Fifteen years ago, the European DG MARE launched the EMODnet data infrastructure, which today provides a consolidated framework for open access to marine data, products and services. The institutions behind it work together by scientific thematic area to offer FAIR (Findable, Accessible, Interoperable and Reusable) information.
The implementation of the FAIR principles on the data is complex and is constantly being developed and improved.
The thematic discipline of EMODnet Chemistry focuses on data and information relevant to eutrophication, pollution by hazardous substances and litter. Each year, regional aggregated datasets on these themes are published, containing validated and unrestricted data.
There are already various access points to the aggregated data collections, which can be downloaded directly (https://emodnet.ec.europa.eu/en/chemistry#chemistry-data) or used for visualization and subsetting (https://emodnet-chemistry.webodv.awi.de/). So far, none of them is interoperable, but this is being sorted out by establishing an ERDDAP instance for the EMODnet Chemistry aggregated data collections (https://erddap.emodnet-chemistry.eu/erddap/index.html), starting with the eutrophication datasets.
ERDDAP was chosen because it is an open-source, simple and user-friendly tool that allows downloading data in different formats. In addition, the automation of requests is possible and it can be linked to other ERDDAPs.
Technical research and development work has been carried out to implement a sustainable workflow that can be reused annually with the release of each new version of the collections. Using a series of Python scripts, the data in the extended SeaDataNet ODV-ASCII format (containing metadata and data) are split into small chunks and converted to NetCDF format for uploading to ERDDAP. Using the newly developed tool “erddapcfg” (https://github.com/PlehanSebastian/erddapcfg) and a SQLite database, the ERDDAP metadata are compiled, ensuring that all metadata and data fields are given appropriate scientific meaning. Complementary, a web service with geoserver provides a WMS of the data stations.
The various thematic datasets differ in their structure, so each type of collection requires a specific development. In the case of the eutrophication datasets, the biggest challenge was the file size.
Once the work on the eutrophication datasets is completed, the next step will be to tackle the work on the microlitter datasets, considering the high relevance of this type of data on a global scale.
How to cite: Molina Jack, M. E., Plehan, S., Buga, L., Gatti, J., Iona, A., Larsen, M. M., Østrem, A. K., Vinci, M., Wesslander, K., Schaap, D., and Giorgetti, A.: Boosting interoperability of EMODnet chemistry aggregated datasets with a new point of access, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19483, https://doi.org/10.5194/egusphere-egu25-19483, 2025.
Throughout its extensive history, Earth’s surface has undergone dramatic transformations, accompanied by significant changes in climate, environment, and resources. Paleogeomorphology is the result of the interaction between deep Earth tectonic processes and surface processes. The coupling process between active tectonics and geomorphological evolution such as earthquakes, volcanic activities, glacial and fluvial processes represents a key interface. Research on paleogeomorphology is closely related to the interactions between the deep and shallow layers of Earth’s interior and is a crucial component of multi-layered, multi-scale Earth system science. Therefore, the reconstruction of global paleogeography and paleogeomorphology during geological time has long been a focus of interest among geologists. The South China Sea, as a sensitive region to global climate and oceanic environmental changes, has experienced significant changes in its topography and geomorphology due to its complex geological structure and dynamic hydrological processes. This region has become a key subject of Earth system science research. The evolution of its three-dimensional geological environment is deeply influenced by tectonic activity, climatic fluctuations, and ocean dynamics, making its changes highly complex and uncertain, which traditional methods fail to resolve accurately. Therefore, it is essential to approach the reconstruction of the paleogeomorphological evolution of this multi-phase tectonic region from a quantitative perspective. In recent years, with the accumulation of Earth system data and the application of machine learning methods in complex system modeling, machine learning-based Earth system simulation has gradually emerged as a new frontier method, particularly in paleoelevation reconstruction. The application of this technology significantly enhances the precision and predictive capabilities of simulations for geological evolution and environmental changes in the South China Sea region. However, using Sr/Ca and Mg/Ca ratios in paleoelevation reconstruction has certain limitations, primarily due to interference from factors such as geological background and climate change, with weaker environmental responses in extreme environments such as arid or cold regions. To improve the accuracy of paleoelevation reconstructions, multiple geochemical indicators (such as δ¹⁸O, δD, and Δ₄₇) can be combined, and experimental calibration can be applied to separate the effects of climate and elevation, thereby optimizing existing models. By combining three-dimensional evolution models, it is possible to reconstruct the geomorphological evolution of the region, explore the tectonic factors of the South China Sea's opening and closure, the arc-continent collision that led to the Taiwan orogeny, and the impacts of surface factors such as paleoclimate and sea-level fluctuations on the northern South China Sea's hydrological systems, topography, and basin sedimentation. This further reveals the intrinsic mechanisms between the complex geological evolution of the South China Sea and oceanic dynamical processes.
How to cite: Liu, Z., Shu, P., Wang, P., Li, Y., Bukhari, S. W. H., Zhang, L., Wang, R., and Lu, K.: Palaeogeomorphic reconstruction of the South China Sea: coupling tectonics, climate, and ocean dynamics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2408, https://doi.org/10.5194/egusphere-egu25-2408, 2025.
Galaxy Europe (https://usegalaxy.eu) is an ELIXIR-recommended open-source IT infrastructure (RIR) (https://galaxyproject.org/news/2023-12-14-elixir-rir-for-galaxy-europe) emphasizing interoperability and FAIR data analysis. This infrastructure, based on the Galaxy project (https://galaxyproject.org), supports multi-disciplinary, data-driven research.
Galaxy Europe enables users to:
- Freely access thousands of tools, regularly enhanced and updated, from various research fields such as life, earth system, environment, or climate sciences. This includes tools for data import, organization, sharing, annotation, and export. Each tool can be plugged into a workflow.
- Use interactive tools such as QGIS, RStudio, and JupyterLab directly on the platform.
- Design, reproduce, (remotely) run, share, and publish analysis workflows using these batch and interactive tools, (with or) without programming skills.
- Freely use huge compute and storage resources without any charge.
- Have a dedicated subdomain designed with the necessary tools regarding one scientific domain. For instance, FAIR-EASE implemented a subdomain focusing on earth system sciences (earth-system.usegalaxy.eu) gathering ocean, land, atmospheric and biodiversity processing software.
Fully integrated into the work area, the Galaxy Training Network (https://training.galaxyproject.org) provides hundreds of free and open tutorials and learning pathways from over thirty scientific topics on data analysis, tool development, and workflow design. The Galaxy Training Network, thus, helps democratize the use of Galaxy, supporting the adoption of open science practices and promoting the reuse of tools and data
The two EOSC projects — EuroScienceGateway and FAIR-EASE — have been joining forces for two years to further improve Galaxy Europe and make it a unique solution for FAIR analysis of scientific data. FAIR-EASE adds numerous tools, workflows, and tutorials for multidisciplinary and interdisciplinary studies on Earth System sciences, creating an interdomain digital architecture for the integrated use of environmental data. EuroScienceGateway, on the other hand, provides a robust open infrastructure for data-driven research.
With inputs from these two projects, we will showcase how Galaxy facilitates access to data, tools, and workflows, while supporting the reuse of these resources across diverse research contexts. Additionally, RO-Crate provides a FAIR packaging solution for research objects, including data, methods, and software, by incorporating structured metadata that preserves workflows and their execution histories. This approach, adopted by projects as a practical implementation of the FAIR vision, enables workflows to be deposited into registries like WorkflowHub for broader accessibility.
How to cite: Detoc, J. and Jossé, M.: Galaxy Europe - An IT infrastructure for FAIR Data Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10084, https://doi.org/10.5194/egusphere-egu25-10084, 2025.
Currently certain earth system models, due to their advanced modeling capabilities and improved computational power, can perform simulations at extremely high resolutions as close to a km. The data from these simulations act as drivers for many downstream scientific research applications as well as decision making tools that aid in policy making. These applications in turn depend on shared or standalone computational resources at HPC infrastructures. As a result the federated data access system design is required to revolve around a triad comprising of:
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Data
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Analysis Tools
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Computing resources
Further, at each of the HPC infrastructures, depending on the earth system model, the format of the data being produced varies. Furthermore, each center has its own combination of storage tiers, each of which are subject to specific hardware constraints. Also, based on the focus of the scientific research, the data usage pattern differs. Hence the organization of the data at each data center for efficient discoverability within the federated data access should cater to :
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Technicalities of the data ( format, size, file count etc.)
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Usage pattern of the data
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Constraints arising due to the Specifications and Limitations of the storage tiers.
Spatial Temporal Asset Catalogs (STAC) fundamentally cater to the discoverability of data corresponding to a specific geographic location associated with a particular time instance or duration. ESM data are a natural fit for such representation. In the present work we provide an overview of the application of STAC for the federated data access within the Warmworld project at the DKRZ and JSC HPC centers. We explain how each of the aforementioned factors at each data center have been addressed and display concrete benefits for data producers and reusers.
How to cite: Modali, K. R., Peters-von Gehlen, K., Ziemen, F., Hinz, C., Saini, R., and Schultz, M.: STAC for federated data access to high-volume ESM datasets in preparation for Exascale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10288, https://doi.org/10.5194/egusphere-egu25-10288, 2025.
The national research data infrastructure NFDI4Earth builds a network of 65 partners to support research data management (RDM) in the earth system sciences. One of the currently established infrastructures is the user support network (USN).
The partner institutions of NFDI4Earth range from universities over research institutes to governmental agencies, all having different approaches to handle research data in their specific discipline, different support infrastructures and workflows and a different way to support users in research data handling. In most cases the local RDM support of an institution is the right place to go for researchers. But for cross-disciplinary projects it might be difficult for the single user to find the right contact person. A distributed support network can help in these cases involving several support persons dealing with one user service request.
Our ambition is to provide a high-quality data management support network for ESS researchers. In this network, already existing support institutions contribute jointly. We also collaborate with national consortium helpdesks of related disciplines to share experiences and offer an even wider support portfolio.
We present our support network, the workflows and internal organization, and address the challenges we are facing.
How to cite: Mehrtens, H., Getzlaff, K., and Lorenz, S.: Cross-disciplinary user support network in NFDI4Earth, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11112, https://doi.org/10.5194/egusphere-egu25-11112, 2025.
StraboSpot is an open-source, US NSF-funded, FAIR-aligned, and community-driven data system that enables researchers to collect, store, and share spatially referenced geologic data across scales. StraboSpot's development has been a collaborative initiative, shaped through a series of community workshops initially focused on providing tools that enhance research in structural geology. Over time, other communities have expanded these efforts to include diverse geological subdisciplines. Community workshops have played a crucial role in establishing shared metadata standards, a unified vocabulary, and workflows tailored to meet the unique needs of each user community. This inclusive approach has been instrumental in creating an infrastructure that integrates diverse data types and promotes interdisciplinary collaboration while minimizing barriers to data entry.
The "Spot" approach provides a flexible framework for characterizing spatial areas across all scales, facilitating seamless integration of data ranging from micro-scale laboratory measurements to regional-scale field data. By allowing Spots to nest indefinitely within one another, users can preserve critical information about spatial context, scale, orientation, and inter-relationships. The StraboSpot ecosystem comprises three core applications: StraboMicro, a desktop tool designed for managing and contextualizing laboratory-derived micro-scale data; StraboField, a mobile application tailored for mapping and field-based research; and StraboExperimental, designed for data derived from rock deformation experiments. All data are tied to a shared database that preserves provenance and context. Additionally, researchers can link data to external repositories, such as EarthChem, further enhancing data interoperability.
In response to clear community priorities, StraboSpot is actively enhancing its functionality to support enhanced collaboration and improve data reusability. Current developments include the implementation of Group Workflows, which enable collaboration in both field and laboratory settings while maintaining data provenance and robust version control. Additionally, a Quality Assurance/Quality Control (QA/QC) framework is being developed to improve confidence in shared observational data. This QA/QC system will provide a transparent and systematic mechanism for evaluating data quality and completeness, facilitating the use of shared data sets within and between disciplines.
How to cite: Ibrahim, Y., Newman, J., Tikoff, B., Walker, J. D., Davidson, D., Shipley, T., Nelson, E., and Martin, C.: Enhancing Multiscale Geologic Data Collection, Sharing, and Reusability Through the Community-Driven StraboSpot Ecosystem, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11892, https://doi.org/10.5194/egusphere-egu25-11892, 2025.
Geo-INQUIRE (Geosphere INfrastructures for QUestions into Integrated REsearch) addresses the pressing need for sustainable and interoperable research data infrastructures to tackle critical societal challenges. With a consortium of over 50 partners, the project integrates diverse data sources and services across geoscientific domains. By fostering FAIR (Findable, Accessible, Interoperable, and Reusable) principles, Geo-INQUIRE supports a cultural shift toward open and reusable science.
The complexity of modern societal challenges, such as climate change, resource management, and natural hazard mitigation, demands a multidisciplinary approach to research. Despite the importance of multidisciplinary research, significant challenges remain for users in accessing, integrating, and analyzing data across diverse scientific domains. The diversity of data formats, vocabularies, and structures often creates barriers to discovering and connecting related datasets, particularly when data stewardship services originate from different disciplines.
In this contribution, we present a metadata approach designed to address challenges in data services interoperability and usability. A key challenge lies in improving the EPOS-DCAT-AP metadata model (https://epos-eu.github.io/EPOS-DCAT-AP/) to describe complex relationships between data services effectively. As of now, these are indeed unrelated, thus hindering users from connecting and querying related datasets. To address this, we introduced semantic information describing service input parameters and output response.
The metadata approach is applied to a multidisciplinary use case involving two data services selected from the Geo-INQUIRE portfolio, provided by two different scientific domains: Anthropogenic Hazards and Geological Information and Modeling. The Anthropogenic Hazards domain provides access to data on human-induced seismic events in the form of a catalogue organized into episodes. Each episode consolidates industrial and geophysical data on anthropogenic activities in specific areas and in a given time period.
The Geological Information and Modeling domain provides access to datasets on geological maps, boreholes (for water, oil, or gas extraction), 3D geological models, and mineral resources.
Specifically, linking seismicity data to borehole data allows users to build better subsurface models for more precise spatio-temporal analysis of relationships between industrial activities, subsurface geology, and seismic responses. For example, users can explore how specific borehole characteristics, such as lithology, correlate with seismicity patterns in a given region.
This work demonstrates how semantic metadata can significantly enhance the usability and interoperability of geoscientific data services. By explicitly defining relationships between services and leveraging metadata-driven automation, the approach significantly reduces users' efforts in multidisciplinary research.
How to cite: Giuliacci, K., Paciello, R., Sbarra, M., Vinciarelli, V., Salvi, M., Bailo, D., Michalek, J., Mtupa-Ndiaye, A., and Chanthaw, F.: Linking services to enhance multidisciplinary dataset usability with semantic metadata in the Geo-INQUIRE Project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15067, https://doi.org/10.5194/egusphere-egu25-15067, 2025.
The assessment of the exploration potential and high upfront exploration costs are significant barriers to the deployment of geothermal energy exploitation. The DEGREE project aims to enhance the success rate of such projects through advancing exploration methodologies and the development of a virtual digital underground laboratory. This laboratory leverages a digital twin of the target area, a geothermal test site in the East Eifel region of Germany. The project covers the entire workflow, from data collection and processing to geological and coupled hydro-thermo-mechanical modeling, as well as visualisation and analysis of the model results. This workflow will be designed to be fully automated, including the computation of individual data processing steps on distributed systems. The final model results will be accessible through a browser-based frontend, featuring three-dimensional visualisation and advanced analysis tools. This poster presents an overview of the project’s approach and the planned architecture of the virtual digital laboratory.
How to cite: Meeßen, C., Volk, M., and Castell, W.: Developing a virtual digital laboratory for geothermal exploration: data processing, distributed systems and three-dimensional model visualisation of a digital twin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15245, https://doi.org/10.5194/egusphere-egu25-15245, 2025.
Improvements in computational speed lead to better resolutions in Earth System Models (ESM) allowing them to resolve scales of a few kilometers. The volume of the resulting data greatly increases with the improvements in resolution and introduces a challenge to processing and storing these results.
While modern HPC systems provide petabyte-scale capacity for file storage, analyzing such data on local user systems can become a prohibitive bottleneck. Beyond the sheer demands on processing high-volume ESM data, there is also increasing demand to make them FAIR and in particular findable.
The goal of the “Easier” module of the Warmworld project aims to simplify the access to ESM data from different HPC centers, in particular the German Climate Computing Center (DKRZ) and the Jülich Supercomputing Centre (JSC). One aspect is the creation of a joined catalog following the SpatioTemporal Asset Catalogs (STAC) specification. This allows browsing data available at both centers. Details on the STAC implementation will be presented by Kameswar Rao Modali et al. at this General Assembly (EGU25-10288).
The catalog also contains links to access the data, either as a download or later as zarr-stream. The explicit implementation of the required REST-APIs depends on the infrastructure, hardware and software, of the data centers as well as the organization of the stored data.
As the first data backend at JSC, we set up a Fields DataBase (FDB), developed by ECMWF, to store the ESM results as multi-dimensional data cubes. For data retrieval, we provide a download service based on the MARS language for identifying data within the FDB and the UNiform Interface to COmputing REsources (UNICORE) for an automated access to our HPC system. The download service integrates the Helmholtz authentication and authorization infrastructure. This will allow a large number of institutions to access these services with the possibility to control access and resource use.
Our poster will provide details on the ongoing implementation and combination of the various tools and services used at JSC as well as further details on the implementation on our HPC systems. In addition, we will provide first information about the planned authorization for different data accesses and also show the performance of different components with a set of benchmarks.
How to cite: Hinz, C., Apweiler, S., Grasse, S., Hagemeier, B., Saini, R., and Schultz, M.: Easier Access to ESM Data: Implementation at Jülich Supercomputing Centre, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19091, https://doi.org/10.5194/egusphere-egu25-19091, 2025.
Earth System Scientists (ESS) work in various research fields spanning from atmospheric research, to land use and oceanographic research using a multitude of data formats, vocabularies and sources for their data. However, data are mostly not presented in a concise and holistic way. Thus, ESS still are forced to deal with different interfaces, searching for relevant information and tools. The National Research Data Infrastructure for Earth System Sciences NFDI4Earth was created to address these issues. With building a platform connecting a large group of sources for data in Earth system sciences, including expert information and educational resources. The OneStop4All provides a user-friendly single-point-of-entry from which all resources can be addressed. This entry-point is enriched with a living handbook and educational resources and the User Support Network provides additional help or the user.
To realize the envisioned level of interoperability, agreements and partnerships have to be established at several levels, which will be the visualized on the poster presentation. On the political level, agreements on modes of participation, a common adoption of quality standards, as well as a proper embedding into the national and international ecosystem have to be constituted. At the same time, a high level of interoperability requires widely accepted identifiers such as DOI, IGSN and other PID services to identify objects across organizational boundaries. On an intermediate level, a jointly accepted data-centric architecture requires to agree on standardized interfaces, harmonization of approaches to metadata standards. Finally, on the technical level, systems need to be integrated, identification and access services have to provide a user experience with as few system disruptions as possible.
Hereby, NFDI4Earth follows the principle of making use of what has been established by the consortium partners such as the DataHub of the Helmholtz Research Field Earth & Environment, as well as following the recommendations of international initiatives, like OneGeochemistry to ensure international connectivity. In particular, the approach is guided by the FAIR principles and full embracement of Open Science (see the NFDI4Earth Fairness and Openness Commitment). Being distributed by design, the approach is open to allow new contributors and members to join-in and engage in this joint endeavour.
How to cite: Schmidt, C., Hezel, D. C., Gerloff, I., Elger, K., Protopopova-Kakar, V., Lorenz, M., Meistring, M., Xu, J. D., Ott, F., and zu Castell, W.: The national research data infrastructure for Earth System Sciences NFDI4Earth: an approach to realize international interoperability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19463, https://doi.org/10.5194/egusphere-egu25-19463, 2025.
