Roland Koppe

Earth and environmental research (E&E) involves managing complex, large-scale data streams that require robust processing, thorough documentation, and secure long-term preservation. The O2A (Observations to Analysis and Archives) Data Flow Framework presents a modular solution linking raw observations to standardized workflows and archival systems, facilitating the transformation of diverse sensor outputs into curated and accessible datasets. Its integrated modules enable efficient instrument metadata management, automated data ingestion, near real-time monitoring, collaborative analysis, and FAIR-compliant data publication. The framework has been successfully implemented in prominent initiatives such as MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) and the German Marine Research Alliance (DAM), providing a scalable and interoperable foundation for contemporary data management and promoting reproducibility as well as cross-institutional collaboration.

The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), has conducted airborne radar campaigns since 1994 across Antarctica and Greenland, utilizing six different radar systems to study ice sheets and their interactions with climate, ocean and the solid Earth. Over the past three decades, AWI has collected more than one million profile-kilometres of radar data, covering approximately one quarter of the Antarctic and the Greenland Ice Sheet, respectively. In this review article, we describe AWI's airborne radar systems and their deployments over the Greenland and Antarctic Ice Sheet. Moreover, we summarize application and usage of AWI's radar systems, which provided crucial insights into e.g., ice dynamics, mass balance, and ancient landscapes buried beneath the ice. The integration of radar data with other geophysical methods has enhanced bathymetric models, improving predictions of ice–ocean interactions and ice-shelf stability and contributed to a better understanding of crustal and geological evolution of the Antarctic continent. As part of this paper, and to support scientific progress, AWI made its airborne radar data publicly accessible through the Radar Data over Polar Ice Sheets viewer hosted by the Marine Data Portal (https://marine-data.de/viewers/, last access: 19 April 2026) and PANGAEA (https://doi.org/10.1594/PANGAEA.972094; Eisen et al., 2024), ensuring compliance with FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Future research will expand on these contributions, focusing on refining ice-sheet models and exploring new areas of glaciological and geological interest.

We demonstrate the latest version of the visualization of permafrost-related map products in the context of ESA CCI+ Permafrost initiatives (Phase I and II, 2018-2021, 2023-2026). Already in ESA DUE GlobPermafrost project (2016-2018), a comprehensive range of remote sensing products was produced by the project committee and visualized as viewer in the AWI O2A (Observation to Analysis & Archive) infrastructure framework: North-south transects in the northern hemisphere with trends in Landsat multispectral indices (e.g. Tasseled Cap Brightness, Greenness and Wetness, and Normalized Difference Vegetation Index (NDVI)), Arctic land cover (e.g. shrub height and vegetation composition), lake ice grounding, InSAR-based land surface deformation and rock glacier velocities. The main products were the Global Permafrost Essential Climate Variables (ECVs), which were derived from a spatially distributed permafrost model driven by Land Surface Temperature and Snow Water Equivalent products. These Permafrost ECVs include mean annual ground temperature (MAGT) and active layer thickness (ALT) at pixel level, and additionally permafrost extent and probability (PFR).In the context of the ESA CCI+ Permafrost project, time was incorporated as a significant climate-related variable into the products. This resulted in a time series spanning over twenty years. It comprises CCI+ Permafrost Circum-Arctic model output for MAGT, from the surface down to a depth of 10 meters, as well as PFR and ALT. All data products are available at yearly resolution, as well as the calculated averages of MAGT, PFR and ALT over the time series.To make the products publicly visible, we created WebGIS projects using WebGIS technology within the O2A (Observation to Analyses and Archive) data workflow framework at AWI. This modular, scalable and highly automated spatial data infrastructure (SDI) has been developed and operated at AWI for over a decade. It has undergone continuous improvement and provides map services for geographic information system (GIS) clients and portals. The FAIR principles were implemented to address the increasing demand for research data and metadata that is discoverable, accessible and reusable. The ESA Permafrost WebGIS products were designed using GIS software and published as Web Map Services (WMS), an internationally standardised Open Geospatial Consortium (OGC) format using GIS server technology. Additionally, visualisations of raster and vector data products have been developed that are specific to the projects and adapted to their spatial scales and resolutions.In addition to data products derived from remote sensing, the locations of WMO GCOS ground-monitoring networks belonging to the permafrost community, which are managed by the International Permafrost Association (IPA) and form part of the Global Terrestrial Network for Permafrost (GTN-P), were incorporated as a feature layer and updated on an ongoing basis. All data products have previously undergone registration with the Digital Object Identifier (doi), and have been published in the data archives PANGAEA or ESA CEDA.

Environmental observations from sensor systems remain one of the most important sources of ground-truth data in Earth System Sciences. In particular, the rapid rise of AI-based methods, high-resolution modelling, and the growing demand for near-real-time reference data to support environmental decision-making, have substantially increased the need for reliable, interoperable, and AI-ready observational data.To enable seamless integration and effective use of such data across diverse application scenarios (especially when combining observations from multiple sources), consistent data structures, well-defined interfaces, and harmonised, machine-readable metadata are essential. These requirements represent both a technical and a community-driven challenge and form a key prerequisite for ensuring the AI-readiness of sensor data.Within the Helmholtz Research Field Earth & Environment, the DataHub initiative addresses this challenge by developing a uniform and FAIR research data infrastructure for observational time-series data across all seven contributing German Helmholtz Centres. Central to this infrastructure is the OGC SensorThings API STAMPLATE-Schema, a unified metadata schema for sensor-based observational data. The STAMPLATE-Schema serves as the semantic backbone of the DataHub ecosystem, providing a shared, machine-actionable language to describe deployments, sensors and observations. It is built upon JSON-LD and schema.org, enabling semantic interoperability, extensibility, and direct compatibility with web technologies and AI workflows.The STAMPLATE-Schema connects and aligns the core ecosystem components, including the Sensor Management System (SMS) – which provides user-friendly management of sensor and deployment metadata - and the Earth Data Portal (EDP), which supports cataloguing, discovery, and visualisation of SensorThings API–based data. Additional integrations, such as the System for automated Quality Control (SaQC) and the time-series handling via time.io, build on this shared metadata foundation and support typical observational data workflows including data flagging, quality assessment, and downstream processing.The STAMPLATE-Schema and the associated federated SensorThings API–based data infrastructures are currently being implemented across several major German research centres and large-scale observational projects, including the TERENO-network with its multiple observatories. Together, they are expected to provide access to more than 20 billion observations from seven research centres spanning multiple environmental research domains, including terrestrial, atmospheric, and marine systems, by the end of the year.The DataHub and the STAMPLATE-Schema thus provide a common metadata language and framework for FAIR and AI-ready sensor data across our research field and similar federated research data infrastructures.

Research data management (RDM) in the Earth system sciences is complex and can be frustrating. Data come in many shapes and formats—observations, model outputs, samples, derived products—and are spread across a wide range of repositories, services, and software ecosystems. These infrastructures differ greatly in metadata quality, interoperability, and FAIR maturity. For researchers, this often means spending too much time figuring out where to publish data, how to describe it properly, or how to reuse existing datasets and software. At the same time, expectations from funders and journals on data outputs continue to rise with respect to openness, curation, and long-term stewardship. Within the German National Research Data Infrastructure (NFDI), the NFDI4Earth consortium tackles these challenges by building practical, community-driven solutions for the Earth system sciences. As developers and designers, our focus is on lowering barriers and making FAIR data and software practices easier to understand and apply in everyday research. In this contribution, we introduce two key building blocks of this effort: the Knowledge Hub and the OneStop4All. The Knowledge Hub (https://knowledgehub.nfdi4earth.de) is a knowledge graph that connects heterogeneous Earth system resources, e.g., datasets, repositories, services, software, and educational materials, using a harmonized metadata model. It harvests metadata from multiple providers—ranging from global aggregators to national and domain-specific services (see, for instance, the Helmholtz DataHub: https://earth-data.de/) - and exposes them through a well-defined SPARQL API. This allows both humans and machines to query, explore, and reuse metadata consistently, and enables developers to build custom applications on top of it. The OneStop4All (https://onestop4all.nfdi4earth.de) builds on the Knowledge Hub to offer a discovery and guidance portal for researchers. It brings together the resources in a single, coherent interface. Cross-domain search and guided navigation help users move along the research data lifecycle without having to know all standards and infrastructures upfront. A central feature is the Repository Wizard, an interactive decision-support tool that helps researchers find suitable repositories for publishing their data based on data type, discipline, and policy constraints. In addition, the NFDI4Earth Label provides a transparent, community-oriented way to communicate repository quality with respect to FAIR principles, sustainability, and relevance for Earth system sciences. Beyond discovery, the OneStop4All puts a strong emphasis on learning and cultural change. It provides integrated access to open educational resources, good-practice guides, and showcases that demonstrate the concrete benefits of FAIR and open data and software. A domain-specific chatbot complements these resources by answering practical questions on metadata, licensing, data publication, and software citation. We will showcase these services, share lessons learned from development, and highlight opportunities for community contributions. From our perspective as a distributed team of designers and software developers, combining harmonized metadata, user-centered services, and hands-on training is key to making FAIR and open research practices work at scale in the Earth system sciences.

The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), has conducted airborne radar campaigns since 1994 across Antarctica and Greenland, utilizing six different radar systems to study ice sheets and their interactions with climate, ocean and the solid Earth. In this review article, we describe AWI's airborne radar systems and their deployments over the Greenland and Antarctic Ice Sheet. Moreover, we summarize application and usage of AWI radar systems, which provided crucial insights into e.g., ice dynamics, mass balance, and ancient landscapes buried beneath the ice. The integration of radar data with other geophysical methods has enhanced bathymetric models, improving predictions of ice–ocean interactions and ice-shelf stability and contributed to a better understanding of crustal and geological evolution of the Antarctic continent. To support scientific progress, AWI made its airborne radar data publicly accessible through the Radar Data over Polar Ice Sheets viewer hosted by the Marine Data Portal (https://marine-data.de/viewers/) and PANGAEA (https://doi.org/10.1594/PANGAEA.972094), ensuring compliance with FAIR principles. Future research will expand on these contributions, focusing on refining ice-sheet models and exploring new areas of glaciological and geological interest.

In environmental sciences, observational data remains indispensable for monitoring and understanding of natural processes, validating earth system models and remote sensing products, and training of data driven methods. However, unified standards and interfaces for ensuring that such data is consistently available, usable, and compliant with FAIR and Open Science principles are still lacking.The so-called DataHub initiative of the Helmholtz Research Field Earth & Environment, involving seven large environmental research Centers across Germany, addresses this gap by collaboratively developing a cohesive and unified research data space, including consistent data formats, metadata standards, tools, interfaces and services.Since the beginning of the DataHub, we have been particularly focusing on unifying time-series data from environmental sensor systems, which are operated across all participating Centers. In this context, we have developed a digital ecosystem, that enhances and links existing and established research data infrastructures with well-defined interfaces and metadata standards. This ecosystem now covers the full processing chain from the integration of new sensor systems and their metadata over automatic and manual quality checks and flagging schemes to the visualization via dashboards and data portals or the usage in data analysis frameworks. In particular, our framework consists of multiple independent tools and services like the Sensor Management System (Brinckmann et al., 2024) as dedicated system for managing sensor metadata, the System for Automated Quality Control (SaQC, Schäfer et al. 2024) as common framework for QA/QC, a tailored metadata profile which adapts the SensorThings API (STA) from the Open Geospatial Consortium to common requirements from environmental sciences (Lorenz et al. 2024), the Earth Data Portal (https://earth-data.de) as overarching data portal and visualization suite as well as tools and services that link all these different building blocks.While the first concepts of this ecosystem were based on temporary tools and interfaces, we have now reached a level of maturity, that allows us to confidently scale our solutions to new communities and user groups. In this presentation, we will hence give a brief overview of our ecosystem as well as the integrated tools and services. The main focus will be on a hands-on demonstration of the full workflow from deploying a new sensor system, the integration into the contributing services, the (meta)data provision via STA as well as the integration in different downstream systems like the Earth Data Portal for data visualization.By this, we want to promote the potential of a decentralized research data infrastructure, that has been developed and adopted across multiple research Centers and reach out for new communities and user groups for ultimately creating a FAIR and inter-institutional open data space for our environmental sciences.

In Earth System Sciences, the landscape of resources for research data management, ranging from specific datasets to RDM services, is very diverse to tackle the heterogeneous and domain-specific (sub) community needs. Although marketplaces for services and central access points for specific data types exist, researchers need assistance discovering resources for research data management tasks without having to navigate multiple, differently designed and not integrated platforms.By engaging with the communities, NFDI4Earth aims to address the needs and requirements of the end users and includes the following objectives:map the existing landscape of sustainable services and reuse them as data sources or user interface components; align strategies across infrastructure providers/across NFDI4Earth community members to curate provided information for data sources with the providers and share compute resources; develop metadata harvesters or required adaptions together with the service provider's developers, and share the source code with an open license; and reuse open standards and specifications for all (service) interfaces and share own specifications openly. We apply this strategy for the implementation of our two central support services.The Knowledge Hub (https://knowledgehub.nfdi4earth.de) is a knowledge graph database and acts as an aggregator. It harvests curated information for relevant resources from various sources and makes it available as semantically enabled open data. The solution builds on an open-source data management system and a triple store. Fostering the community effort, we encourage and investigate whenever possible the implementation across Knowledge Hub and data source developers, such as with the Helmholtz Data Hub Earth and Environment. By actively collaborating with the original sources on the curation of the harvested information, e.g., with re3data for repository information, we ensure the distribution of high-quality information via the data sources and the NFDI4Earth Knowledge Hub. The OneStop4All (https://onestop4all.nfdi4earth.de) and the integrated Living Handbook facilitate the discovery of ESS-relevant RDM resources, such as datasets or software, and act as a resource catalog based on the Knowledge Hub data. Through the publication, curation, and integration of related information, such as best practices or showcase articles for published resources, the OneStop4All also acts as a community portal. This approach is implemented by managing Living Handbook articles in an open repository, editing them in an open review process, harvesting them through the Knowledge Hub, and making them visible in a user-friendly presentation. In addition, the OneStop4All offers several search functionalities providing benefits for differently skilled users including RDM novices and experts. In the following steps, we will integrate existing frontend services, e.g., Earth Data Portal map viewers, to facilitate researchers using a single entry point for their RDM tasks. Our FAIR-by-design services will be iteratively developed with an open and distributed developer team focussing on data access to data publications, with an eye on using the content for advanced data analytics use cases.

Time-series data are crucial sources of reference information in all environmental sciences. And beyond typical research applications, the consistent and timely publication of such data is increasingly important for monitoring and issuing warnings, especially in times of growing frequencies of climatic extreme events. In this context, the seven Centres from the Helmholtz Research Field Earth and Environment (E&E) operate some of the largest environmental measurement-infrastructures worldwide. These infrastructures range from terrestrial observation systems in the TERENO observatories and ship-borne sensors to airborne and space-based systems, such as those integrated into the IAGOS infrastructures.In order to streamline and standardize the usage of the huge amount of data from these infrastructures, the seven Centres have jointly initiated the STAMPLATE project. This initiantive aims to adopt the Open Geospatial Consortium (OGC) SensorThings API (STA) as a consistent and modern interface tailored for time-series data. We evaluate STA for representative use-cases from environmental sciences and enhance the core data model with additional crucial metadata such as data quality, data provenance and extended sensor metadata. After centre-wide implementation, the standardized STA interface also serves community-based tools, e.g., for data visualization, data access, quality assurance/quality control (QA/QC), or the management of monitoring systems. By connecting the different STA endpoints of the participating research Centres, we establish an interlinked research data infrastructure (RDI) and a digital ecosystem around the OGC SensorThings API tailored towards environmental time-series data.In this presentation, we want to show the status of the project and give an overview of the current data inventory as well as linked tools and services. We will further demonstrate the practical application of our STA-based framework with simple and representative showcases. With our contribution, we want to promote STA for similar applications and communities beyond our research field. Ultimately, our goal is to provide an important building block towards fostering a more open, FAIR (Findable, Accessible, Interoperable, and Reusable), and harmonized research data landscape in the field of environmental sciences.

Research data in the Earth System Sciences (ESS) are managed in diverse repositories with varying aims, publishing, and curation approaches, as well as technical solutions. The resulting heterogeneity often hampers implementing interoperability and harvesting concepts. From the researchers' perspective on integrative data-driven research questions across repository borders, this leads to ineffective search and reuse of the data. We consider it is vital to train researchers to provide high-quality FAIR data and metadata. However, it is even more important to enable repository providers to act as multipliers, as this enables them to provide researchers with suitable repository solutions. This can be done, for example, by implementing fit-for-purpose metadata schemas and interfaces.In Germany, several initiatives serve as umbrellas for joint activities with ESS repository providers. In collaboration of the German national data infrastructure for Earth System Sciences (NFDI4Earth) and the Helmholtz Metadata Collaboration (HMC), we have developed a roadmap that enables repository providers to meet the needs of researchers and technical requirements. As an initial step, we developed recommendations in a community-driven process across NFDI4Earth and HMC. These recommendations provide common steps to foster interoperability, particularly with regard to search and harvesting. Moreover, we have identified a first set of use cases for specific types of ESS data that complement the developed recommendations, e.g. underway measurements of seawater temperature. Through regular updates in the form of community consultations and workshops, we will identify further community needs, as well as support updates and developments of metadata standards, e.g. the implementation of underway measurements in GeoDCAT. In this contribution, we will describe our recommendations, use cases, and lessons learned from the activities for a community-driven process to enable repository providers.